Times and Tech

Eliminate Your Fears And Doubts About Cybersecurity

noreply@blogger.com (Rishi Mishra) — Thu, 30 Jan 2020 19:58:00 +0000

Cyber-attacks are growing in severity and in numbers each year despite the best effort of security experts worldwide. Organizations small and large, government or non government are losing millions to bigger and bigger cyber-attacks. Wannacry, Notpetya, Melissa virus, Conficker, Shamoon are just a few out of a large list of successful cyber-attacks the world has seen. Cyber-attacks could be of more than one type, such as- Malware, Ransomware, Phishing, DDoS, Malvertising and Password attack. In this era of growing cyber-threat, significance of cyber-security is undeniable. Organizations are now spending millions on cyber-security to keep attackers at bay.

Source of cyber-attacks

A cyber-attack can be caused by an individual or a group of individuals such as a criminal hacker group. Cyber-attack could be state sponsored or can be caused by non state actors. Reason of a cyber-attack can also vary. It could be for money as in the case of ransomware attacks or it can be for crippling state infrastructure and utilities.

Types of cyber-attack

Malware: It stands for malicious software which is crafted to cause problems to a computer or network. A malware can be a virus or a worm or spyware, adware or trojan. Malware can infiltrate a system through a download or a malicious link or operating system vulnerabilities. Superfish adware, zeroaccess botnet, Cryptolocker trojan, Stuxnet worm are some of the biggest malware attacks that happened.

Ransomware: It is a type of attack in which the hacker gains access to the system and encrypts the data, and asks for money to decrypt it. Users of the system are effectively locked out. This type of attack can be very devastating if target is a critical utility. SimpleLocker, TeslaCrypt, NotPetya and WannCry are some of the biggest ransomware attacks.

Phishing: Cyber-criminals posing as a trusted third party send emails asking for username, passwords, Bank account details, credit card details and then use this data to carry out a theft or gain access to sensitive information. It is one of the oldest and most widespread form of cyber-attack. Users should be careful while reading emails and clicking on links to protect themselves against this form of cyber-attack.

DDoS: It stands for distributed denial of service attack. Multiple compromised systems as in a botnet are used by criminal hackers to flood a targeted server with traffic which overwhelms the system by using up all the bandwidth and system resources, leaving the server inaccessible to normal users. A DDoS attack can run for hours to days. Reason for a DDoS attack can vary from business competition to political. GitHub, CloudFlare and Spamhaus has suffered some of the biggest DDoS attack.

What is cyber-security

Cyber-security is the practice of keeping systems safe from cyber-attacks. Cyber-security is achieved through network security, application security, Information or data security and user training and awareness. Optimized people, process and technology is a pre requisite for successful deployment of cyber-security. Users must adhere to safe web practices such as carefulness about opening links and setting strong passwords and changing passwords regularly. Organizations must have well defined policy regarding cyber-security. Technology such as firewall, antivirus software, anti-malware must be competent and up to date.

Cyber-security in numbers

Cyber-security market will hit 300 billion dollar mark by 2024.

Cyber-attacks will cause 6 trillion dollar in damages by 2021.

A cyber-attack occurs every 39 second.

Nearly half of all cyber-attacks target small businesses.

Around 230,000 malwares are created by criminal hackers everyday.

US cyber-security budget was 14.98 billion dollar in 2019 and may increase to 17.44 billion dollar in 2020.

Ransomware attacks will cost about 20 billion dollar by 2021.

Importance of cyber-security

In the era of Internet of Things more and more everyday objects are getting equipped with an IP address through which they can communicate with other objects. Apart from raising convenience level for users, this also creates growing opportunity for cyber-criminals to find a security vulnerability and launch an attack. In this increasingly connected world cyber-attacks are getting increasingly disastrous. Cyber-security is more relevant today than ever before. Strong cyber-security practices is a must for trouble free function in the world we are living today.

References:

1) https://www.cisco.com/c/en/us/products/security/what-is-cybersecurity.html

2) https://us.norton.com/internetsecurity-malware-what-is-cybersecurity-what-you-need-to-know.html
3) https://www.cpomagazine.com/tech/11-eye-opening-cyber-security-statistics-for-2019/

Things You Probably Didn't Know About Internet Of Things

noreply@blogger.com (Rishi Mishra) — Wed, 29 Jan 2020 18:42:00 +0000

Devices with embedded sensors and ability to gather and exchange data over an Internet connection are steadily rising in numbers. Everyday objects such as your toaster, refrigerator, car, electric lamp, alarm, wristband, watch etc. can now send and receive data through an Internet portal. By 2025, there could be around 75.44 billion connected devices around the world according to Statista.com. A common Internet of Things platform brings together the data devices send, analyses this data and extracts meaningful information which is then used to trigger meaningful action in a secure manner. This is how Internet of Things work.

What is Internet of Things platform

Diverse connected devices or things require a common language to securely communicate with each other. Internet of Things platform is a technology which makes that possible apart from data analytics and derivation of actionable intelligence from the device data. It makes use of cloud technology to securely receive and send data to various connected devices. IoT platform also provides tools for developing applications for IoT hardware. Number of IoT platforms is rising with rising number of IoT devices.

Stats about Internet of Things

Internet of Things or IoT device market could reach 1.1 trillion dollar by 2026.

There could be 3.5 billion cellular IoT connections by 2023.

IoT Market will attract 15 trillion dollar in investments by 2025.

IoT Management market could reach 16.86 billion dollar by 2025.

Global spending on IoT could reach 1.29 trillion dollar by 2020.

IoT Will add 10 - 15 trillion dollar to global GDP by 2030.

75% Of new cars will come with built in IoT connectivity by 2020.

Internet of Things and Cyber-security

IoT technology makes life more convenient but at the same time it is increasing opportunities for hackers and cyber-criminals. Every connected device is a potential target and can become a point of network vulnerability. Cyber-security should be the first thing in mind while purchasing an IoT device. Usually manufacturers don't make their devices secure enough. A not properly secured IoT device could be used by hackers to breach network and hold the entire system for ransom. The increasing number of cyber-attacks is a signal to manufacturers to make their products with advanced security features.

A Use case of Internet of things

You are awaken in the morning by your smart alarm. The smart alarm doesn't just wakes you up, it also signals the coffee maker to start brewing coffee and curtains to fold up. It signals the geyser to turn on, so by the time you enter shower, hot water is ready. The geyser can signal your smart toaster to turn on and electric vehicle to start charging so that by the time you are all set it is ready to take off. Your smart camera senses your absence and signals smart doors to lockup and thermostat to turn off. This is an example of how IoT makes life easy, but it can also be used by hackers to make life difficult, if the security is not competent enough.

References:

1) https://www.ibm.com/blogs/internet-of-things/what-is-the-iot/
2) https://www.iotforall.com/what-is-iot-simple-explanation/
3) https://www.visioncritical.com/blog/internet-of-things-stats
4) https://financesonline.com/iot-statistics/

How Industry 4.0 Is Transforming Industrial Production

noreply@blogger.com (Rishi Mishra) — Fri, 21 Jun 2019 09:37:00 +0000

A wave of new technologies such as cloud computing, 3d printing, robotics, artificial intelligence and internet of things has brought forth what is widely addressed as the 4th industrial revolution. Industries are using these new technologies to become more productive and efficient. Industry 4.0 is changing the world economy as it enables production of personalized goods closer to market.

IoT and IIoT

Network of interconnected devices is known as internet of things. When each device and machine in an industry is interconnected through a portal, we have what is known as industrial internet of things or IIoT for short. One simple way to achieve IIoT is to provide each device an IP address and then interconnect the devices using this IP address. IIoT makes it possible to get wide range of data for efficient automation and control of plant machinery thus raise productivity while cutting cost.

Cloud Computing and Industry 4.0

Cloud computing makes it possible to access data and computing power from any suitable device with Internet connection. With cloud computing, workers can access information and execute control operations remotely. Cloud solutions make way for faster innovation. Cloud is more secure and saves money.

Artificial Intelligence and Industry 4.0

Machines with artificial intelligence are saving cost and improving production. More and more industries are employing intelligent machines in production lines for higher productivity. Algorithms derive meaningful insight from plant data. This insight is utilized to optimize processes. Machines capable of learning from experience are accomplishing many tasks that previously required human hands. Machines are now capable of facial recognition, natural language processing, obstacle avoidance, autonomous driving, autonomous movement and much more.

3D Printing and Industry 4.0

The process of additively manufacturing a 3d product or component using a 3d printer and a 3d digital model is referred as 3d printing or additive manufacturing. Different type of 3d printers can be used to produce different type of product. For example, a plastic printer can be used to make plastic products and a metal printer can be used to make metallic products. 3D Printing makes it possible to produce highly customized end products. Here is a short list of different types of 3d printers-

1) Fused deposition modeling (FDM)

2) Stereolithography(SLA)

3) Digital Light Processing(DLP)

4) Selective Laser Sintering (SLS)

5) Selective laser melting (SLM)

6) Laminated object manufacturing (LOM)

7) Digital Beam Melting (DBM)

Robotics and Industry 4.0

Robots have become a key element of modern industry. There are collaborative robots that work with humans and there are stand alone robots. Robots have taken over much of the work in a number of fields ranging from automotive to agriculture. AI Powered robots are welding joints, assembling parts and weeding farms. Robots with advanced machine learning algorithms are learning from past mistakes thus becoming more precise and efficient at their tasks.

Engineers are using augmented reality to visualize their designs in 3d, collaborate and communicate better. Industry 4.0 is present and future. With these new technologies industry is aiming to become more autonomous, climate friendly and sustainable, cut cost and waste while raising productivity and efficiency. In future we will see more inclusion of new technologies in production.

References-

1) https://interestingengineering.com/the-industrial-revolution-40-and-its-possibilities-revealed

2) https://www.researchgate.net/profile/Rainer_Schmidt/publication/274894802_Industry_40_-Potentials_for_Creating_Smart_Products_Empirical_Research_Results/links/552beaa00cf21acb091ec04d.pdf

3) http://www.scielo.br/scielo.php?script=sci_arttext&pid=S1807-76922018000400100

4) https://www.seebo.com/industrial-ai/

5) https://proto3000.com/industry-4-0/additive-manufacturing-perspectives-in-industry-4-0/

What Is Artificial Intelligence And How Its Changing Our World

noreply@blogger.com (Rishi Mishra) — Fri, 17 May 2019 07:52:00 +0000

Machines capable of learning, reasoning, self correction are known as intelligent machines having artificial intelligence. In short machine intelligence is Artificial Intelligence. Artificial Intelligence is achieved through hardware that resembles human brain as in neuromorphic computing. IBM has developed a brain inspired architecture using neurosynaptic cores. Most machines today are based on Von Neumann architecture. To achieve machine intelligence researchers are combining Von Neumann architecture with neuromorphic architecture. The Von Neumann architecture activity is measured in Flops while neuromorphic architecture activity is measured in sops or synaptic operations per second. Neuromorphic architecture simulates the working of neurons using neural networks. This helps researchers achieve amazingly high computing ability than traditional computers at lesser energy consumption as demonstrated by IBM true north board and Intel's Loihi board. Memristors also are used to achieve cognitive computing in machines or machine intelligence.

A concise history of AI

Concept of artificial intelligence has existed for 1000s of years. The term 'Artificial Intelligence' became official at 1956 Dartmouth Summer Research Project. John McCarthy and Marvin Lee Minsky are the Founding fathers of modern artificial intelligence. The Dartmouth conference also outlined 7 original aspects of artificial intelligence. They are-

1) Automatic computers

2)How computers can be programmed to use a language

3)Neural nets

4)Ability to measure the complexity of a problem

5) Abstraction

6) Self improvement

7) Randomness and creativity

Jeff Hinton is yet another prolific researcher in this field who kept working on developing AI through thick and thin. Research on artificial intelligence boomed from 1956 to 1974 with lots of funding and researchers taking interest. The period from 1974 to 1980 is known as first AI winter. Money stopped flowing and researcher interest waned due to lack of computing power and data. Period from 1980 to 1987 is known as second AI boom. During this period expert systems rejuvenated researcher interest. Hopfield net was created. Period from 1987 to 1993 is known as second AI winter. From 1993 onwards AI research and development exploded. Now a days we have deep neural nets, natural language processing and facial recognition working seamlessly.

Artificial Intelligence, Machine Learning and Deep Learning

A machine is called intelligent if it shows cognitive capabilities such as learning and problem solving. AI can be subdivided into narrow AI, general AI and strong AI. When the machine is better than humans in a specific task, it is called narrow AI. When the machine shows human like intellectual capabilities, its general AI. When the machine is better than humans in intellectual tasks, its strong AI.

Machine Learning is a subset of Artificial Intelligence. It is the ability of a computer to analyze a large set of data and learn from it . Using machine learning algorithms, computers can learn to accomplish a task without being programmed for it.

Deep Learning is subset of machine learning. It teaches computers to learn by example. Deep Learning is how driverless cars recognize a stop sign or other cars on road. Data is fed into neural networks in order to learn the characteristics of an object and thus identify it.

Supervised Learning, Unsupervised Learning and Reinforcement Learning

Supervised Learning, Unsupervised Learning and Reinforcement Learning are types of machine learning. When the machine learns under guidance using labeled data, it is called supervised learning. When the machine learns without any guidance using unlabeled data, it is called unsupervised learning. Reinforcement learning is a type of machine learning in which an agent interacts with its environment in order to maximize the chance of a reward. Regression and classification problems can be solved using supervised learning. Association and clustering problems can be solved using unsupervised learning. In case of reinforcement learning the input depends on action taken, there is no predefined data. Supervised learning can be used to forecast sales. Unsupervised learning can be used for anomaly detection. Reinforcement learning is used to make driverless cars and gaming agents.

What is Automated Machine Learning or Auto ML

If machine learning is applied to real world problems automatically, it is identified as automated machine learning. Using traditional machine learning methods to solve real world problems is time consuming and challenging. Auto ml makes machine learning simple to use through sophisticated algorithms capable of fetching most relevant information from data set. Not everything is yet automated though. Some human expert may still be required for a successful deployment and running.

What is AI bias?

AI systems are only as good as the data they are trained on. Bad data may result into a biased AI. Algorithms created by biased individuals may show bias when used to solve problems. Bias can enter into AI system at many stages such as understanding the problem, collecting data and preparing data. More than 180 human biases have been identified. Biases can cause trust deficit between man and machine. Good thing is it can be tackled using specific methods. Identifying and solving AI bias is essential.

Future of AI and applications

AI is predicted to write a high school essay by 2026. By 2028 it will be able to generate a creative video. By 2049 it will be able to write a new york times best seller book. By 2050 it will become able to compete in a standard math competition and by 2059 it will be smart enough to conduct math research. List of AI applications is huge. AI is finding applications in transport industry, manufacturing and agriculture. It is also used to create new tech experiences. Offices worldwide are employing AI solutions for higher productivity. It is estimated to add $16 trillion to global economy by 2030. Its predicted to create more jobs than number of jobs it will eradicate. Future seems bright for artificial intelligence.

Reference:

1)https://www.britannica.com/technology/artificial-intelligence
2)https://futureoflife.org/background/benefits-risks-of-artificial-intelligence/?cn-reloaded=1
3)https://www.tutorialspoint.com/artificial_intelligence/artificial_intelligence_overview.htm

7 Amazing Facts About James Webb Space Telescope

noreply@blogger.com (Rishi Mishra) — Sun, 12 May 2019 13:45:00 +0000

1) James Webb Space Telescope will help astronomers and cosmologists get higher resolution images of distant galaxies and star systems. JWST is the advanced successor of Hubble Space Telescope. It is named after NASA's second administrator James E. Webb.

2) JWST is primarily an infrared observatory designed for near to mid infrared range. For this purpose a large solar shield made of five sheets of silicon and aluminum coated Kapton will keep JWST mirror and 4 science instruments below 50K(-220 degree C) .

3) Primary mirror of this space telescope is made of 18 gold coated beryllium mirror segments. The mirror segments are hexagonal in shape. At a diameter of 6.5 meter, this telescope is much larger than Hubble space telescope.

4) The Integrated Science Instrument Module or ISIM for short holds four science instruments, the near infrared camera, the near infrared spectrograph, the mid infrared instrument, the fine guidance sensor and near infrared imager and slitless spectrograph and a guide camera.

5) The ISIM provides electrical power, computing resources, cooling capability and structural stability to the Webb telescope. It is made of bonded graphite epoxy composite connected to underside of telescope.

6) Webb telescope planned launch date is March 30, 2021 on Ariane 5 rocket. It is a collaboration among NASA, European space agency and Canadian space agency. Primary mission time is 5 years, extendable to ten years at second lagrange point.

7) Northrop Grumman Aerospace Systems is the primary contractor responsible for building the spacecraft. NASA's Goddard Space Flight Center is leading the project. Ball Aerospace is subcontracted to build the optical telescope.

Reference:

1) https://en.wikipedia.org/wiki/James_Webb_Space_Telescope#Infrared_astronomy
2) https://www.jwst.nasa.gov
3) https://www.space.com/21925-james-webb-space-telescope-jwst.html

How Brain Machine Interface Is Changing The Way We Interact With Machines

noreply@blogger.com (Rishi Mishra) — Sat, 11 May 2019 14:38:00 +0000

Research on brain machine interfaces is going on since 1970s. A brain computer interface makes it possible to control a machine such as a robotic arm by thinking about it. Electrodes placed directly on the brain through surgery or those placed on the head can be used to collect brain signals which is then used to trigger control commands through a computing machine. Brain signals are used to create an electroencephalogram or EEG which means electric brain picture.

Types of Electrodes

Electrodes measure potential difference between neurons. Charged particles move between neurons in response to external stimuli. This movement of charged particles creates potential difference. This signal is amplified and applied to a computer in order to control a machine. Electrodes can be of direct type and non invasive type. Direct type electrodes provide better signals than those which are worn overhead. Non invasive electrodes are of dry type and gel based. Again gel based electrodes work better than dry electrodes. Dry electrodes are however more convenient to use. Researchers are coming up with high sensitivity dry electrodes for brain machine interfaces.

Developments in the field

Brain computer interface research gradually moved from animals to human subjects, over the years. Researchers at DARPA have done much work in direct neural interfaces which allowed them to help paralyzed person control a robotic arm and play a video game using thoughts in brain. DARPA also demonstrated that sensors can be used to help a paralyzed person feel the touch on a prosthetic or robotic arm. Such sensors can also be used to help a blind person experience vision without using eyes.

Companies and institutes active in the field

Research and development of brain computer interface is going on at several universities across the world such as University of Miami and University of California. Several companies are working on launching commercial BCI devices such as Neuralink and Emotive. Emotive is a headset which can be used to control toys or play a game on computer. Justin Sanchez who is currently with DARPA and Polina Anikeeva at MIT are two prolific researchers in this field.

Future of brain machine interface technology

In future paralyzed people will be able to control a humanoid bot or an exoskeleton in order to accomplish simple tasks. People will also be able to work with a computer, browse the Internet and communicate with others using their brains alone. Brain to brain communication is yet another possibility. In short people will become able to run most machines just by thinking. Possibilities for this technology seem endless.

References:

1) https://www.nature.com/subjects/brain-machine-interface
2)https://towardsdatascience.com/a-beginners-guide-to-brain-computer-interface-and-convolutional-neural-networks-9f35bd4af948
3)https://www.techworld.com/tech-innovation/we-spoke-some-neuroscientists-about-computer-brain-interfaces-3691918/

Our Future With Robots Will Be Amazing And Here Is Why

noreply@blogger.com (Rishi Mishra) — Tue, 23 Feb 2016 03:00:00 +0000

Robots have started to cook and clean for us and are assisting us in our day to day lives. Industrial robots have been assembling parts and manufacturing materials for a long time now. In healthcare, robots have started performing surgeries. Bots and drones are delivering packages. Military has been extensively using robots for diffusing bombs, for surveillance and for vigilance. Autonomous tractors are tilling and ploughing farms. Robots are appearing in almost every field with abilities that seem to grow every day. With artificial intelligence they are beginning to show some cognition as well, like Honda's ASIMO which can remember names, faces, take simple orders and execute them.

We have been thinking about machines that can move about themselves and do things for as far back as ancient times. In around 400-350BC, Archytus of Tarentum built a mechanical bird that can fly. "If every tool when ordered or even of its own accord could do the work that befits it then there would be no need either of apprentices for the master workers or of slaves for the lords." Aristotle supposedly said that in 320BC. Two texts- Pneumatica and Automata which talks about building automatic machines, are attributed to ancient Greek engineer Hero of Alexandria. We find the mention of mechanical giants in ancient Greek texts. Leonardo Da Vinci built a Robot that can swing its arms and move its jaws, in around 1495. Tanaka Hisashige made Karakuri dolls in 1800s. These dolls were capable of drawing arrows from a quiver and shooting them. They could also be used for serving tea and were very popular among Japanese aristocracy.

Word 'Robot', taken from an old Slavic word 'Robota' meaning compulsory labor, was first used by Czeck writer Karel Capek in his play Rossum's Universal Robots. The play was about a society that build robots to serve them, but gets enslaved by the robots afterwards. Later in 1942, word 'Robotics' was used by Issac Asimov in his story 'Runaround', which also included his three laws of Robotics. Later he added Zeroth law saying- a robot may not injure Humanity or by inaction allow Humanity to come to harm. George Devol made a Robot in 1954 which was programmable. He Sold this robot to General Motors in 1960. General Motors became first company to use a robotic arm in its production line when it installed this robot called 'Unimate' in its Trenton, New Jersey plant. Researchers at Stanford, MIT and world-over, continued to develop newer, better Robots, bringing us to the current age of humanoid bots like ASIMO and ATLAS.

In old times people made robots using springs and pulleys and gears. Developments in the field of Electrical and Electronics in 19th and 20th century brought us Electric motors, sensors and microprocessors. These are the components we use in building robots now. Going about building your own bot, first you'll need to decide what you want your bot to do. It can be an obstacle avoiding robot, or a cleaning bot or a walking bot like DARWIN. Next you will need to decide what it will look like. Make a sketch or draw it on computer. After that you will need to select material for robot's body and select components which you'll put into it. Usually, the components which you will be needing are main processor board like an Arduino or Raspberry, controller board like Arbotix Pro Robocontroller. Motors could be geared DC motors, stepper motors and/or DC servomotors, normally referred as actuators. After that you may need wheels and casters, linear actuators, specialty robot motors, Bluetooth module or WIFI module or Ethernet for communication.

Stereo cameras or a webcam can be used for vision. Large number of sensors are available such as accelerometers, gyros, LIDARs, light sensors, temperature sensors such as LM35, voltage and current sensors, gas sensors, ground sensors, position sensors such as rotary encoders and potentiometers, touch sensors, Ultrasonic sensors for sensing distance from objects. Hydraulic pumps and pipes and solenoid valves may be required for some designs. LiPo or VRLA Batteries will be required for power supply. Other than this, you are going to need data cables and wires with connector, LEDs and displays, I/O boards, Motor driver boards, glue and bolts and some hardware tools such as pliers and keys and screwdrivers. You can always search for a particular part on Google and select from a number of vendors. Next you will require to program the processor for which you can use a programming interface and load the program from your computer using USB connector. After that you will need to put all the components together using your schematic. Microprocessor uses the feedback from a number of sensors to drive motors and pumps of the robot to accomplish tasks that it was programmed to accomplish.

Accelerometer measures proper acceleration as a vector quantity in three dimension. Proper acceleration is acceleration relative to acceleration of the object in free fall. For the object under free fall, accelerometer will measure a value of 0m/s² and for an object sitting on ground it will measure a value of 9.81m/s² upwards. Accelerometer also senses orientation as it can sense the direction of weight. It can sense vibration as well as shock. Due to such properties, it is widely used in navigation system of aircrafts and spacecrafts and for balancing robots and to trigger safety mechanism in case of excessive shock or vibration. Accelerometer typically comprises of a spring mass system made of Piezoelectric, Piezoresistive or Capacitive sensor as spring and some mass with some damping medium such as a gas inside a housing. They are usually micro electromechanical systems or MEMS that can fit on a PCB. When the object accelerates, mounted accelerometer also accelerates creating displacement of mass which stresses the Piezoelectric crystal or Capacitive sensor causing a voltage change which can be calibrated to give acceleration reading.

Gyros are used to sense rotation. They can measure angular velocity and the feedback along with position sensor feedback can be used for rotating arms or torso of the Robot or for maintaining balance in conjunction with accelerometer feedback. They measure angular velocity in degrees per second. Rotating gyro resists any change in its axis of rotation which is why it can be used for sensing orientation. Stereo camera is used for getting 3D images of surrounding, serves as 3D vision for robots. LIDAR is used for creating a 3D map of environment by shooting pulsed laser. It gives distance of objects around which is utilized by the processor in navigating the robot to tasks. It consists of laser, scanner and a receiver such as Silicon avalanche photodiodes. Ultrasonic sensors are also used to measure distance to nearby objects. It works by measuring time between transmission and reception of an ultrasonic signal. Current and voltage sensors are used with motors for precise speed control and protection. Temperature sensor gives temperature reading to the processor.

Honda started work on bipedal humanoids with prototype E0 in 1986. This was a slow walker taking 5s between steps. Researchers analyzed how humans and animals walk and run to get ideas and improved on their design. Next prototype E1 could walk at .25km/h. Model E2 was first to walk nearly like a human and could attain a speed of up to 1.2km/h. Model E3 could walk at 3km/h. Prototype E1, E2 and E3 were developed between 1987 and 1991. Next model E4 could perform quick walk at 4.7km/h. With more improvements prototype model E5 was made. E5 could walk autonomously. Engineers incorporated ground reaction control, target zero moment point control and foot planting location control to enable the robot to walk autonomously without falling. This was done to achieve more human like movement. Prototype E6 could balance itself on slopes or when faced with rough terrain. It could also walk on stairs without falling. After achieving reliable walking capability, engineers added torso, arms and head and first humanoid like prototype P1 was created. P1 could push carts. Prototype P2 (210kg) could maintain its balance when knocked. With improved sensors, software and body, P3 could walk faster, weighed less (130kg) and appeared more not like a science experiment at 1.57m. Development of P1, P2 and P3 was carried out between 1993 and 1997.

Engineers continued to research and improve on their work. On Nov 20, 2000 they presented ASIMO, standing for advanced step in innovative mobility. This humanoid robot was 1.2m tall and had abilities like intelligent real time flexible walk featuring predicted movement control. ASIMO was able to walk and turn more smoothly than earlier prototypes. By 2002, they had a more improved version able to recognize faces, postures and gestures, different sounds, objects under motion and surrounding environment. By 2005, ASIMO was able to carry beverages. Equipped with new posture control system, it was able to run at 6km/h in circular pattern. Height was slightly increased to 1.3m. Software was further improved to let ASIMO move more gracefully with the help of visual sensor, ground sensor and ultrasonic sensor. Ability to avoid obstacles was also improved. By 2007, ASIMO could recharge itself on sensing low battery using specially developed charging station. Two or more ASIMOs could work in collaboration now. They also added the ability to give way to people passing through.

ASIMO had a higher degree of autonomy by year 2011 as a result of continued improvements. The new ASIMO could determine its behavior based on information gathered with the help of sensors, from surrounding people and objects. Some of the components used by ASIMO are- lightweight but reliably strong Magnesium alloy body, gyroscope and accelerometer, 6 axis force sensor, joint angle sensor, 6 ultrasonic sensors in midsection, brushless DC servomotors and harmonic drive speed reducer, battery, IC communication card, floor surface sensors in feet. Some of the people involved in development of ASIMO are chief engineer Masato Hirose and project leader Satoshi Shigemi. Honda team has done an awesome job and they are not finished yet.

Apart from ASIMO, many other developers have created amazing bots. UCLA Professor Dr. Dennis Hong is using DARWIN as a research platform to develop working humanoids. ATLAS is a humanoid developed by Boston based company Boston Dynamics, primarily for disaster relief ops such as search and rescue . As of February 2016, ATLAS can open and push a door to let itself out, maintain balance on rough snowy terrain and get up by itself when knocked down. It can maintain balance on a narrow beam of wood for considerable amount of time. It can also lift a heavy box and place it on shelf. ATLAS uses hydraulics for its movements, a stereo camera and a side camera for vision, a LIDAR for sensing its surrounding and gyros and accelerometer for orientation and balance. HRP 4 is a humanoid bot developed jointly by KAWADA Industries and AIST Japan. HRP 4 can walk, move its arms and legs in sync to make gestures and lift up to .5kg with its 5 fingers. NAO is a biped bot developed by Aldebaran Robotics of Paris, France. Bruno Maisonnier is the CEO. NAO can speak with coordinated gestures, tell jokes and stories and can even dance using pre programmed moves. It can get up on its own if pushed over. NAO uses 2 HD cameras for vision, four microphones, nine tactile sensors and eight pressure sensors among many other.

Under social robots we have Zenbo from ASUS, Tapia from MJI Robotics Japan, Aido from Aidorobotics and Jibo from Jibo Inc. For military purposes there is MQ-9 Reaper and MQ-1 Predator from General Atomics Aeronautical Systems, Packbot from IRobot, Massachusetts, TALON from Foster-Miller, Massachusetts and DRDO Daksh. Packbot and DAKSH are bomb diffusing bots used by armed forces and law enforcement. New Holland has developed an autonomous tractor for farm automation. Swiss company Sensefly makes eBee SQ drones which are used by farmers to watch over crop health. AgEagle is another drone that can watch over crops. Da Vinci series of surgical robots from intuitive surgical are remotely operated and have been performing surgeries for close to a decade. Smart Tissue Autonomous Robot or STAR did a better job sewing up a pig's small intestine than human surgeons. Amazon is testing delivery drones in order to deliver packages in under 30 minute. Food companies in UK and USA are testing autonomous delivery vehicles. YuMi from ABB, Baxter from Rethink Robotics and Nextage from Kawada Robotics, Japan are some of the industrial robots in use. We even have fully automated lights out factories like IBM's keyboard assembly factory in Texas.

After the disaster at TEPCO's Fukushima Daiichi nuclear power plant following the failure of emergency generators due to tsunami on March 11, 2011, many were hoping robots will come to rescue. None were up to task except for Packbot. Plant was dangerously radioactive for any human to enter. Packbot was sent in to take images of damage. At Osaka conference held in November of 2012, DARPA program manager Gill Pratt announced DARPA Robotics Challenge to encourage teams from around the world to build disaster rescue humanoid bots. DARPA was to provide funding of up to 4 million dollars to 8 teams coming up top in trials. To win the challenge, a humanoid had to complete 8 tasks in shortest time under disaster like scenario which included failure of wireless communication between bot and operator. The tasks included driving a vehicle, stepping out of the vehicle, walking on debris, opening door, going up stairs, turning on a drill and cutting through wall, opening a valve and a surprise task. 16 teams participated in trials dominated by team SCHAFT of Japan. Following the trials, SCHAFT inc. was acquired by Google and the team withdrew from finals. Their humanoid S-one was equipped with compact liquid cooled motors allowing for higher currents and therefore higher torque.

25 Teams competed in finals held at Fairplex, LA county fair grounds on 5th and 6th June 2015 for the top prize of 2 million dollars. Of these were, team MIT, team Tartan Rescue from Carnegie Melon University, Team KAIST from South Korea, team Robosimian from NASA JPL and team IHMC robotics from IHMC, Pensacola Florida. Team MIT and team IHMC were using ATLAS. Prof. Russ Tedrake of team MIT had given his ATLAS as much autonomy as he can. Due to a small glitch the robot tried to step out of the vehicle while pressing throttle and fell down, breaking its right arm. Dr. Jerry Pratt led team IHMC. Jerry has been working on bipedal robots for more than 20 years, developing a sophisticated walking software. Team IHMC ATLAS also fell while walking over debris but without causing itself any serious damage. Repairs and error compensations were done overnight and the bot was able to finish all 8 tasks in second run. Team Tartan Rescue competed with their robot 'Chimp' which was the only bot to get up on its own after falling. Chimp with its motion planning ability was also able to complete all 8 tasks. Brett Kennedy of NASA JPL was leading team Robosimian. They competed with the quadruped bot Robosimian.

Team KAIST was led by Prof. Jun Ho Oh. After a disappointing performance in trials, Jun Ho Oh thought up some improvements to give their robot HUBO an edge. He put wheels at HUBO's knees and casters at its toes which allowed it to move forward while kneeling, increasing its chances of completing the tasks without falling. HUBO Could rotate its torso. Because of the air cooling system, the 33 motors in the robot could draw more current than rated, allowing it to be more powerful and faster. They put a supercapacitor system for emergency power to keep the bot balanced and communication up in case of main power failure. HUBO was able to complete all 8 tasks faster than other bots, claiming first prize. Team IHMC Robotics came second with a clock of 50:26 and was awarded 1 million dollars. Team Tartan Rescue came in third with a clock of 55:15 and received 500,000 dollars.

Graphene is a honeycomb like 2 dimensional hexagonal lattice of Carbon atoms. It is 100-300 times tougher than steel yet extremely lightweight at .77mg/m² and flexible. It is the best conductor of electricity and heat we have. It shows nonlinear diamagnetism, allowing it to levitate over suitable magnets. It is almost transparent and can be used to make semitransparent electronics. It can absorb light and has possibility to be used in solar cells. Continued research have shown that Graphene can be used in making classical and quantum transistors as well. Graphene can also be used to make best quality barriers. Due to such awesome properties, researchers are keenly pursuing ways of using it in building better bots. One possibility is using it as replacement for Silicone. It can also be used to make flexible, lightweight and extremely tough structure for robots. With Graphene actuators, future bots may become faster, more powerful and highly flexible. With Graphene as covering, they may also be able to harness sunlight for all their electrical power needs.

Quantum computing presents even higher possibilities for robots of future. Quantum processors equipped with sophisticated quantum algorithms can figure out global weather patterns, design stable new molecules or simulate human brain patterns. Robots equipped with quantum AI may be able to make decisions in real time factoring in huge amount of information from their surrounding, bringing them further close to human like behavior. Equipped with such abilities, robots of future may be able to carry out decision intensive tasks making their integration with human environment look even more natural. They are already taking over restaurant and fast food jobs. Zume Pizza of Mountain View California uses robotic chefs and Eatsa is a highly automated fast food joint operating in San Francisco. Autonomous trucks and cars are taking over driving jobs. Google and Uber already have working autonomous vehicles and others are coming along fast. Robots are taking over the jobs of doctors, lawyers and accountants as well. They are increasingly being used for dangerous and dirty works in factories and laboratories. Robotic soldiers are poised to reduce the number of serving personnel. New technology brings new kind of jobs. There will be other type of jobs. People will have to just train accordingly. Future served by robots looks safer and more convenient. It's going to be awesome.

References:

1) http://world.honda.com/ASIMO/technology/index.html

2) http://www. ancient-origins.net/ancient-technology/steam-powered-pigeon- archytas-flying-machine-antiquity-002179

3) https://learn.sparkfun.com/tutorials/gyroscope

4) https://learn.sparkfun.com/tutorials/accelerometer-basics

5) https://www.technologyreview.com/s/538136/a-transformer-wins-darpas-2- million-robotics-challenge/

Image credits goes to respective sources.

5 More Secure Alternatives to Login Password

noreply@blogger.com (Rishi Mishra) — Thu, 11 Feb 2016 05:17:00 +0000

Logging into your account has become easier now with biometrics finding its way into Laptops and Smartphones. Alphanumeric login passwords are hard to remember, hard to enter and easily compromised, which is why biometric passwords are gaining preference among tech organizations and users. Of many biometric technologies, most popular are fingerprints, iris scans, facial scans and vocal patterns. Apart from these, other more secure methods include two factor authentication and multi factor authentication which are already in wide use but involve a bit more hassle than biometric techniques.

Finger print scanners first appeared in laptops. Now they are common in Smartphones. You can swipe or press your finger against the scanner for authentication. Scanner reads the pattern of ridges and lines using optical sensors, capacitive sensors or ultrasonic sensors, to create a digital copy through a dedicated onboard IC. This copy is then compared with a template stored in a secure area of main processor. In most cases minutiae which are short ridges or points where ridges end or split in two are compared for a match, making process faster and more efficient. Optical sensors take a 2D image of finger print using a camera and LED light and can be easily fooled. Capacitive scanners record the variation in their stored charge as a finger print is scanned which is then converted into a unique digital copy which is extremely tough to imitate. Ultrasonic sensors are even better as they use ultrasonic transceiver to create a detailed 3D print. Apple’s touch ID makes use of capacitive sensors.

Voice patterns are in use as password since a long time, mainly at big banks and large corporations. Now the technology is coming to smartphones and other daily use gadgets. A voice pattern is first registered with the device in digital form detailing unique vocal characteristics of user. Person has to speak the registered password which is processed and compared with the stored template. This early form of voice authentication can be cracked by obtaining user’s speech style, which is why researchers are developing new techniques. In one of these techniques, developed by researchers at Carnegie Melon, user’s voice is converted into data strings and transmitted over the network, which is then used as password for authentication. For extra security, certain data of user’s smartphone is also added to the data string.

Unique facial characteristics of a person can be recorded by 2D or 3D sensors as digital template, which can then be compared each time for authentication. Selfie password tech works this way. User takes a selfie using his smartphone which is compared with template for unique facial characteristics. Process is hassle free, fast, secure and contactless which is why various payment apps including Amazon’s are using it as user authentication tool. Other services are beginning to deploy it as well. Facial recognition tech makes use of various recognition algorithms which are extremely tough to crack.

Iris is the colored circle around pupil of an eye. A person’s iris is unique and therefore can be used to authenticate him in a contactless, hassle free manner. An iris scanner is used to capture still image or video of user’s iris which is then converted into template data using custom algorithms. Each time, a user has to put his eye in front of scanner for authentication. This technology has been miniaturized and will be appearing in smartphones soon. A person’s iris doesn’t changes after 6 months from birth which makes it highly reliable for the purpose of authentication.

Google’s project abacus is about making a record of user’s characteristics such as the way he types, speaks, appears, his online behavior, what apps he uses, to authenticate him. It’s a form of multifactor authentication. Online services have been making use of two factor authentication for a long time. A user enters his password first and then receives a code on his phone, on entering which the authentication process is completed. This authentication method has been made mandatory for financial transactions in many countries. Many online services offer this option for enhanced security of user accounts.

References:

1) https://arxiv.org/ftp/arxiv/papers/1312/1312.7511.pdf

2) https://blog.kaspersky.com/google-projects-soli-jacquard-vault-abacus/9135/

3) http://www.intel.com/content/dam/www/public/us/en/documents/research/2014- vol18-iss-4-intel-technology-journal.pdf

4) https://www.technologyreview.com/s/523371/ces-2014-a-technological-assault- on-the-password/

Image credits goes to respective sources.

NASA's WFIRST Mission to Understand Dark Energy and Find Exoplanets

noreply@blogger.com (Rishi Mishra) — Fri, 29 Jan 2016 09:37:00 +0000

Wide Field Infrared Survey Telescope or ‘WFIRST’ is an infrared space observatory based on a design proposal for ‘Joint Dark Energy Mission’ between ‘Department of Energy’ and NASA. It formally became a NASA mission on Feb 17, 2016. Primary mission time is 6 years during which the mission will collect data for examining expansion history of Universe and growth of large scale structures to assess the effect of Dark Energy. It will also find exoplanets in Milky Way, in order to take forth the survey started by ‘Kepler Mission’. Exoplanets are planets orbiting stars other than our Sun. Exoplanet data will be analyzed for signs of other habitable worlds in Milky Way. Mission is set to be launched in mid 20’s making it NASA’s first space mission dedicated to understanding Dark Energy. It will be second such mission after ESA’s Euclid spacecraft.

‘WFIRST’ will have a 288 Megapixel wide field camera with HgCdTe focal plane array having 110 milliarcsecond pixels, operating in near infrared band (0.7-2.0 micron). Its field of view will be 100 times wider than that of Hubble Infrared Instrument. A grism will be integrated for wide field slitless spectroscopy and for small field spectroscopy it will be using an integral field spectrograph. Grism is a combination of Prism and Grating which allows a central wavelength to pass undeviated. With this wide field instrument, WFIRST will observe distant Supernovae, Weak Gravitational Lensing and Baryon Acoustic Oscillation to obtain data for understanding ‘nature of Dark Energy’.

Mission will also include a custom built, high contrast, advanced stellar Coronagraph for imaging exoplanets directly. It will work in the wavelengths of (0.4-1.0) micrometer and will also provide spectra of planets. Coronagraph, invented by French Astronomer Bernard Lyot in 1939, suppresses starlight using masks, mirror and lenses. It blocks the light from Star while allowing light from surrounding sources to pass, which enables it to see planets which are otherwise not visible due to overwhelming brightness of their host Star. Mission will observe Gravitational Micro Lensing signature of planets which is brief brightening of Stars due to a passing by planet, to detect exoplanets.

WFIRST will be able to look as far as HST with the help of its 2.4m primary mirror Anastigmat Telescope and with its integrated Wide Field Instrument, will have a field of view 100 times wider than HST. Mission will launch on an Evolved Expendable Launch Vehicle or ‘EELV’ from Cape Canaveral to Sun-Earth L2 Halo Orbit with a launch mass of 4166 Kg. Spacecraft will operate in near infrared and visible bands. Data will be transmitted to Earth station in Ka band. Project is managed from Goddard Space Flight Center ‘GSFC’. GSFC also supervises work on system integration, spacecraft bus and wide field instrument. Stellar Coronagraph and Telescope is managed by Jet Propulsion Laboratory ‘JPL’. Space Telescope Science Institute, as a partner, will be concerned with data processing, data analysis and data archiving. Neil Gehrels chairs the Formulation Science Working Group with deputy chairs David Spergel and Jeremy Kasdin. Gehrels is also the Project Scientist and Kasdin the lead scientist for Coronagraph. David Spergel and Jeremy Kasdin are Princeton University professors.

Coronagraph’s ability to provide high contrast images of exoplanets in habitable zone of Planetary Systems is in doubt which has led to discussions on including a Starshade in the mission. Starshade is a giant screen about the size of a baseball field and of the shape of a Sunflower with paper thin petals. This foldable screen can be loaded on a rocket and transported about 50000 km directly ahead of the Telescope, where it can be unfurled and deployed. It works by blocking Starlight and supposed to help in obtaining much higher contrast images of exoplanets than a Coronagraph. Because it can help provide desirable quality images of exoplanets in habitable zone of Planetary Systems, a Starshade is highly desirable by Scientists but the technology is not fully tested and NASA budget cannot support a speedy development right now. In a better scenario, both Coronagraph and Starshade should be in the mission as their function is complementary.

References:

1) https://wfirst.gsfc.nasa.gov/

2) https://exoplanets.nasa.gov/resources/1015/

3) https://arxiv.org/ftp/arxiv/papers/1411/1411.0313.pdf

Image credits goes to respective sources.

Amazing Things to Know About ESA's Euclid Dark Universe Mission

noreply@blogger.com (Rishi Mishra) — Thu, 28 Jan 2016 12:49:00 +0000

I. Euclid Dark Universe Mission, named after Greek Mathematician ‘Euclid’, known as Father of Geometry, is first space based mission dedicated to collect data for understanding Dark Matter and Dark Energy, led by European Space Agency, ESA. Euclid spacecraft will look as far back in time as 10 billion years. In Astronomy, it is known as look back time. A Look back time of about 10 billion years is equivalent to observing objects with redshift close to 2. Weak Gravitational Lensing and parameters related to Galaxy Clustering such as redshift, will be measured to infer insight into nature of Dark Matter and Dark Energy.

II. Euclid will operate for 6.25 years after its launch in last quarter of 2020. During that period, it will cover more than a third of extragalactic space which is equivalent to covering more than 15000 deg² of sky, excluding Solar System and Milky Way. The spacecraft will also peer about 10 times deeper, for 3 times during its operation, covering 40 deg² of space for calibration and performance monitoring purposes, during which it will be observing objects with redshift higher than 2, which includes distant Quasars and Galaxies. Euclid will cover about 10 billion objects, measuring weak gravitational lensing of more than 1 billion and redshift of about 50 million of them.

III. Thales Alenia Space, which is Europe’s largest Satellite manufacturer, headquartered in Cannes, France, is chosen to make the Satellite and its service module. Payload Module and telescope, which includes 1.2 m Silicon Carbide primary mirror, Korsch Telescope, covering an area of 0.5 deg² with a focal length of 24.5 m, will be built by Airbus Defenseand Space. Euclid Consortium which is an International Consortium of Scientists, will make very broad band R+I+Z filter, visible CCD imager- VIS, with pixel size of .1 arcsecond, near infrared, broad band Y,J,H filter Photometer- NISP P and a slitless Spectrograph- NISP S, with common field of view of .53 deg². Data will be collected by the Spacecraft using these instruments and will be sent to Earth at 855 Gbit/s in 4 hr daily slots in K band (25.5-27 Ghz). Onboard storage capacity will be more than 300 GB. The Spacecraft will have an exposure time of up to 4500 sec/field.

IV. Visible CCD detectors will be a mosaic of 36 (6×6), 4000×4000 pixel each, e2v charge coupled detectors, operating in visible wavelength (550-900 nm). They will be used for measuring shape of Galaxies. Near Infrared detector will be a mosaic of 4×4 Teledyne H2RG detectors, 2000×2000 pixels each, operating in (900-2000) nm wavelengths. It will provide low accuracy redshifts of over a billion galaxies using multicolor photometry and high accuracy redshifts of millions of Galaxies using Spectrometry.

V. Solar Panels will supply power and provide stability to orientation of telescope. Thermal Insulation will be done to protect against radiation heat. The Spacecraft will weigh 2100 kg and it will be 4.5 m long and 3.1 m in diameter. It will be launched to L2 Sun-Earth Lagrangian point- halo orbit using Soyuz ST-2.1B rocket from Kourou launch site, Guiana Space Center. Travel time to orbit is 30 days.

VI. Nasa is collaborating with ESA on Euclid Mission. From JPL Lab in Pasadena, California, NASA will put up infrared flight detectors for Euclid science instrument. Goddard Space Flight Center will be used for testing these detectors. Three US science teams totaling 40 scientists are nominated to add to planning and analysis of data.

VII. Dark Matter is the main contributor to Weak Gravitational Lensing effect of Galaxies as it constitutes most of Galactic matter content. A measurement of bending of light by Galaxies, therefore, gives information about the Dark Matter that it contains. By measuring this effect at this large scale and accuracy, scientists will try to gain additional insight into Physics of Dark Matter. Also, clustering of Galaxies is influenced by Dark Energy. A measurement of clustering is hoped to help in understanding the nature of this mysterious type of Energy.

References:

1) http://sci.esa.int/euclid/

2) https://www.euclid-ec.org/

3) https://arxiv.org/ftp/arxiv/papers/1110/1110.3193.pdf

Image credits goes to respective sources.

Dark Energy and Accelerating Expansion of Universe: Part 2

noreply@blogger.com (Rishi Mishra) — Tue, 29 Dec 2015 14:41:00 +0000

Click here to go to first part of this article

Supernovae were first explained by Caltech Astrophysicist Fritz Zwicky and his collaborator for few years- Astronomer Walter Baade, in their 1934 paper using recently discovered Neutrons. Term ‘Supernova’ was introduced by them. Zwicky and Baade argued that since Galaxies are extremely distant to one another, Supernovae must be releasing extremely high amount of energy to be observable. It is now known that Supernovae can sometimes be as bright as entire Galaxies for a couple of weeks. Zwicky envisioned that Supernovae will be used to survey Universe at extremely large distances. He found many Supernovae using wide view 18 inch Schmidt Telescope at Caltech’s Palomar Observatory, San Diego County, California, by looking for them during new moon. In total, he found more than 120 of them for which he also used 48 inch Schmidt at Palomar. Around that time, Cepheid variables were used as standard candle at large distances. At even larger distances, Hubble used brightest stars in Galaxies as standard candle, assuming them to be of same size and brightness which was disapproved in following years. In 1952, at Conference of International Astronomical Union in Rome, Walter Baade revealed that he had found two different types of Cepheid Variables in Andromeda galaxy. This called for a revision of Hubble’s earlier estimates in which he had considered, what turned out to be population2 Cepheid variables, as standard candle.

By 1941, Supernovae abbreviated as SNe, were classified into two types. SNe that didn’t have Hydrogen emission lines were called Type1 and those with Hydrogen emission lines were called Type2. By 1985, Type1 SNe were found to be of two subtypes. Type1 with Silicon absorption line at 6150Å were classified as Type1a and those without Silicon absorption line, were classified as Type1b. There is yet another subtype named Type1c. Type1a Supernovae occur when a white dwarf reaches 1.44 Solar mass, accreting matter from its companion star. 1.44 Solar mass limit is known as Chandrasekhar limit in honor of Indian-American Astrophysicist Subrahmanyan Chandrasekhar, who discovered it. Astronomers studied type1a SNe and found that their spectra and light curves were strikingly similar. Swiss Cosmologist Gustav Andreas Tammann and his student Bruno Leibundgut were among the first to notice this similarity. This raised hopes that Type1a can be used as standard candle at large distances. Further detailed study revealed some significant differences in their luminosity and light curve. Mark Phillips of Cerro Tololo Inter-American Observatory, after studying light curve of a number of low redshift Type1a, found that, brighter the Type1a, longer it takes to fade and fainter it is, faster it fades. This observation allowed physicists and Astronomers to know the peak brightness of a type1a with higher precision by observing its light curve- pattern in which it brightens and fades over time and gave them confidence to use type1a as standard candle.

Supernovae are very rare events, occurring a very small number of times in a Galaxy over a century. Type1a SNe are even more rare. This is why the need for automated search was felt. First robotic Supernova search was attempted by Stirling Auchincloss Colgate in 1970s, without much success. He was a Physicist at Los Alamos National Laboratory and Prof. of Physics at New Mexico tech. His project was a search for early Supernova in Galaxies with a remote controlled telescope in real time using an IBM 360-44 mainframe computer through a digital microwave link from the New Mexico Tech campus to the school’s Langmuir Laboratory. Later in mid 1980’s, Richard A. Muller, Prof. of Physics at UC Berkeley and Carlton R. Pennypacker, Astrophysicist at same institution, started ‘The Berkeley Real Time Supernova Search’ renamed as ‘The Berkeley Automated Supernova Search’. Muller’s group with their robotic telescope, fitted with new CCD detectors and latest computers, identified 20 Supernovae. They were the first to demonstrate the efficiency of automated supernova search. Muller’s graduate student Saul Perlmutter was a leading member of the team. In 1988, the group made a proposal to use their search technique to find distant supernovae. Goal was to measure deceleration parameter q₀ and reveal ultimate fate of Universe using distant Type1a SNe as standard candle. Mass density, expansion history and curvature of Universe was hoped to be found, as well. They faced constant funding problems. In 1991, Muller and Pennypacker handed the leadership to Perlmutter.

In 1986, Danish Astronomer Hans Ulrik Norgaard-Nielsen led a team at La Silla Observatory, Chile, to search for Type1a SNe at large distances. After two years, they only had one Type1a which was already past its peak brightness. This was a dampener for many Astronomers who were hoping to use distant Type1a for measuring cosmological parameters. Berkeley team continued its effort unabated. In 1988 Pennypacker and Perlmutter built a wide field imager for 3.9m Anglo-Australian Telescope at Siding Spring, Australia, to observe thousands of Galaxies in one go. For this they were allocated 12 nights of telescope time to look for distant SNe. Without a convincing search strategy during early years, team had difficulty securing telescope time. They had what is known as catch-22 telescope scheduling problem. They couldn’t get follow up time for obtaining spectra and light curve for a Supernova that may or may not be found and without prescheduled follow up time they couldn’t get time to look for Supernovae. Any search strategy required telescope time to demonstrate its effectiveness. With improved techniques, Berkeley team was successful in identifying its first candidate Supernova in 1992 using Isaac Newton Telescope in La Palma, Canary Islands. This was named SN 1992bi. In 1994, Perlmutter demonstrated that by taking images of adjacent patches of sky containing 10s of thousands of Galaxies just after a new moon and subtracting it from images of same patches of sky taken before next new moon about 29 days later, nearly a dozen new Supernovae could be found as new bright spots. Timing between two new moons ensures that most of the Supernovae found will be still brightening as it takes 21 days for a Type1a to reach peak brightness. After this, scheduling observation time on large telescopes at Keck, Cerro Tololo and Isaac Newton was easy as the team was able to make specific proposals and schedule follow up time with Hubble Space Telescope and other ground based telescopes to confirm findings. At this point the team had grown considerably as prominent Physicists and Astronomers from Institutes around the world joined in. The project was renamed ‘Supernova Cosmology Project’.

More distant SNe have higher redshift than near ones. Therefore same filter cannot be used to measure and compare their brightness to identify the type. Doing so will give incorrect result. This is known as K-correction problem in Astronomy. Light of Supernova is also dimmed by dust and gas in host Galaxy, making it even more difficult to identify their type correctly. SCP Team went about this problem by using correspondingly redshifted filters. By end of 1997, the team had analyzed data for 40 distant Type1a SNe. They found that the SNe were fainter for their redshift than one would expect from a decelerating Universe dominated by matter density. They were fainter, even for an empty Universe, leading them to conclude that expansion of Universe is not decelerating but accelerating. For the acceleration to happen a previously unknown form of energy density should be present in Universe and everyone’s first thought was Einstein’s abandoned cosmological constant, in a somewhat different sense. Cosmologist Michael Turner named it Dark Energy, in analogy with Dark Matter. Perlmutter presented the result first at a press conference sponsored by American Astronomical Society on Jan 8, 1998 in Washington D.C. and then next month in February at UCLA symposium on Dark Matter, in California.

Having heard about the success of Perlmutter’s team in finding Type1a Supernova at about 5 billion lightyears away in early March of 1994, Nicholas Suntzeff of Texas A&M and Brian Schmidt started talking about forming their own team to compete with Perlmutter’s. Newly formed ‘High Z Supernova search team’ had Suntzeff as its principal investigator. Later in 1996, Schmidt took over the leadership. Another leading member of the team was Adam Riess who was working on his doctoral thesis at the time and whose contributions proved crucial in team’s success. In 1993, Adam had worked with Harvard Prof. William Press on a method to reduce error in measuring Luminosity and distance of Type1a SNe, using data from Calan/Tololo survey. This method was called ‘Light Curve Shape’ method. Later, Adam improved this method by making use of filters of different color to reduce error caused by intervening dust. This new method was called ‘Multicolor Light Curve Shape’ method or MLCS for short. With the help of further improved MLCS, number of Type1a SNe required to make reliable calculation of expansion rate of Universe was greatly reduced. This helped in catching up with SCP team. Brian Schmidt wrote software required for automated calculations and was the one to find, team’s first high z Type1a.

By February 1998, the team had analyzed 16 high redshift Type1a SNe. Their calculations showed a negative matter density which couldn’t be possible. After working out the possibility of overlooked error, only logical conclusion was a negative deceleration parameter, which means an accelerating Universe. Their data was showing the same result as SCP team’s data. Supernovae were too faint for what would be expected from a decelerating Universe. Prof. Alex Filippenko of UC Berkeley, who had done most of the spectroscopic work for measuring redshifts, made the announcement at UCLA Symposium on Dark Matter in California in February 1998. Formal submission of result to ‘The Astronomical Journal’ came on March 13, 1998, in a paper titled ‘Observational Evidence from Supernovae for an Accelerating Universe and a Cosmological Constant’. High Z team was several months early than SCP team in formally publishing their result. Perlmutter, Schmidt and Riess were awarded The 2006 Shaw Prize in Astronomy. In 2011, they were awarded The Nobel Prize in Physics, which they split among their team members, making it clear that everyone's contribution was important in the discovery.

Members of both team continued to find SNe at even higher redshift. A new ‘Higher Z’ team was formed by including some new members with some members of old High Z team. Goal was to plot the expansion history of Universe using Type1a SNe that exploded when Universe was young. A comparison of change in redshift of these SNe with change in redshift of more nearby SNe, would effectively give clues about expansion history of Universe. By using the improved Hubble Space Telescope, they found 6 Type1a at redshift greater than 1.25, between 2002 and 2003. Data analysis showed that Universe was decelerating early on but after reaching a particular size during its decelerating expansion phase, started accelerating. A simple explanation is that- matter density dominated in early Universe, but with increasing size it grew weaker against Dark Energy density. Acceleration phase started when Dark Energy density started dominating the weakening matter density. In 2007, with new data from 23 Type1a SNe, this conclusion was confirmed by the ‘Higher Z’ team. This data also indicated that property of Dark Energy didn’t change over time. Another conclusion which came from data is- Density of Dark Energy doesn’t dilute with expanding space, which means, we are living in a Universe which will accelerate forever, taking Galaxies away from each other, ever faster.

Meanwhile Perlmutter and others have been promoting space based Supernova/Acceleration Probe Mission or ‘SNAP’ for getting better data to work with. This mission is now superseded by Widefield Infrared Survey Telescope Mission or ‘WFIRST’. Budget overruns on JWST mission has pushed dates for any Satellite mission for Dark Energy studies to mid 20’s. Ongoing Dark Energy Survey at Cerro Tololo Inter-American Observatory is supposed to provide valuable insight into nature of Dark Energy. European Space Agency is going ahead with ‘Euclid Dark Universe Mission’, which is expected to launch in December 2020. This spacecraft will map 2 billion Galaxies across more than a third of sky providing Astronomers with wealth of data to analyze. A new study by Adam Riess and his team using HST with its wide field camera 3 is indicating that Dark Energy may be growing in strength. Newly measured, expansion rate of Universe is giving a value which is about (5-9)% faster than what is measured from CMB data. They have submitted their paper about this study to arXiv on 5 Apr, 2016. The study will also appear in ‘The Astrophysical Journal’.

Theorists are hard at work trying to figure out Dark Energy. It has been put forth that Dark Energy is a property of space itself and doesn’t dilutes with its expansion and time for Universe to double in size remains same. But that line of thought now seems in jeopardy with the release of recent measurements by Riess and his team. Universe should double in size in about 9.8 billion years, according to these new measurements.

References:

1) http://adsbit.harvard.edu//full/2005ASPC..342...53K/0000053.000.html

2) http://www.astro.princeton.edu/~burrows/pub-html/papers/pnas201422666_7rt2gl.pdf

3) https://arxiv.org/pdf/astro-ph/9812133

4) https://arxiv.org/pdf/astro-ph/9805201.pdf

5) https://www.nobelprize.org/nobel_prizes/physics/laureates/2011/popular-physicsprize2011.pdf

Image credits goes to respective sources.

Dark Energy and Accelerating Expansion of Universe

noreply@blogger.com (Rishi Mishra) — Thu, 24 Dec 2015 14:09:00 +0000

Cepheid variables are stars whose luminosity/brightness increases and reduces with time. 18^th century Astronomers were well aware of such stars. In 1893, Harvard Astronomer Edward Charles Pickering (Jul 19, 1846-Feb 3, 1919) recruited a recent grad of ‘Radcliffe College’ then called- ‘the society for the collegiate instruction for women’ to work as a ‘human computer’ to analyze photographic plate collection of Harvard College Observatory to study these stars with variable brightness/luminosity. She was Henrietta Swan Leavitt (Jul 4, 1868 – Dec 12, 1921), daughter of a congregational church minister. While observing those plates, she noticed a pattern in some of variables. Brighter variables appeared to have longer periods than less bright ones. Leavitt used the method of trigonometric parallax to calculate distance to these Cepheids located in small and large Magellanic Clouds. She assumed all Cepheids in a Magellanic Cloud to be at same distance from Earth. With these distances she was able to calculate the maximum luminosity of stars from their observed apparent brightness or apparent magnitude in photographic plates using inverse square law.

B = L/(4πd²)

Where, B= Brightness of star measured using magnitude scale

L= Luminosity or energy output of star per unit time also known as

intrinsic brightness of the star measured in Suns

d= Distance from the star

Also, apparent magnitude m and absolute magnitude M can be linked as

M = m + 5 - 5logd

Where, d= Distance from star

Apparent magnitude m= Brightness as observed through telescope without atmospheric interference.

Absolute magnitude M= Apparent brightness of star at 10 parsec from

observer.

A star’s luminosity in Suns can be linked to its absolute magnitude M as

logL = -0.4M + 1.884

In Astronomy, Brightness is measured using a calibrated magnitude scale first created by Greek Astronomer Hipparchus in around 130-120 BC. SI Unit for apparent brightness is W/m² and is defined as measure of amount of energy coming from a star per unit area per unit time to Earth. Magnitude of two stars and their brightness b₁ and b₂ can be linked as

b₁/b₂ = 10^(2/5)(m2-m1)

When she plotted luminosity against period of each variable, the pattern was noticeable. Period of these variable stars was directly proportional to their maximum luminosity. She analyzed 1777 of these variables to come to her conclusion and published her result in ‘Annals of the Astronomical Observatory of Harvard College’ in 1908 titled ‘1777 Variables in the Magellanic Clouds’. After further study she gave confirmation to her initial conclusion in 1912. As Leavitt put it- “A straight line can readily be drawn among each of the two series of points corresponding to maxima and minima, thus showing that there is a simple relation between the brightness of the variables and their periods”. Leavitt’s plot is known as ‘period luminosity relationship’ or ‘Leavitt’s law’ and is used by Astronomers to determine absolute brightness/luminosity/magnitude of Cepheid, having obtained its period through telescopic observation.

Trigonometric Parallax method can be used to determine distance to stars which are up to 200 parsec or 650 light-years away. In this method, position of a nearby star is obtained either visually or photographically with respect to a background star further away. 6 months later, when Earth is at diagonally opposite point in its orbit around sun, position is obtained again. If the angle between the two lines of sight is 2p, distance of the star from sun is ‘d’ and distance between Earth and Sun is ‘r’, then

Tanp = r/d

From this,

d = r/(Tanp)

Distance of star from Earth will be

D = √(r²+ d²)

Here, p = parallax

r = 149 million km.

Parallax is a very small angle and is usually measured in seconds of arc. A star with parallax of 1 second of arc as observed from Earth is said to be at 1 parsec from Sun. 1 Second of arc or 1 arcsecond is 1/3600 of a degree. A parsec is equal to 3.0857×10¹³ km or about 19 trillion miles. Astronomical unit is distance between Earth and Sun and equals to about 149,597,870,700 meters. Yet another unit is a lightyear which is the distance light travels in a year and equals to 9.4607×10¹² km or about 6 million million miles. A parsec is about 3.26 lightyears in length. Appropriate unit is used in case of small and large distances.

Hipparchus classified stars he could see in night sky according to their visual brightness. He assigned a magnitude of 1 to the brightest stars and magnitude 6 to least bright ones. Ptolemy refined Hipparchus system in 140AD. This magnitude scale is still in use having modernized and improved from time to time. Galileo using his telescope introduced seventh magnitude star. In 1856, Oxford Astronomer Norman Robert Pogson (Mar 23, 1829-Jun 23, 1891) set first magnitude star to be 100 times as bright as sixth magnitude and established the logarithmic magnitude scale. In Pogson’s scheme, difference of one magnitude is same as brightness difference of (100)^1/5 which is 2.512- known as Pogson’s ratio. Pogson’s scale assigned Polaris a magnitude of 2. It was used as zero point of the scale. Later, on discovering that Polaris is slightly variable, Vega was used as standard reference with an assigned magnitude of 0, a standard still in use. Stars brighter than Vega are assigned negative magnitudes. Hubble space telescope could see stars up to a magnitude of 31. In late 19^th century, after the introduction of photography in stellar photometry, Astronomers found that some stars appearing similar in brightness to eye were differing on photographic plates. It was happening because photographic emulsions used on photographic plates were more sensitive to blue light than red. This led to the creation of photographic magnitudes denoted as m_p whereas visual magnitudes are denoted as m_v. Henrietta Swan Leavitt analyzed 299 plates from 13 telescopes to construct her logarithmic scale, spanning 17 magnitudes. Difference between star’s photographic and visual magnitudes is called ‘color index’ which is a measure of star’s color. Color index of blue stars came to be of negative value while that of yellow, orange and red stars is increasingly positive. Now days, magnitude is obtained using standard photoelectric photometer through standard color filters, most common of which is UBV. U stands for near ultraviolet filter, B stands for Blue filter and V stands for visual band filter. Color index is obtained by subtracting V magnitude from B magnitude. This way the color index of yellow sun came to be 0.63. UBV system was extended to red and near infrared filters, becoming UBVRI system. System was extended beyond infrared to J, K, L, N, Q bands. An object’s real brightness is known as its bolometric magnitude m_bol which is a measure of total radiation the object is emitting. Modern Photometry makes use of CCD sensors. CCD stands for charge coupled devices. CCD Sensors can receive more than 95% of incoming light.

Spectrum is obtained when stellar light is shown through a prism. Prism or a diffraction grating splits light into its constituents. Continuous spectrum is obtained when there is no intervening matter between the light source and prism or diffraction grating. When dust or gas cloud is heated by a proto star or active galactic nucleus, Electrons of their atoms absorb specific amount of energy and emit it in specific quantas. Such re emitted radiation when passes through prism gives of a particular type of spectrum known as emission spectrum, having bright lines corresponding to specific wavelengths depending upon type of atom that emitted the radiation. By comparing such stellar spectrum with spectrum of known elements, composition of stellar dust or gas is known. When radiation of a star is absorbed by electrons in the atoms of surrounding colder dust or gas, it gets re radiated with somewhat reduced intensity and in random direction. When such re radiated light passes through prism it gives of absorption spectrum which is a continuous spectrum except for dark lines at wavelengths where elements in dust or gas would have their bright emission lines. Therefore such spectra can also be used to obtain elemental composition of intervening dust or gas. Helium line was discovered in 1868 in solar spectra independently by Norman Lockyer and Pierre Janssen and was found on Earth in 1895. Modern Spectroscopy makes use of Holographic gratings and gratings made using Lithographic techniques. Reactive Ion Etching is another advanced method in use now for making gratings.

Click here to read The Dark Matter Story to know more about measuring wavelengths and redshifts

By the year 1913, Edwin Powell Hubble (Nov 20, 1889 – Sep 28, 1953) was sure that he wanted to get into Astronomy. He gave up law practice and went back to his alma mater- the University of Chicago, to get doctorate in Astronomy. While finishing his doctoral work in early 1917, he was invited by George Ellery Hale to work with recently finished 100 inch telescope at Mount Wilson observatory, Pasadena, California. Hubble accepted the commission as an army captain instead. After war, he joined Mount Wilson Observatory in summer of 1919. Hubble was well aware of spectroscopic work done by Vesto Melvin Slipher (Nov 11, 1875 – Nov 8, 1969) at Lowell Observatory in Arizona and his 1912 discovery of shifts in spectral lines toward red band indicating that most of the nebulae are moving away from us. Also, Slipher was first to observe the rotation of spiral Galaxies in 1914. General consensus among Physicists of those days was that the Universe is static. Even Albert Einstein (Mar 14, 1879-Apr 18, 1955) believed that Universe is unmoving which led him to introduce cosmological constant in his field equation of General Relativity to exactly balance out the crunching effect of gravity which he thought would cause the Universe to collapse on itself. General relativity showed how stress-energy causes spacetime to curve. His equations in their original form indicated an expanding or shrinking Universe which Einstein couldn’t believe.

Nebulae, which later became known as Galaxies were the great mystery of those days. They appeared as fuzzy patches in those old telescopes and were subject of great debate between Harlow Shapley and Heber Curtis in 1920. Shapley believed that the Milky Way is 300,000 lightyears wide and is our entire Universe, Sun is not at center and Nebulae are part of Milky Way system. Curtis argued that Milky Way is only 30,000 lightyears across and Nebulae are Island Universes, separate Galaxies beyond Milky Way. Hubble was interested in studying these Nebulae and so he started taking photographic plates of these objects. On the night of Oct 5, 1923, he observed 3 Novae close to Andromeda Nebula- M31. On comparing this plate with earlier plates, he noticed that one of the Novae is actually a variable star. Further observations confirmed that the variable star matches characteristic of a Cepheid variable. Using the period luminosity graph for Cepheids, Hubble was able to calculate distance to the variable star and got a value of about 900,000 lightyears for distance of Andromeda Nebula. The actual value is close to 2.2 million lightyears. Earlier, Harlow Shapley had found a value close to 300,000 lightyears for the diameter of Milky Way, current value being 100,000-120,000 lightyears. This conveniently put M31 well beyond the boundaries of Milky Way and therefore Heber Curtis’s point of view was partially confirmed that M31 and other such Nebulae are separate star systems comparable to Milky Way. Hubble published his discovery first in Nov 23, 1924 issue of New York Times and then in front of American Astronomical Society on Jan1, 1925.

Hubble continued his work on Nebulae, calculating distance to 22 Nebulae. He also calculated their velocities using shifts in their spectral lines, 4 of which were determined by his assistant Milton Lasalle Humason. He further calculated distance to 22 more Nebulae from their radial velocities, assisted by Humason. Observing the photographic plates, Hubble could see that small appearing Nebulae have greater radial velocities than bigger ones. Assuming that all Nebulae are more or less the same size, he concluded that more distant Nebulae are moving at much greater velocities than the nearer ones. Together with 2 earlier estimates by Harlow Shapley, he had data for total 46 Nebulae. He plotted the radial velocities corrected for solar motion against distance calculated using luminosities for 24 Nebulae and also for the 22 Nebulae whose distance could not be calculated individually. He found an almost linear variation in radial velocity with distance. This indicated that with increasing distance the radial velocity of Nebulae also increases by a common factor, a term which later became known as Hubble Constant. Hubble concluded that Nebulae are going away from each other and the Universe is expanding. He communicated these results in his Jan 17, 1929 paper titled ‘A Relation Between Distance and Radial Velocity Among Extra Galactic Nebulae’. The relation can be mathematically expressed as,

v = H₀×d

This is known as Hubble’s law, where,

v = recessional velocity of Galaxy

d = Distance to the Galaxy

H₀ = Hubble’s constant

Hubble got a value of about 500 km/s/Mpc for his proportionality constant, current value being 67.8±0.77 km/s/Mpc which means that expansion of Universe increases by about 67.8 km/s for every 3.26 million lightyears in any direction.

In 1917, Albert Einstein introduced cosmological constant to curvature side of his field equation of Gravitation to make the equations predict a static Universe as a dynamic Universe was considered absurd at that time. Russian Physicist Alexander Friedmann (Jun 16, 1888-Sep 16, 1925), worked on Einstein’s field equations without presumptions and showed that Universe might be expanding at a rate which can be calculated using the equations. Friedmann’s equation can be obtained by putting metric for homogeneous and isotropic Universe in Einstein field equations. He presented his equations in 1922. Georges Lemaître (Jul 17, 1894-Jun 20, 1966), a Belgian priest and astronomer, found something similar from Einstein’s field equations in 1927. Lemaître made the first empirical determination of Hubble constant H₀ using these equations. He also suggested that if Universe is expanding then it must have been unimaginably small back in time, a state he called ‘cosmic egg’. He met Einstein and showed his results to him. Einstein held on to the popular belief of a static Universe and disapproved Lemaître’s result. After Hubble published his findings in 1929, Einstein visited him. He saw the data and was convinced that the Universe is expanding. He then dropped cosmological constant, restoring the field equations to their original form.

After Hubble, almost everyone accepted an expanding Universe. Astronomers and Physicists believed that the expansion must be slowing down due to gravitational pull of matter-energy density. Rate of slowdown was named deceleration parameter with symbol q₀. Allan Rex Sandage (Jun 18, 1926 – Nov 13, 2010), a student of Walter Baade and Hubble, published a paper in 1961 titled ‘The Ability of the 200 inch Telescope to Discriminate Between Selected World Models’. In this paper he advocated that cosmology is search for two parameters- Hubble constant H₀ and deceleration parameter q₀. Earlier in 1958 he had measured Hubble constant to be 75 km/s/Mpc, which is its first good estimate.

Click here to go to next part

References:

1)https://www.famousscientists.org/henrietta-swan-leavitt/

2)https://apod.nasa.gov/debate/debate20.html

3)http://www.amnh.org/explore/resource-collections/cosmic-horizons/profile-georges-lemaitre-father-of-the-big-bang/

4)http://skyserver.sdss.org/dr1/en/astro/universe/universe.asp

5)http://w.astro.berkeley.edu/~mwhite/darkmatter/hubble.html

Image credits goes to respective sources.

The Dark Matter Story

noreply@blogger.com (Rishi Mishra) — Tue, 08 Dec 2015 14:07:00 +0000

Mount Wilson observatory, built on top of Mount Wilson in Southern California by George Ellery Hale, a prolific astronomer who discovered magnetic field in sunspots, houses the 100 inch telescope, largest from November 2, 1917 to January26, 1949. During early 1930’s, Fritz Zwicky, then associate professor of physics at Caltech, was using this 100 inch telescope to look at galaxies in Coma Cluster- a rich cluster of approximately 1000 galaxies about 330 million light years away. Zwicky gathered light from galaxies through the telescope and obtained spectrum by placing spectrograph at focus of telescope. Spectrograph is a Spectrometer used to obtain spectrum which is a graph showing intensity as function of wavelength. Spectrograph of those days were light tight boxes comprising a prism or diffraction grating plate to which light was let through a narrow opening and a detector placed at appropriate distance and angle to record the spectrum.

Diffraction Gratings, pioneered by David Rittenhouse in 1785 and furthered by Joseph von Fraunhofer in 1821, are plates with many uniformly spaced, parallel, opaque, grooves per millimeter, engraved upon them. Transparent plates are used for making transmission gratings and metal coated opaque plates are used for reflective gratings. Space between grooves could be of the order of microns. Groovings can be sinusoidal or triangular. Triangular groove gratings are also known as blazed gratings because of higher brightness of the spectra they produce. Grooves do the diffraction. Light falling on gratings diffracts and splits into constituent wavelengths. In most directions, light diffracted from one groove cancels out light diffracted from another, known as destructive interference. In certain number of directions though, constructive interference takes place. These directions correspond to diffraction order ‘m’. Many such orders exist when wavelength of light diffracted is much smaller compared to spacing between adjacent grooves often denoted by ‘d’. Fewer such orders exist in case ‘d’ is comparable to wavelength. Wavelength ‘λ’ of diffracted light depends on angle of incidence w.r.t normal to grating substrate, angle of diffraction w.r.t normal to grating substrate, spacing between consecutive grooves and diffraction order. Gratings can be reflective or transmissive. Reflective gratings are better suited for commercial spectrography. The detector used to be a photographic plate which was glass plate coated with special emulsion.

mλ = d(sinθ_i + sinθ_r)

Where, θ_i = Angle of incidence measured w.r.t grating normal, anticlockwise

θ_r = Angle of diffraction measured w.r.t grating normal, clockwise

Zwicky obtained graph of intensity of light as function of wavelength. This was usually done using a Microdensitometer which shines a compact ray of light through the photographic plate to a light sensitive photo multiplier tube. The tube evaluates and registers amount of light at each wavelength as light crosses the photographic plate, usually in form of an intensity amplitude and wavelength graph. Once wavelengths were obtained, Zwicky calculated redshift for each galaxy and then radial velocities and using that velocity dispersion for the cluster. Link between redshift and velocity of galaxies can be expressed as:

z = (λ – λ₀)/λ₀ = v/c = (R_Present/R_Emit)-1

For z << 1.

In much broader sense:

z = {(λ/ λ₀)² – 1}/{(λ/ λ₀)² + 1} = v/c

Here, z = Redshift

λ = Measured wavelength

λ₀ = Emitted wavelength

v = Radial velocity of object

c = Speed of light

R_Present = Radius of curvature of Universe at present = 1 (Very-Very close)

R_Emit = Radius of curvature of Universe when radiation was emitted

Velocity v calculated this way is the radial velocity or line of sight velocity of the object.

V_Radial = V_Recessional ± V_Peculiar

Here, V_Recessional is velocity due to accelerating expansion of spacetime and V_Peculiar or sometimes infall velocity is velocity of object due to net gravitational effect of surrounding objects. For higher radial velocities or large distances, V_Radial can be approximated to V_Recessional. Peculiar velocities and Galactocentric velocity of sun become significant at radial velocities below about 1500km/s or in other words for closer objects. Moreover, several Earth related velocities should also be considered for higher precision. Distance d of object from viewer can be linked to its recessional velocity using the equation:

V_Recessional = H₀ × d

Known as Hubble’s law. Here, H₀ is Hubble constant with current value of 67.8 km/s/Mpc, Mpc stands for megaparsec and equals to 1 million parsecs or 3.262 million light years or 3.086×10¹⁹ km. Hubble constant is speed with which a galaxy at 1 Mpc distance, is moving away from us in any direction, assuming our Universe is homogeneous and isotropic at large scales. Inverse of Hubble constant is called Hubble time T_h.

In his 1933 paper titled ‘The redshift of extragalactic nebulae’ Zwicky considered Coma cluster to be virialized which means the cluster is neither expanding nor collapsing, it has reached a state of dynamic equilibrium. Further, he counted the number of Galaxies in cluster to be approximately 800 each having a mass of the order of 10⁹ Solar masses. He thus calculated the approximate total mass M of cluster.

M ∼ 800 × 10⁹ × 2 × 10³⁰ kg = 1.6 × 10⁴² kg

He then calculated mean potential energy of system using:

P.E_Mean = (P.E_Total)/M ∼ -64 ×10⁸ m²/s²

Where, P.E_Total = -(3/5) × (GM²)/R

R is radius of cluster, about a million light years or 10²² m.

Since cluster is considered virialized, virial theorem can be applied, according to which:

K.E_Mean = -(1/2) × P.E_Mean = 32×10⁸ m²/s²

Also, K.E_Mean = (Mean v²)/2

From this, (Mean v²)^1/2 = 80 km/s

Also, mean v² = 3 × σ², where σ is radial velocity dispersion. From this,

σ = ((Mean v²)^1/2)/√3

Zwicky found a radial velocity dispersion of 1019 ± 360 km/s for Coma cluster which he calculated from observed radial velocity of 8 Galaxies using their spectral redshift, Comparing the two results, Zwicky concluded that average density of Coma cluster must be at least 400 times greater than density due to luminous matter alone, for a velocity dispersion of over 1000 km/s. This directly indicated presence of non luminous matter in the cluster. Zwicky called it Dunkle Materie which is Swiss for dark matter. Since Zwicky considered Hubble parameter H₀ to be 558 km/s/Mpc, his estimates are different than more recent ones, but meaningful nonetheless.

In 1973, Physicist James Peebles and Astronomer Jeremiaha Ostriker were trying to simulate the evolution of Galaxies using N Body Simulation. They programmed 300 mass points to represent stars in a Galaxy rotating about a central point with more mass points towards center and fewer toward boundary. Simulation was based on movement of mass points due to Newtonian gravitational force between them. In less than a rotation period most of the mass points were collapsing into a bar shaped blob near central region. However, they were able to obtain recognizable spiral or elliptical shapes on adding a uniform mass distribution 10 times the size of the 300 mass points. This indicated that Galaxies might be harboring non luminous matter about 10 times the mass of visible matter. They presented their results in 1974 paper titled ‘The size and mass of Galaxies, and the mass of the Universe’. They also gave a criterion known as Ostriker-Peebles criterion, according to which if T is first kinetic energy component and W is total kinetic energy, then, a Galaxy will become barred if T/W > 0.15.

At Carnegie institution in Washington, Astronomer Vera Cooper Rubin was collaborating with instrument maker Kent Ford. Ford had created one of the most sensitive spectrometer of those days. Together they used this spectrometer to obtain reliable spectrum of Hydrogen gas clouds orbiting in different parts of Andromeda, including the boundary regions. They obtained the velocities and plotted a chart. What they obtained was a curve which looked almost flat indicating that the gas near boundary region is orbiting as fast as the gas near central region of Galaxy. They noted an almost constant gas velocity outside visible boundary of Galaxy from their plot. This couldn’t be explained by Newtonian gravity. Gas orbiting that fast near boundary region couldn’t be held by the gravity of luminous mass of Galaxy alone. This indicated presence of non luminous matter in large quantities, about 10 times more than luminous matter according to Rubin’s calculations. Rubin noted that if Andromeda obeyed Newton’s law then it must contain Dark Matter with quantities increasing with increasing distance from its center. Rubin and Ford announced their result first in 1975 at a meeting of the American Astronomical Society. In 1980, Rubin published these results in a widely reviewed paper.

In 2004 NASA’s space based orbiting X-ray observatory recorded an image which came to be known as galaxy cluster 1E 065756 or Bullet Cluster in common usage. A deeper look at object 1E 065756 revealed that it’s in fact two Galaxy clusters that underwent a collision about 100 million years ago. Gas in two clusters underwent friction as the two clusters passed through each other and got superheated emitting X-ray captured by the observatory. Hubble space telescope recorded optical image of the object. Scientists also used gravitational lensing effect of colliding clusters to obtain an image of gravitational mass of object. On combining the three images it was clear that X-ray emitting portion of object is lagging behind mass concentration, indicating that weakly interactive dark matter and heavy compact objects passed right through without colliding but the gas was slowed down.

At end of cosmic inflation, at about 10^-32s after big bang, inflation field decayed into Quark-Gluon plasma. This phenomenon is named Reheating. Between 10^-12s to 10^-6s after big bang, W and Z Bosons and Photons separated and Higgs field manifested and particles interacting with this field acquired mass via Higgs mechanism. Between 10^-6s and 1s after big bang, Universe was cool enough for Quarks to combine using Gluons forming Protons and Neutrons, collectively known as Hadrons. Between 1s and 10s after big bang most of Hadrons and Antihadrons annihilated each other leaving a Universe primarily filled with Leptons and Antileptons. Approximately 10s after, creation of new Lepton-Antilepton pairs stopped as the Universe further expanded and cooled. A small residue of Leptons remained at the end of mutual annihilation. Between 10s and about 380000 years after big bang, Photons kept colliding with charged electrons, protons and nuclei because of low mean free path. Nucleosynthesis took place during this period forming heavier nuclei. 70000 Years after Big Bang, Cold Dark Matter was dominating. Small variations were present in the density of matter and dark matter, owing to quantum mechanical fluctuations. Both normal matter and dark matter were pulled toward higher density regions by gravity making dense regions denser and rare regions rarer. Dark matter kept getting concentrated around center of these quantum mechanical fluctuations without any obstruction as it didn’t interact with Photons, but normal matter while falling in under the effect of gravity was getting hit by Photons causing it to move away.

When photon pressure was more, normal matter moved away and when gravity was stronger, it fell in creating an oscillating effect known as baryonic acoustic oscillation. When the normal matter fell in it grew denser and therefore hotter and when it was pushed out, it cooled off. Also areas where matter concentrated grew hotter compared to areas from where it moved out giving rise to hotter and colder regions in Universe which we see as hot and cold spots of different sizes in CMB map. About 380000 years after Big Bang, the Universe was so big it became cool enough for electrons and protons to combine to form neutral atoms in a process known as recombination. The process was fast and faster for Helium than for Hydrogen. Due to recombination the mean free path of Photons became infinite and they for the first time were able to travel throughout the Universe. This phenomenon is known as decoupling. The pattern of temperature variation and therefore the baryonic acoustic oscillations and information about fluctuations that rose during inflation was encoded into this light which we today call cosmic microwave background radiation as the wavelength of this primordial light has shifted to microwave band after billions of years of traveling through an expanding Universe. This is why an analysis of cosmic microwave background is sometimes called a baby picture of Universe. It shows the seeds of large scale structures that we find in Universe today. Planck CMB data gives an effective temperature of CMB as 2.7 degree Kelvin with variations of 1 part per 100,000. The angular size of cold and hot spots observed in CMB and extent of temperature variation indicates a dark matter density of 26.8%, normal matter density of 4.9% and a dark energy density of 68.3%.

Efforts are ongoing around world to detect dark matter directly. Scientists have hypothesized a fundamental particle having all known properties of dark matter known as WIMP and are trying to detect it through underground experiments in deep mines such as UK’s Boulby mines. Now, USA’s large underground xenon or LUX experiment and Europe’s ZonEd proportional scintillation in liquid noble gases or Zeplin experiment are collaborating to combine both experiments to increase sensitivity to WIMPs by more than 100 times. LZ experiment is second generation direct dark matter detection experiment. 7 ton purified liquid xenon at ultra low temperature with an active system to suppress non WIMP signals is used in this experiment to detect faint effect of a WIMP on a Xenon nucleus. The experiment uses high voltage feed through, 120 veto photo multiplier tubes, 488 photo multiplier tubes, additional 180 Xenon skin photomultiplier tubes and Gadolinium loaded liquid scintillator veto. System is housed inside a water tank shield. The LZ collaboration has 190 scientists in 32 institutions.

Meanwhile scientists working on dark energy survey at Cerro Tololo Inter-American Observatory, in Chilean Andes, are using the 570 megapixel Dark Energy camera or DE cam mounted on Blanco 4 meter telescope there, to create detailed maps of dark matter by utilizing effect of Dark Energy and strong and weak gravitational lensing effect of said dark matter, in order to understand the nature of dark energy through analysis of clumpiness of dark matter in those maps. DE cam has about 3 ft wide mirrors and weighs between 4 to 5 tons. It is the largest digital camera ever built. The survey started on 31 Aug 2013 and will utilize 525 nights of observation till 2018 to record information from 300 million galaxies. It is supposed to create the most detailed dark matter map of Universe. Dark Matter or cold Dark Matter in this case, bends light through its gravitational effect and the bending is directly proportional to strength of gravitational field which is directly proportional to the concentration of dark matter. Therefore a measure of bending in light could be used to create a density map of Dark Matter through careful calculations.

References:
1) http://blair.pha.jhu.edu/spectroscopy/measure.html
2) https://arxiv.org/pdf/astro-ph/9904251.pdf
3) http://adsabs.harvard.edu/full/1999ApJ...525C1223T
4) https://ned.ipac.caltech.edu/level5/Sept03/Einasto/paper.pdf
5) https://www.sciencealert.com/this-timeline-shows-the-entire-history-of-the-universe-and-where-it-s-headed

Image credits goes to respective sources.

Matter and Forces of Nature at Quantum level

noreply@blogger.com (Rishi Mishra) — Thu, 03 Dec 2015 03:07:00 +0000

Particles of nature can be put in two large distinct groups- Bosons and Fermions, based on their overall spin. Bosons correspond to Bose-Einstein statistics and possess integer spin such as 0, 1, 2 while Fermions correspond to Fermi-Dirac statistics and exhibit odd half integer spin such as ½, 3/2 so on. Fermions cannot exist in same quantum state at same place at the same time. This is known as Pauli Exclusion Principle. Bosons on the other hand can and do exist at same place, at the same time in same quantum state. Gluon, Photon, W, Z, Higgs and still hypothetical Graviton are Bosons. W and Z Bosons have spin of 1 and carry the weak force field which holds nucleons together to form atomic nucleus. Gluons exhibit a spin of 1 and carry strong force field which keeps Quarks together to form Protons and Neutrons. Photons also have a spin of 1 and carry Electromagnetic field responsible for Electromagnetism. Higgs Boson has a spin of 0 and it carries the field responsible for mass of particles. Particles become massive when they interact with the Higgs field. Particles such as Photons pass straight through this field without interacting and therefore have zero mass. Gravitons are supposed to have a spin of 2 and carry the field responsible for Gravity. Of these field carrying Bosons only W Boson carries charge. Charge carried by W Boson has a value of -1. Photon and Gluon are massless because they are not affected by Higgs field. Gravitons also are predicted to be massless. W Boson carries mass of 80.4 GeV/c², Z Boson Carries mass of 91.2 GeV/c² and Higgs Boson carries mass of 125.3 GeV/c². Apart from these there are composite Bosons such as Mesons. One Quark and one Antiquark held together by strong field is named Meson. Both constituting Quarks have odd half integer spin and therefore are Fermions, giving Meson an integer overall spin of either 0 or 1. Mesons are very short lived. They quickly decay into more fundamental particles. Charged Mesons decay into Electrons and Neutrinos. Sometimes they decay into intermediate particles which then further decay to Electrons and Neutrinos. Pion, Kaon and J/Ψ are Mesons. Atomic nucleus can be a Fermion or Boson depending on number of Protons and Neutrons contained. If the number is even then it’s a Boson, otherwise it is a Fermion. Depending on whether it is a Boson or Fermion, some strange properties are observed in Elements.

Quark and Lepton are Fermions. So far we know of six Quarks named Up, Down, Charm, Strange, Top and Bottom, all having spin of 1/2. There is an anti particle pair for each one of them. They all carry fractional charge and they all have mass. Up Quark carries charge of +2/3 and Down Quark carries charge of -1/3. A Proton is two Up Quarks and a Down Quark held together by three Gluons. Since overall spin is half integer, Proton is a type of composite Fermion classified under the name of Baryon- particles made of three Quarks. Before 1987 it was thought that spin of Protons is a resultant of spin of its three constituent Quarks. But the 1987 European Muon Collaboration test indicated that this was not correct. It turned out that Quarks contribute only a very little, 25% at most to the overall spin of Protons. Scientists at RHIC have come up with conclusive evidence that contribution of Gluons to overall spin of Protons is almost same as that of Quarks, a value in the range of 20% to 30% of total Proton spin. Remaining spin might be coming from orbital angular momentum of Quark-Gluon system buzzing around confined by the weak force. Confinement might also be contributing to mass of Proton apart from the Higgs field contribution. Missing spin problem was named Proton spin Crisis. Neutron is another composite Fermion made of two Down Quarks and one Up Quark held together by three Gluons. Because it is made of three Quarks, Neutron also is a Baryon. Baryons are strongly interactive in nature. Protons can exist freely for extremely long time, free Neutrons on the other hand have a mean lifetime of 881.5±1.5 s. At the end of life, free Neutrons decay into Proton, Electron and Electron Antineutrino. Nucleus of a Carbon-13 atom is also a composite Fermion as it is formed by six Protons and seven Neutrons, making overall spin odd half integer.

Electron, Electron Neutrino, Muon, Muon Neutrino, Tau and Tau Neutrino are six known Leptons with a spin value of 1/2. Electron, Muon and Tau carry a charge of -1 while the three Neutrinos are neutral. Antiparticles of all six Lepton are also Fermionic. Leptons are weakly interactive Fermions and have lower mass than Baryons, Electron and Electron Neutrino being least massive with mass of .511 MeV/c² and less than 2.2 eV/c² respectively. Electrons are stable, Muons have lifetime 2.197 microseconds, Tau have lifetime of .2906 Picoseconds while lifetime of the three Neutrinos is unknown.

Composite particles made of Quarks, Antiquarks and Gluons are classified as Hadrons. Fermionic Baryons are made of three Quarks and Bosonic Mesons are made of one Quark and one Antiquark and therefore are Hadrons. Baryonic Hadrons can be put in three groups- Baryons made of one type of Quark, Baryons made of two types of Quark and Baryons made of three types of Quark. Baryonic Protons and Neutrons are most common Hadrons in nature. Pion and Kaon are confirmed Mesonic Hadrons. All Mesons are highly unstable and quickly decay into other more stable particles such as Electrons.

Exotic Baryons and Exotic Mesons are composite particles grouped as Exotic Hadrons. Some of them are confirmed to exist while some other still remain hypothetical. Composite particles made of four or more Quarks and Antiquarks and Gluons are collectively called Exotic Baryons. As of August 2015, two Pentaquarks made of four Quarks and an Antiquark have been discovered at Large Hadron Collider. Dibaryon or Hexaquark and Skyrmion are exotic Baryons predicted to exist but have not been detected yet. Glueballs, composite of Gluons and Tetraquark are exotic Meson candidates. Z(4430) is a charged Tetraquark whose existence is confirmed by LHCb experiment.

For Every particle in standard model an anti particle exists. Anti particles are same as particles except for their charge which is opposite. For example nucleus of antiatom is negatively charged but the Positrons whirling around are positively charged making the antiatom neutral. Particle and anti particle if brought together, annihilate each other converting into energy. If all matter in Universe is replaced with #Antimatter and flow of time is reversed, the anti matter world thus formed will be a mirror image of our everyday matter world with identical nature. In science it is known as Charge-Parity-Time Reversal symmetry or CPT symmetry. Matter and Antimatter particles are always produced in pair. Equal number of particles and anti particles should have been created at Big Bang. Then why there is so little anti matter in known Universe against amount of Matter? This is one of the questions LHC will try to answer in its future runs. Scientists have hints that laws of nature do not apply equally to Matter and Antimatter. A very small amount of matter may have survived mutual annihilation during early days of Universe causing it to be as we find it today. Using ALICE experiment a team of scientists at CERN confirmed in August 2015 that Matter and Antimatter indeed are perfect mirror of each other and should completely annihilate one another whenever they meet. Baryon Antibaryon symmetry experiment gave same conclusion.

Standard model is incomplete. It still cannot explain Gravity and Dark Matter. Experiments at LHC are aimed at solving these problems. Scientists there will try to detect Graviton, particle supposed to carry Gravitational field and weakly interactive massive particles or WIMPS which are supposed to compose Dark Matter. Detection of either one of these will be an epochal moment for humankind.

References:
1) https://arxiv.org/pdf/1105.4992.pdf
2) http://hyperphysics.phy-astr.gsu.edu/hbase/quantum/disfd.html
3) https://home.cern/about/updates/2015/08/alice-precisely-compares-light-nuclei-and-antinuclei

Image credits goes to respective sources.

Awesome and Mysterious Quantum Mechanics

noreply@blogger.com (Rishi Mishra) — Sun, 08 Nov 2015 10:42:00 +0000

While Ernest Rutherford, Hans Geiger and Ernest Marsden were bombarding Gold foils with Alpha particles in 1909 leading to the discovery of atomic nucleus, Chemists were finishing analysis of gas emission spectrum. When light obtained from heating up gases in a glass tube was passed through a prism, it formed distinct lines of light of different colors for example in case of Hydrogen, Red, Blue/Cyan and Violet colored lines were obtained. Niels Bohr, by putting together Einstein’s theory of light and J.J. Balmer's empirical formula came up with an explanation in 1913. He figured that Electrons absorb energy when gas is heated up and leap to higher energy orbits around the nucleus, but they only leap to certain orbits after absorbing specific amount of energy. When cooled down the Electrons emit energy in specific amounts termed as Quanta and leap in to lower energy orbits. We obtain distinct lines of different colored light because electrons absorb and emit energy in certain amounts. Electrons can only have certain amounts of energy, not just any value. This explanation also rescued Rutherford’s atomic model because now it was understood why Electrons did not get pulled into the nucleus given their opposite charges.

Balmer's formula

Here R_H is Rydberg constant for Hydrogen, n₁=2 and n₂ greater than n₁

Louis-Victor De Broglie after intensely studying wave particle duality of light pioneered by Max Planck and Albert Einstein, presented his famous hypothesis in 1924 stating not only light has both wave and particle properties but particles such as Electrons too should have both wave and particle like characteristics. De Broglie called the wave associated to a particle, matter wave. He showed that wave, characteristic to a particular particle should have a wavelength of

λ=h/p

Where h=Planck’s constant having a value of 6.626068*10^-34m²kg/s and p=momentum of the particle.

Werner Heisenberg et al presented matrix mechanics to describe wave nature of particles in 1925. In 1926 Erwin Schrodinger created wave mechanics in an attempt to describe matter waves. Latter Schrodinger showed that matrix mechanics and wave mechanics are equivalent. Max born showed a statistical version of wave function and pointed that solution to Schrodinger’s wave equation for particles gives probability of finding a subatomic particle like an Electron at a particular location, it doesn't describes a smeared out Electron as Schrodinger himself had thought. By 1927 George Paget Thomson in UK and Clinton Davisson and Lester Germer in US had experimental evidence of wave like properties of Electrons. They were conducting their experiments with Electron beams although with different purposes but found similar diffraction patterns indicating wave like nature of Electrons. These were very first experimental support for De Broglie’s matter waves, 3 years after they were presented. Latter while calculating probability of finding an Electron at different locations using Schrodinger’s wave equation, scientists found a definite probability of finding the Electron on other side of the detector screen. Further they found a certain probability of finding an Electron on other side of a thick wall and even a mountain. This surprising probability is described as Quantum Tunneling and it is real. It is thought that Electron borrows energy required to get through solid wall from future and returns that energy once it is on the other side. As bizarre as it may sound but most probably, that’s how it is. Scientists are harnessing this property of Electrons in creating faster and smaller transistors and Quantum Computers. Transistors utilizing Quantum Tunneling will be much smaller and much faster than the smallest transistors we have today like those 11nm CMOS transistors.

After the equivalence of Matrix and wave mechanics was established, Jordan in Gottingen University and Paul Dirac in Cambridge university merged these two different ways of representing a matter wave mathematically and came up with what became known as transformation theory. Heisenberg while pondering over the papers of Jordan and Dirac figured that more precisely the position of a subatomic particle is known, less precisely its momentum can be known. In 1927, He came up with a mathematical expression to quantize this uncertainty.

ΔxΔp ≥ h/4Π

Where Δx= Standard deviation of position, Δp= Standard deviation of momentum, h= Planck’s constant

Same uncertainty holds for certain other pair of variables too such as energy and time for which the particle can have that energy. In order to explain this result Heisenberg thought up an experiment using Gamma ray microscope. Gamma rays have higher frequency than Electrons and therefore when used to determine position of Electron it will significantly change the direction of motion of Electron upon impact. Even visible light when shone to find the location of Electron will alter its velocity by some amount as energy of photon is comparable to energy of an Electron, leading Heisenberg to conclude that uncertainty is inbuilt into nature itself. As a matter of fact, with Uncertainty principle the predictions of Quantum Mechanics became consistent. Of ‘course the principle has been verified in many experiments since 1927, most common of them being the slit experiment.

In 1801 Thomas Young took up the task of measuring light’s wavelength. He used a paper card to split a single pinhole beam of sunlight into two to carry out his experiment. Latter the practice of using two narrowly separated slits caught on. Italian physicists Pier Giorgio Merli, Gian Franco Missiroli and Giulio Pozzi did the double slit experiment with a single Electron in 1974. They found an interference pattern on the detector screen, kind of pattern which is created by waves, proving the predictions of Quantum Mechanics. Latter on Scientists discovered that when they look at the Electron fired from Electron gun, it formed a particle like pattern on detector screen and when they did not look, it formed a wave interference pattern. But, how a single Electron can form wave interference pattern? Although the predictions of Quantum Mechanics were verified, nobody had any idea, how. This mystery is still without a good explanation. In more recent versions of this experiment, Scientists observed the Electron after it crossed the slits. To their surprise they found that when they look, the Electron formed a particle like pattern and when they didn’t, it again formed a wave like pattern. How is that possible? Nobody knows the answer even today, but we do know now that Bohr was right. That, act of observation does really changes behavior of a particle. In addition, these observations also gave support to Heisenberg’s Uncertainty Principle. These experiments supported probability wave nature of Electron as predicted by Schrodinger’s wave equation and supported De Broglie’s matter waves or wave particle duality. We know now that the Electron can be in many positions at the same time or wave like if we are not looking at it, a Quantum Mechanical phenomena known as Quantum Superposition, and takes a particular position or behaves particle like if we do look at it.

Time-dependent Schrödinger equation- General

Ψ is wave function of Quantum system, Ĥ is Hamiltonian operator, ћ is reduced Planck’s constant, i=sqrt(-1), r is 3d position vector

Albert Einstein had other ideas about Quantum Mechanics. He and two of his colleagues Boris Podolsky and Nathan Rosen came up with a prediction of Quantum Mechanics in 1935, which he thought cannot be true, leading to his declaration that Quantum Mechanics is not wrong but it is incomplete. That prediction was Quantum Entanglement. Einstein together with his colleagues said that according to Schrodinger’s wave equation and other principles of Quantum Mechanics if two fundamental particles share their source of origin then their properties will have to be linked in such a way that sum of measurements of their Quantum properties give the Quantum property of source particle no matter how far apart these two particles are. This can be possible only if an act of measurement on one of these entangled particles simultaneously affects the Quantum state of other particle thus keeping the sum total same as it would be for the Quantum state of the source particle. This indicates some form of communication between the two particles happening at speeds greater than speed of light, leading Einstein to conclude that the theory is incomplete and requires modifications. Bohr and his colleagues remained unmoved. In his 1964 paper, Irish Physicist John Stewart Bell came with an inequality to settle this dispute. According to the inequality if Einstein was right then Quantum Mechanics would not be just incomplete but it would be wrong. When experiment was done in 1972 by John Clauser and Stuart Freedman, Einstein was found wrong. Results of this experiment supported immediate communication between entangled particles. Latter in 1981-82 a more precise experiment was conducted by Alain Aspect which corroborated faster than light communication between entangled particles when an act of measurement is performed. Bell’s inequality indicated that if Quantum Entanglement was real then entangled particles will have higher correlation than classical physics would allow. Results obtained from experiments based on Bell’s inequality unequivocally indicated a higher correlation between entangled particles. Now scientists around world are harnessing this phenomenon for creating Quantum Computers and to achieve Teleportation.

Because of the uncertain nature of reality, first indicated by Heisenberg, we can’t say with certainty that empty space is without any energy-mass density. According to Quantum Mechanics there is a finite probability that empty space may have certain amount of energy as long as nobody observes it. More specifically, particles and antiparticles may originate from empty space in pairs and exist for a certain while before annihilating each other. Amount of time they exist for depends on their energy, as Quantum Mechanics predicts. More the energy, shorter the duration they exist for and vice versa. This prediction came to be known as quantum vacuum fluctuations of electromagnetic field and is inherent to space.

Hendrik Casimir while investigating the discrepancies in measurements done on colloids, using the theory of Fritz London concerning Van Der Walls forces, the forces that govern colloids, thought up an interesting event. In his 1948 paper he indicated that if two neutral conducting plates are placed about a micron apart in vacuum, then vacuum between plates could only create virtual photon pairs with very small wavelengths compared to vacuum around as kind of wavelengths that can exist between plates becomes limited because of the very short gap. This will cause a higher pressure due to impact of colliding virtual photons from vacuum around compared to pressure caused by virtual photons contained in between, causing plates to get pushed together. This became known as Casimir effect. Until recently, scientists were not able to create experimental conditions required to measure the force predicted by Casimir’s equation.

F=(Πhc/480L⁴)A

F= Force experienced by the plates, h= Planck’s constant, c= Speed of light, L= Gap between plates, A= Area of plates

In 1996, Steven Lamoreaux finally succeeded in creating lab conditions required for the experiment and found the experimental results to be within 5% of the value predicted by Casimir. By 2011, more accurate experimental confirmations have been achieved. Particles other than Photons also affect the plates but in magnitudes too small to be measurable by current technology. Effect of Bosons is attractive on the other hand effect of Fermions is repulsive. Existence of Casimir effect reveals a lot about nature of reality. For one it entails a broken Super symmetry, because it indicates absence of Fermionic photinos. Super symmetry has not been detected yet. It has other implications such as quantum gravity and about nature of space-time itself. Dynamic Casimir effect is a direct derivation and predicts that if the two plates move to and fro at speeds close to speed of light then virtual particles of vacuum may become real by converting energy of motion of plates.

References:

1) https://www.nobelprize.org/nobel_prizes/physics/laureates/1922/bohr-lecture.pdf

2) http://www.pitt.edu/~jdnorton/teaching/HPS_0410/chapters/quantum_theory_ origins/
3) http://math.ucr.edu/home/baez/physics/Quantum/bells_inequality.html
4) http://www.casimir-network.org/IMG/pdf/Casimir_20effect.pdf

Image credits goes to respective sources.

Facts About Large Hadron Collider; World’s Largest and Most Powerful Particle Accelerator

noreply@blogger.com (Rishi Mishra) — Sun, 01 Nov 2015 02:28:00 +0000

LHC is a 26.659 kilometer ring of superconducting magnets cooled to -271.3˚C, a temperature even below the temperature of outer space which is -270.5˚C. It lies 50-175 meters underneath the surface. 1232 Dipole magnets, 15m in length are used for bending the beams and 392 quadrupole magnets, 5-7 meters long are used to focus them. Another type of magnets is used to bring beams closer, just prior to collision. Most of the 9593 magnets installed weigh over 27 tonnes and are made of Copper clad Niobium-Titanium and approximately 96 tonnes of superfluid Helium is required to maintain their operating temperature at -271.3˚C.

Pipes in which particle beams travel includes 48km of arc sections at 1.9K and 6km of straight sections at room temperature and are kept under ultra high vacuum even higher than the vacuum of intersteller void which is below 1.0133*10^-10 mbar or 10^-13 atmospheres.
Housing tunnel of beam pipes crosses the France-Switzerland border at 4 points and most of it lies within French territory. The 2 beam pipes run adjacent and parallel crossing at points where main particle detectors- ATLAS, CMS, ALICE and LHCb are located. ATLAS detector was used to find Higgs-Boson. Each detector serves a specific kind of detection. Beams travel in opposite direction within these pipes and are made to collide at the intersections at a staggering rate of 1 billion collisions per second. TOTEM, LHCf and moEDAL are the other 3 smaller detectors.
ATLAS Detector or #ATLASExperiment is equipped with Muon spectrometer, Magnet system, pixel detectors, transition radiation trackers, semiconductor tracker, electromagnetic calorimeter, and Hadronic calorimeter to record the trail of subatomic particles created in collisions. These trails are latter analyzed to obtain information about the subatomic particles that created them.
ATLAS stands for A Toroidal LHC apparatus. It is the largest detector at 46 meters long, 25 meter wide and 25 meter high and weighs 7000 tonnes. It is used to investigate #HiggsMechanism, #ExtraDimensions, micro black holes and particles constituting #darkmatter.
CMS is for compact muon solenoid and has same scientific goals as ATLAS detector but uses different technology and different magnet system. Its in the form of a multi layered cylinder and weighs more than 13000 tons. At inmost it comprises a particle tracker made entirely of silicon. After that electromagnetic calorimeter then hadronic calorimeter and then the solenoid magnet. At the outmost is the muon detectors and return yoke.
ALICE Stands for A large ion collider experiment. It is a heavy ion detector. It is designed to study Quark Gluon plasma which is created by the collision of Pb nuclei. Data obtained from these collisions could help understand the beginning of universe. One of the goals is to investigate why Protons and Neutrons weigh 100 times more than their constituent Quarks.
LHCb or Large Hadron Collider beauty experiment is used to investigate the slight differences between matter and antimatter by studying a type of particle called beauty quark or b quark. It includes a forward spectrometer and planar detectors.
Energy of 6.5TeV per proton has been achieved speeding the protons to 99.9999991% of speed of light which corresponds to a Lorentz factor of 7460, giving total collision energy of 13TeV.
Pb nuclei collisions create temperature of 5.5 Trillion degree Celsius for a fleeting while which is close to the temperature of Universe when it was only moments old.
As of 25 Nov 2015 first ion collision was achieved at 1PeV which is a record.
LHC Computing grid is designed to handle massive amount of data generated by collisions. It includes over 170 computing facilities across 36 countries and is the world’s largest computing grid. Over 30 petabytes of data is produced per year and over 6*10^15 proton-proton collisions has been analyzed by 2012.
Hadron in Large Hadron Collider stands for particles made of 3 Quarks such as Protons and Neutrons also known as Baryons and particles made of 1 Quark and 1 Antiquark also known as Mesons such as Pions.
Future runs of #LHC are aimed at testing Supersymmetry predictions, String theory and expanding our understanding of Higgs mechanism. Scientists will be looking for Sparticles and Gravitons and presence of higher spatial dimensions in data obtained from even higher energy collisions. They will also try to find dark matter and detect dark energy.
It took the effort of thousands of Scientists and Engineers over a period of 10 years and about $10 billion to build the LHC. For second run the estimated power consumption is 750 GWH per year which will cost in excess of 30 million dollars. Annual cost of running experiments comes up to be in excess of a billion dollars.

Watch how Proton beams are made to collide at such high energy levels in this video.

References:
1)https://home.cern/topics/large-hadron-collider
2)https://home.cern/about/experiments

Image credits goes to respective sources.

Multiverse Alternate Timelines and Copies of You and Me

noreply@blogger.com (Rishi Mishra) — Fri, 30 Oct 2015 07:49:00 +0000

There are scenarios in Quantum mechanics, Theory of eternal inflation, and String Theory that allows for the possibility of existence of Multiverse that is countless other Universes apart from our own. In this Multiple Universe picture there may exist another Universe very similar to our own as the math of the theory suggests. None of the observations made so far have contradicted Quantum mechanics, it has proven to be correct over and over again, and if the same theory allows for a Multiverse, then there is a strong chance. Data from NASA’s WMAP and latter ESA’s Planck Satellite supports the predictions of inflation theory which makes a good case for the possibility of multiple Universes as in the theory of eternal inflation. String theory has elegance and it holds together beautifully and experiments are being conducted in particle accelerators all around the world to test its predictions. There is a strong chance that results will be affirmative.

Many world interpretation/Everett interpretation of quantum mechanics simply suggests that all the possible outcomes of a quantum event do really gets played out, only in other Universes that are non communicative and increasingly divergent. All the probable outcomes do really occur, they just occur in other Universes. It asserts that universal wave function gives us a good picture of reality; we just need to find a way to verify it. Many world interpretation talks about Quantum decoherence. For every possible outcome of a quantum event an alternate time line exists which is divergent to other time lines. This is what the math of the theory indicates. Tests are being devised to verify the predictions of this interpretation. There are both proponents and opponents of this theory.

Theory of eternal inflation draws from the theory of inflation and says that inflation caused by false vacuum energy never stops. False vacuum energy decays here and there creating regions with lesser rate of inflation. These comparatively lower inflation rate regions are local universes. Inflation continues to happen at higher rate outside of this region and continues to decay every now and then giving rise to countless such universes. Scientists are hard at work trying to figure out ways of testing this theory. If two such universes were close enough at their formation then they might have collided leaving an energy signature. Colliding universe scenario has been simulated and people are looking hard at data obtained from high sensitivity Planck satellite to find those signs in cosmic microwave background radiation. With even better satellites and probes we will have an even better chance of detecting these signs.

Yet another theory that gives us a possibility of multiple Universes is the string theory. It points that, tiny strings of energy vibrating or wiggling in different patterns along 3 dimensions of space, one of time and 7 other dimensions, form different subatomic particles. These strings can be open ended with each end tied to a plane of existence or they can be like closed loops. Open ended strings are tied to their plane and therefore cannot move freely to other planes of existence. However, close ended strings are not attached to their plane and therefore can move to other planes of existence. From this theory comes the idea of Branes. Theory hints of parallel planes or Branes spreading across higher dimensions. These parallel Branes collide from time to time causing energy conversion creating local universes one of which is ours.

Dimension is akin to degree of freedom of movement. We only have freedom to move along 3 spatial dimensions which we denote as dimensions X, Y, Z and one temporal dimension. String theory requires the existence of seven extra dimensions. This is what math of theory calls for in order to make sense. If those extra dimensions do really exist, then why we have not been able to sense their existence? If graviton is detected by particle accelerators, it may signal the existence of these extra dimensions as one of the properties of graviton is its ability to move along dimensions other than the ones associated to its Brane. As the graviton disappears into one of those higher dimensions, we will know.

One way to test #StringTheory is to find Sparticles, whose existence is supported by it. It is called Supersymmetry and it suggests that there is a Sparticle for every particle in standard model. Standard model is incapable of answering all questions such as why Higgs Boson is light, on its own, giving rise to the requirement of Sparticles. Sparticles or superpartners are much heavier than their symmetrical pair and their inclusion gives better solution to our questions and enriches Quantum mechanics even more. Hunt is on at every major particle accelerator around the world to detect one.

Weakness of gravity as compared to other fundamental forces of nature is explained by string theory. It argues that gravity may be caused by a closed string of energy- a graviton or gravity particle and since closed strings are not tied to their Branes they are free to move to other Branes, which reduces their concentration and thus intensity. People are at work in particle accelerators such as the LHC at CERN to detect a graviton, which will also give support to the idea of extra dimensions whose existence is required for String theory to make sense.

Three theories suggest the possibility of a #Multiverse, I would say, chances are pretty strong that we live in a Multiverse and probably there are people out there very similar to ourselves in alternate timelines in other Universes. Many world interpretation also allows for the possibility of communication between two Universes that corresponds to two possible outcomes of an event, making a way for testing this theory. Another way of communication could be gravitons as they can move freely between parallel Branes. With more powerful and more sensitive equipments coming up in future, who knows what we may find.

References:
1) https://plato.stanford.edu/entries/qm-manyworlds/

2) https://arxiv.org/pdf/hep-th/0702178.pdf

3) https://arxiv.org/pdf/1512.02477.pdf

Image credits goes to respective sources.

Science Says Time Travel is Possible: Technology Has to Catch Up

noreply@blogger.com (Rishi Mishra) — Thu, 29 Oct 2015 10:00:00 +0000

Time is a relative quantity. As indicated by Einstein in his special theory of relativity, t’=t√(1-(V²/C²)) where t’ is time elapsed for person moving at velocity V and t is time elapsed for person at rest, in a particular frame of reference of ‘course. This has been verified over and over by putting synchronized highly accurate Cesium atom clock on a fast moving aircraft and then comparing its reading with the other clock at rest. For a person moving at speed of light C, time will completely stop, while everybody else moving at normal speed will continue to age normally. When the person moving at light speed stops, he will find himself in future having not aged at all. If the person keeps moving at speed of light, he will be immortal. Of ‘course nothing that has mass can reach speed of light, no matter how much energy you supply it. The faster a massive object gets the more its relativistic mass as E=MC²/√(1-(V²/C²)) where M is rest mass and C is constant, and therefore more and more energy is needed to accelerate it. Infinite amount of energy will be required to reach light speed. It was proven by MIT’s Bill Bertozzi when he accelerated electrons and measured their kinetic energy. We can’t accelerate massive objects to light speed yet but we can get very close to it at the cost of an enormous amount of energy. A person moving close to light speed will still find himself years into future when he stops. By one estimate you would be 500 years into future if you move at 99.99% of light speed for 7 years. Astronauts who have taken rocket trips have already traveled into future by fractions of a second, yes only by that much because speed of a rocket is nowhere close to light speed. So, is time travel really possible? Turns out Yes! In fact it’s already been done, on numerous occasions, to the future at least. Russian cosmonaut Gennady Ivanovich Padalka has spent 879 days in space moving at great speed. This has taken him a fraction of a second into future because in his case, the relative speed up in passage of time due to weaker gravity is less compared to the slow down caused by high speed. Particles such as Pi Mesons have a very short lifespan of millionth of a second which increases spectacularly when they are accelerated to near light speed. “Particle accelerators are closest thing we have to a time machine” says Stephen Hawking. LHC at CERN can accelerate particles to 99.9999991% of light speed transporting them into future on a regular basis. Such an accelerator suitable enough for humans can one day help us travel into future, once the technical limitations are overcome.

Einstein’s general relativity theory suggests that time gets slower in stronger gravitational fields. Time passes at much slower rate near black holes than it does near Earth. By one estimate, if the remnant core of a supernova explosion is heavier than 2.37 Solar mass, then not even Neutron degeneracy pressure will hold against Gravity, resulting in collapse of the core, giving birth to a singularity. The collapsed core because of its enormous mass density, creates a dark sphere of influence all around it by warping spacetime around, to extremes. This dark sphere of influence is known as Black Hole. Dark because it doesn't gives out energy, at least not in amounts that can be detected by current technology. There is no other object in known Universe that creates as strong gravitational effect as the one that causes black hole. Einstein's field equations predict the manner in which local mass-energy and momentum surrounded by local space-time affects the curvature of that space-time. Both spinning and non spinning black hole mass density warps space-time with its presence, creating extremely deep curves in spacetime around the Black Hole, making a near by wave of light to travel much greater distance to pass through the surrounding regions of the dark sphere as the comparatively straighter spacetime light was moving along, turns into a deep geodesic near it. Presence of mass-energy density turns parallel straight path along relatively flat spacetime into nearing geodesics around it. Path would be relatively straight in absence of mass-energy density. But, the speed of light still remains same. This increases the time taken by it to pass through that region, as observed by someone standing out of that region. But for a person standing inside that sphere of influence, no time delay will be observed because in that region same thing happens to every other moving entity, no matter how infinitesimally small it is. Every movement, every cycle, takes longer to complete because space-time itself has been stretched. Everything slows down in there, including a person's bioclock, the person himself wouldn't notice it though. Imagine you and your friend have synchronized Cesium atom watches and you travel to a black hole while your friend stays on Earth. Somehow its possible for you to see your friends watch and vice versa. While you go around the #Blackhole in a stable orbit, your friend will observe that second's hand on your watch is taking hours may be even days to tick but you will observe that it ticks at normal rate of 1 second per tick. On the other hand, when you look at your friend's watch, the second's arm will be rotating at speeds greater than that of a ceiling fan while for your friend, the ticking rate stays at 1 second per tick. These predictions of Einstein's general relativity has been verified by data obtained from Cassini-Huygens probe experiment.

A spinning black hole, twists the space-time around it as well, apart from warping it and most of the black holes present in universe are of spinning type. They twist and distort the space-time creating an Ergo-sphere with oblate spheroidal shape in case of a low spin central mass, around the event horizon touching it at poles. In that ergo-sphere, objects cannot be observed as stationary with respect to rest of universe as that would require the object to be moving faster than speed of light. There, things can easily go along the spin but they will require far greater energies to go against it as they will be dragged alongside the twisting space-time. Space is elastic and interconnected as predicted by field equations of #Einstein. It can inflate, it can warp, it can twist, it can warp and twist simultaneously due to mass-energy influence and it can return back to its normal geometry once that mass-energy influence goes away. Twisting of space-time by spinning objects has been named frame dragging. It was derived from field equations of general relativity by Josef Lense and Hans Thirring and is also known as Lense-Thirring effect. The theory predicts that inner regions will be dragged faster than outer regions. Earth also twists and distorts space-time continuously by a very small amount, verified by Gravity probe B experiment. Lense-Thirring effect also predicts that an object constrained in an equatorial orbit, but not in free-fall will weigh lesser while moving along the spin and will weigh more while moving against it.

Gravity is proportional to warping of space-time geometry. Warping of space-time formed by Earth is nothing compared to the warping caused by a black hole. Time on Earth's surface, where Earth's gravity is stronger, passes at a slightly slower rate than it does in orbit around it. This is the reason why GPS clocks have to be compensated to match Earth time. GPS Satellites move at 3874 m/s relative to Earth's center, making their clocks get slower by about 7200 ns/day compared to Earth clocks, yet due to gravitational time dilation, those clocks get ahead by about 45900 ns/day, which gives us a figure of ahead by 38700 ns/day which is consistent with practical observations. Time dilation caused by a height difference of less than a meter has been verified in laboratories around the world using highly precise Cesium atom clocks. Due to curved space, the cycles take longer to complete. Greater the curvature longer it will take the cycle to complete and hence lesser will be the frequency of the wave. So a light wave passing through high gravity field will appear redder to a person standing outside that field or in weaker gravity field, and this is exactly what we see in observations. This phenomena has been named Gravitational red shift. As predicted by field equations of general relativity theory, light or any other object moves along the curvature of space-time, which could be close, open or flat. When light passes through nearby regions of mass-energy density, its path changes as it moves from a relatively flatter curvature to a more bent curvature, causing lensing. This is yet another prediction of general relativity named gravitational lensing. When images are formed with this light, the lensing effect shows up clearly. Arthur Eddington was the first to observe and measure the extent of lensing caused by celestial bodies and found the results to be in close proximity to figure predicted by Einstein's field equations of general relativity, thus verifying the theory in 1919. But it was not until the 1960's when radio frequency observatories started to come up that the observed values started to get extremely close to figure predicted by Einstein's theory. Since dark matter has far greater presence in Universe than normal matter, the extent of lensing gives us an indirect measure of amount of dark matter present in that locality. People spending time in much stronger gravitational fields may find themselves years into the future on returning to Earth. Gravity stretches space, brings geodesics closer and since time is relative, this affects time as well, even though the co-ordinates of time are different from the co-ordinates of space as indicated in Einstein's field equations. Closer the geodesics are brought by warping, stronger will be the gravitational field intensity. The field equation is usually written as

where is the Ricci curvature tensor, is the scalar curvature, is the metric tensor, is the cosmological constant, is Newton's gravitational constant, is the speed of light in vacuum, and is the stress–energy tensor.

Karl Schwarzschild came up with first exact solution of field equations. Schwarzschild radius is the radius of non spinning black hole, equation for which was given by him as

R_s=(2GM)/c²

Here G is the gravitational constant whose value is 6.67408*10^-11 in SI units, M is the mass of object and c is speed of light in vacuum. Any mass density with radius smaller than its Schwarzschild radius will collapse under its own gravity creating a black hole around it. Anything that gets into the black hole will not be able to escape the gravity well no matter how much energy it burns, as predicted by the theory. Black Holes are dark spheres with radius R_s caused by a Planck length mass density, a singularity. Schwarzschild also gave the equation for calculating gravitational time dilation due to non spinning energy density (celestial bodies), which can be written as

t_r/t=√(1-(r_s/r))

where, t_r=elapsed time for an observer at radial coordinate "r" within the gravitational field
t=elapsed time for an observer standing outside the gravitational field
r_s=Schwarzschild radius of the energy density or object
r=radial coordinate of the observer from the gravitating object
Using this equation you can calculate the figures for your time travel to future, yourself.
When technology becomes sufficiently advanced and it becomes possible to take a trip to a black hole, a person taking his ship near a #Blackhole and spending a few months there may find himself 100s of years into future on returning to Earth, because super gravity of black hole will slow time down for him while time on Earth will continue to pass at much faster rate due to Earth’s much weaker gravity.

Einstein’s general relativity also predicts a worm hole. These are conduits across space-time that forms for a very short while and then pinches off before anything can pass through because of pile up of quantum mechanical fluctuations of radiation called vacuum fluctuations which become infinitely energetic and explode, but in that short while it may be connecting two extremely distant regions in space and time, forming a shortcut between them. If the worm hole can be stabilized it may make it possible to travel to far regions of space which would otherwise take 1000’s of years to reach. Conditions have been found within general relativity which allows worm holes to be used as a time machine to the past. Physicists have argued that negative matter will be needed to stabilize a worm hole. Negative matter is non-baryonic and has opposite properties to normal matter. If normal matter is represented as 2kg then negative matter will be represented as -2kg. It has not been detected yet although efforts are underway.

Negative matter could also make it possible to travel at faster than light as Miguel Alcubierre suggests. He tells us that a spaceship could travel faster than light by contracting space in front and expanding it behind, creating a warp bubble or Alcubierre warp drive. It's something like a dust particle riding a ripple on a sheet of fabric. Metric suggested by Alcubierre is mathematically valid but it requires negative energy density to make sense, which means it requires negative matter. We haven’t detected the presence of negative matter yet. That’s a problem we need to solve before this becomes a possible means of time travel, even remotely.

Special theory of relativity allows for a hypothetical particle with imaginary rest mass. Such a particle is called a Tachyon. E=MC²/√(1-(V²/C²)), for imaginary rest mass the denominator must be imaginary and for that V must be greater than C. Therefore Tachyons will always travel faster than light. If ever detected, these particles could provide a means to send communication back in one’s past. A device which would make that happen has been named Tachyonic Antitelephone. As for paradoxes involving traveling to past, it is been argued that nature always finds a way to stay self consistent.

Galaxy's flat rotation curve corroborated by the observations from the Radio Telescope in Puerto Rico, accelerating expansion rate of Universe and the data from Wilkinson Microwave Anisotropy Probe (WMAP) and Planck space observatory has given us the standard model of Astronomy. Universe is composed of- 4.9% Baryonic matter or matter made of atoms, 26.8% Dark matter or non baryonic matter and 68.3% Dark energy. These figures may get better with improved data from future missions and deeper analysis. Nobody has detected either Dark matter or Dark energy yet. We know Dark Energy is out there causing the accelerating expansion of space-time around us and Dark Matter from the flat rotation curve of Galaxies. Who knows what secrets lie ahead or what doors might open? But one thing is certain, the future is full of mind warping possibilities.

Theories of relativity and Quantum mechanics is about how much we know so far about reality and with String theory, Quantum gravity and Quantum cosmology, we continue our relentless effort to grow our awareness of reality.

References:
1) http://hermes.ffn.ub.es/luisnavarro/nuevo_maletin/Einstein_GRelativity_1916.pdf
2) https://arxiv.org/ftp/arxiv/papers/1002/1002.4154.pdf
3) https://www.its.caltech.edu/~kip/index.html/PubScans/VI-47.pdf
4) http://www.hawking.org.uk/space-and-time-warps.html
5) http://cse.ssl.berkeley.edu/bmendez/html/time.html

Image credits goes to respective sources.

Quantum entanglement- The advent of Quantum computing and Teleportation

noreply@blogger.com (Rishi Mishra) — Tue, 27 Oct 2015 08:01:00 +0000

In Quantum computing, iterations are done using Quantum phenomena such as Superposition and Entanglement. Analogous to bits of classical computing we have Qubits in Quantum computing. In some cases spin of an Electron is used as Qubit as it is an inherent property and it fulfills the requirements for Qubit, apart from this certain properties of atom, ion and even a photon which is nothing but quanta of energy, can be used as Qubit. Electron spin can be assigned a value of up or down, but we can only calculate the probability of either state. Until measured, it could have both spin values at same time.

Scientists are constantly looking for new candidates for Qubit. A Qubit does not have absolute state of either 0 or 1 like a classical bit rather it is a superposition of both states. Qubit can be 0, 1 and any value in between at the same time, until an act of measurement is performed which forces it to relinquish all possible states except for one. Act of measurement turns the Qubit into a classical bit and all the Quantum mechanical advantage is lost. This is where property of Entanglement helps out. Quantum Entanglement is the phenomena under which properties of two particles that have previously interacted are inextricably linked in such a way that any change in the state of one particle simultaneously changes the state of other, and this holds true even if the two particles are at opposite ends of universe. Superposition of Qubit is maintained while figuring out its state by performing the measurement on its Entangled pair from which state of Qubit under consideration is inferred. Quantum Entangled bits have higher correlation than two classical correlated bits as established by Bell's inequality. While performing measurements through Entanglement, high correlation between the two Qubits is desirable for faithful results. Correlation giving a fidelity of 96-97% has been achieved by Professor Andrea Morello and his team.

Fact that Qubit can be in two state at same time allows for performing millions of iterations simultaneously making Quantum computers astonishingly superior than classical ones. Quantum computers use sequence of Qubits. A Qubit can be 0, 1 and all points in between at same time. Quantum computer with two Qubits can be in 4 different states at same time. Quantum computer with n Qubits can be in 2^n different states at the same time on the other hand a classical computer can only be in one of these 2^n states at any given time. Thus with every additional Qubit computing power grows exponentially. A Qubit has 2 key states denoted as 0=(1 0) and 1=(0 1) known as basis states. Quantum computer uses these states to perform iterations according to unitary matrix transformation. Theory and logic of Qubit computations is getting developed and numerous methods have been submitted to realize Quantum computing. One such method could be Quantum Annealing as indicated by T Lanting et al. Scientists so far have achieved successful multiplication of two integers using a Quantum computing method.

Quantum computers are based on behavior of matter at Quantum level. Manner in which the spin, energy or speed of these particles changes on interaction is used to create the logic based on which Quantum logic gates are created which are then used to operate on a set of Quantum inputs so called Qubits to yield an output. Qubits are Input to Quantum computers but output comes in form of classical bits because act of getting an output forces particles to relinquish all states they can be in except for one. Binary computer uses binary code as input which is then operated upon using logic circuits made of binary logic gates such as AND, OR, XOR. A binary logic gate is a realization of binary operators such as AND or NOT operator and are made using transistors such as a CMOS transistor. Architecture of Quantum computer is different from architecture of binary computers. In a Quantum computer, Quantum transistors made of controlled Qubits are used to create Quantum gates in order to realize basic Quantum logical operators as in unitary matrix which are then used to create Quantum logic circuits designed to solve real world problems. Code corresponding to such circuits is developed and used for programming. Quantum algorithm is used for creating codes for solving problems using Quantum computers. Based on the definition of Qubit, Quantum transistors have been created such as single atom transistor wherein by controlling the state of Qubit, conduction path can be opened or closed. Using single electron Qubit, Quantum logic gates have been created such as the CNOT gate, a two Qubit gate wherein target Qubit flips its spin when control Qubit is pointing down and maintains its spin when control Qubit is pointing up. Here spin of electron serves as Qubit and control is exercised through microwaves. This 2 Qubit gate alongwith single Qubit operations can be used to create any other gate set. It gives us a way of creating Quantum computers with 100s of Qubits. For sheer processing power, Quantum computer with 300 Qubits will have more computing ability than all binary computers on Earth combined. Quantum computer with 300 Qubits in Entanglement will have processing power equivalent to 2³⁰⁰ bit conventional computer. 2³⁰⁰ is about the number of particles in observable universe.

Vector representation is used to present Quantum states mathematically. Mathematically a Qubit can be presented in terms of its basis vector states as

2 Qubits in terms of their 4 basis vector states can be shown as

Quantum logic gate operation represents the multiplication between matrix representing it and vector representing Quantum state of Qubits. Quantum logic gate acting on k Qubits is represented as 2^k x 2^k unitary matrix. Qubits are input and output depends on type of Quantum logic gate used. With clear understanding of Quantum state mathematics, logic circuits can be designed to realize operations such as addition, multiplication, division, encoding, decoding, multiplexing et al and to form registers to store information on Qubits. Quantum transistors are used to construct Quantum logic gates. Quantum computer components such as processor, memory, I/O devices are created using Logic circuits made of Quantum logic gates. Communication protocols for allowing communication between the various components has been developed and is getting improved. Toffoli, Feynman, CNOT, Pauli X, Pauli Y, Pauli Z, Fredkin are some of the Quantum logic gates we have. Pauli X gate corresponds to rotation of Bloch sphere around X axis by π radian. It flips the state of input Qubit. Other gates have their own effects. We have the math and the logic, work is going on to figure out ways of realizing it to build working Quantum computers.

Models of Quantum computing include Adiabatic, one way, Quantum gate array and Topological. Many methods are available for implementing a Quantum computer such as Nuclear magnetic resonance, Fullerine based ESR, Linear optical, Trapped ion and Quantum dot. Logic of Quantum computing is far more complex than classical binary logic and requires simplification. Apart from this Scientists have to deal with Decoherence while designing these Quantum computers. Decoherence is the characteristic of getting into disorderly and unorganized state due to external interference or internal causes. Quantum state of Qubit changes with slightest of disturbance. To do calulations its essential to maintain their state that is up spin or down spin state for example, for entire duration of calculation. Scientists try to work around this problem by keeping Qubits in super cooled, ultra vacuum environment causing them to get in Quantum mechanical ground state. Liquid Nitrogen or liquid Helium is used for cooling. Preservation of Quantum state has been achieved for a maximum period of upto 2-3 hours so far. With more and more research in Quantum error correction, factors that can affect the state of Qubits are being recognized and ways of neutralizing those factors are getting created by research teams around the world. We only have a certain probability of getting the expected result when computing using quantum mechanical properties because state of particles at Quantum level cannot be measured with absolute certainty, we can only have a probability of one result or other determined according to Heisenberg uncertainty principle. This is why Quantum algorithms have to be run several times in succession to get result expected as per Quantum logical operators (unitary matrix transformations).

Researchers at the National Institute of Standards and Technology (NIST) have now managed a significant breakthrough by ‘teleporting’ or transferring, quantum information from one photon to another over a distance of 100 km of optical fiber. In this experiment as shown in their infographic they created a Photon and then split it in two using a special crystal generating a pair of entangled photons whose states are identical. One of the Entangled Photon is transported to receiving end through a spool of Optical Fiber. Then they generate the input Photon and select its state either early, late or a superposition of both. Input and helper Photon are made to meet at a beam splitter with a 50/50 chance of getting straight through or reflecting at an angle. Detectors developed at NIST and based on superconducting nanowires made of molybdenum silicide are placed suitably to detect the arrival of Photons. When one detector clicks early and the other late, it means Photons are out of phase. Detectors at receiving station measure the state of output Photons from which the state of input photon can be inferred. Thus teleportation of Quantum information is achieved. NIST’s Marty Stevens says “Only about 1 percent of photons make it all the way through 100 km of fiber”.

This is nothing like the general idea of Teleportation but it’s a great progress towards achieving the same. After all this is how the first conventional computers were developed and over 50 years of constant improvements have given us the computer and internet as we know it. Just remember the early experiments on Silicon and Germanium crystals in order to develop the very first transistors. We know that teleportation in principle is achievable because of the insight provided by the team of C.H. Bennett, G. Brassard, C. Crepeau, R. Jozsa, A. Peres, and W. Wootters. They pointed that complete teleportation of quantum information can be achieved in theory at least. Say you want to teleport object A. You can do this by scanning the quantum state of A and another object B together. The unscanned part is transferred to another object C through B which is Entangled with C. Using the scanned data of original Quantum state of object A, one of many treatments can be applied to C in order to recreate the complete original Quantum state of A, transforming C into A. This theory has been used by many scientists to demonstrate quantum teleportation at numerous occasions.

Anton Zeilinger and his team are carrying out Photon teleportation between the Islands of La Palma and Tenerife, over a distance of 143 km through open space. In their experiments they create two identical Photons (Heralded Single Photon), one of which is transported to Tenerife over a high energy Laser. A third Photon which they are going to teleport is brought close to the Photon at La Palma and their interactions are observed. Due to entanglement the state of distant Photon changes with the state of the Photon at the sending station. The observations made at sending station are used to convert the photon at Tenerife into an exact copy of the third Photon. A number of Photons have already been teleported using this method.

These experiments are very early steps towards making Quantum communication possible and creating Quantum Internet. Since a qubit cannot be copied, as any attempt to do so will alter the information due to uncertainty principle, information can be sent and received securely over Quantum Internet. Work is going on for the development of Quantum computer at institutes like MIT, IQC and corporations like IBM, Google. With Quantum Internet all the Quantum computers in world can be instantaneously connected and with help of Quantum Entanglement may be we could create a universal network one day, enabling us to communicate from anywhere in the universe instantaneously.

References:
1) https://arxiv.org/pdf/1501.00011.pdf

2) http://newsroom.unsw.edu.au/news/quantum-computing-taps-nucleus-single-atom

3) http://researcher.watson.ibm.com/researcher/files/us-bennetc/BBCJPW.pdf
4) https://arxiv.org/pdf/quant-ph/9511027.pdf

Image credits goes to respective sources.

New Graphene Based Ink for High Speed Manufacturing of Electronics

noreply@blogger.com (Rishi Mishra) — Fri, 23 Oct 2015 06:00:00 +0000

Developed by researchers at the University of Cambridge in collaboration with Cambridge-based technology company Novalia, by applying NMP solvent to large flakes of Graphene, this ink can be used in consumer grade inkjet printers such as Epson Stylus 1500 cartridges without clogging them. This allows for high speed printing of Electronic circuits such as a paper thin MIDI controller, at a cost which is much lower than that of the current practice of using big industrial printers for such jobs. So in near future if you want a device, you can just design and print it yourself right at your desk. Not only large scale manufacturers but anyone with a compatible desk printer can create circuits with this tech. Using this ink, researchers have managed to print thin film transistors on silicon base.

Science daily reports- 'Researchers from Aneeve Nanotechnologies, a startup company at UCLA's on-campus technology incubator at the California Nano Systems Institute (CNSI), have used low-cost ink-jet printing to fabricate the first circuits composed of fully printed back-gated and top-gated carbon nanotube based electronics for use with OLED displays. The team made carbon nanotube thin film transistors with high mobility and a high on-off ratio, completely based on ink-jet printing. They demonstrated the first fully printed single-pixel OLED control circuits, and their fully printed thin-film circuits showed significant performance advantages over traditional organic based printed electronics.'

References:
1) http://www.printedelectronicsworld.com/articles/4119/graphene-inks-at-university-of-cambridge

Image credits goes to respective sources.

Self Driving Cars are on Road

noreply@blogger.com (Rishi Mishra) — Wed, 21 Oct 2015 12:00:00 +0000

With version 7.0 of Tesla software, Model S can drive in autopilot mode, hands free. At low speeds the car can answer you summoning and can park itself in the garage as well. 2014 Mercedes S class has active lane assist capability too, but it wont turn on unless your hands are on the steering. This is where Tesla scores. As awesome as it sounds, you are still required to be paying attention during autopilot. If the sensors or any other component malfunctions, responsibility of resulting accident will still be of the person who is supposed to be driving, that is, the car drives but still, you are the driver.

The Tesla Motors Team posts- 'A forward radar, a forward-looking camera, 12 long-range ultrasonic sensors positioned to sense 16 feet around the car in every direction at all speeds, and a high-precision digitally-controlled electric assist braking system. Today's Tesla Version 7.0 software release allows those tools to deliver a range of new active safety and convenience features, designed to work in conjunction with the automated driving capabilities already offered in Model S. This combined suite of features represents the only fully integrated autopilot system involving four different feedback modules: camera, radar, ultrasonic, and GPS. These mutually reinforcing systems offer real time data feedback from the Tesla fleet, ensuring that the system is continually learning and improving upon itself. Autopilot allows Model S to steer within a lane, change lanes with the simple tap of a turn signal, and manage speed by using active, traffic-aware cruise control. Digital control of motors, brakes, and steering helps avoid collisions from the front and sides, as well as preventing the car from wandering off the road. Your car can also scan for a parking space, alert you when one is available, and parallel park on command.'

While Google's self driving cars roam roads in Texas watch

BMW235i Autonomous drifting

Image credits goes to respective sources.

Brain Plasticity- Brain's Ability to Modify its Structure and Function

noreply@blogger.com (Rishi Mishra) — Wed, 21 Oct 2015 09:30:00 +0000

Brain has the capability to change itself and a new research is going to be conducted to investigate just that and find more about the what, why, how of this extraordinary cerebral process. The initial research team consists of prominent Neuroscientists from UC Berkely, Berkely lab, Livermore lab and Physicists, Engineers, Computer Scientists.

Brain plasticity forms the base for our ability to learn and improve ourselves. Brain keeps bettering its abilities with time, a lot fast during initial years but slowing as it gets older.

Named Kavli Institute for Fundamental Neuroscience (Kavli IFN), established as a partnership between The Kavli foundation and UCSF with an initial funding of 20 Million Dollars alongside additional startup funding, the Institute aims to develop greater insight into Brain plasticity with the edge coming from collaborating Physicists, Engineers and Computer Scientists. Kavli foundation has Pledged more than $100 million for this cause in association with its many University partners.

References:
1) https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2896818/

Image credits goes to respective sources.

A Much More Efficient Way for Finger Printing Crime Scenes

noreply@blogger.com (Rishi Mishra) — Wed, 21 Oct 2015 07:33:00 +0000

CSIRO Material scientist Dr Kang Liang, developed a technique in which tiny extremely porous metal organic framework (MOF) crystals combine with fingerprint residue on a molecular level causing it to glow brightly under a back light. In conventional method, sometimes the samples have to be sent for heat and vacuum treatment delaying the investigations. The new method allows for precise digital imaging of fingerprints on almost any surface, right on spot. Published in Advanced Materials Journal on October 20, 2015, the research claims to reduce the number of steps in finger printing, while adding more precision to the prints. MOF crystals applied as liquid drops combine rapidly with finger print residue causing it to glow brightly under UV light in around 30 seconds. The method works well for faint residues as well.

Dr Liang said- “Because it works at a molecular level it’s very precise and lowers the risk of damaging the print.” The method is tested on nonporous surfaces including window and wine glass, metal blades and plastic light switches, with successful results. CSIRO Website reports- 'The strong luminescent effect creates greater contrast between the latent print and surface enabling higher resolution images to be taken for easier and more precise analysis. MOF crystals have a number of benefits in that they are cheap, react quickly and can emit a bright light. The technique doesn’t create any dust or fumes, reducing waste and risk of inhalation.'

References:
1) https://www.csiro.au/en/News/News-releases/2015/Glowing-fingerprints-to-fight-crime

Image credits goes to respective sources.

Smart homes-Smart cities-Smarter planet

noreply@blogger.com (Rishi Mishra) — Mon, 19 Oct 2015 14:04:00 +0000

The incorporation of digital systems into control of home appliances, Electric systems, home security and monitoring has made it possible to control and optimize them through a smart phone. Signal communication happens between smart devices and controller over a mix of wireless and wired medium using com ports, which means you can control your device, while at home and can also monitor and control them when you are away. That is to say you can still see what's going at home all the time while at office or in the metro. You can know the status of your systems anytime you want, from anywhere.

Com port equipped smart devices and appliances can communicate with each other, paving way for smart management of utilities (Electricity, Water and Fuel conservation). A national grid of such devices will help in conservation of energy, water and other utilities on a national level and an International grid could do much more, may be even establish world peace. Greater ease and more effective home security is just the start. We will be creating the world wide network of smart devices and smart appliances, just the way we have created the world wide network of computers, something like IBM's smarter planet idea. We already have smart Electric grids in place around the world which is helping conserve resources and reduce the waste of Electric power in form of heat, by matching supply with demand with the help of smart meters and other equipment installed alongside. Data is transmitted by smart devices to a hub where a controller processes it using an algorithm and generates control signals for sub controllers for realizing optimal utilization, conservation and security. Google's Nest and start-ups like Canary are already selling popular smart systems creating smart homes. Global smart home market was valued at $20.38 billion in 2014.

Meanwhile watch

References:
1) https://arxiv.org/ftp/arxiv/papers/1509/1509.05722.pdf

Image credits goes to respective sources.

About 99% Mass of Protons and Neutrons Keeps Going In and Out of Existence

noreply@blogger.com (Rishi Mishra) — Mon, 19 Oct 2015 11:30:00 +0000

Nearly 1% mass of Protons and Neutrons is attributed to the mass of the three quarks that constitutes them and the remaining 99% is attributed to the strong nuclear force that binds these Quarks together. The Strong Nuclear Force is carried by a field of Gluons (virtual particles), which keeps fluctuating in and out of existence. The energy of these fluctuations is what renders the remaining mass of Protons and Neutrons and since together these Nucleons account for nearly all the mass of normal matter, it can be declared that close to 99% mass of normal matter keeps going in and out of existence. Equations of quantum chromodynamics, or QCD, describes the strong nuclear force. In most cases, these equations are too difficult to solve. Consequentially a new approach called Lattice QCD was developed which models smooth space and time as a grid of pixels. This allows for creation of close computer simulations of Strong Nuclear Force.

Virtual Gluons, Virtual Quarks and Anti Quarks are constituents of Quantum vacuum. Virtual Quark-Anti Quark pairs can appear suddenly and for an instant transform a proton into a more exotic particle. In fact, the proton as we know it is the combination of all these possibilities going at once. Virtual quarks make the calculations much more complicated, involving a matrix of more than 10,000 trillion numbers, says team member Stephan Dürr of the John von Neumann Institute for Computing in Jülich, Germany. A calculation involving that much data is beyond the capability of computers we have currently.

To calculate the mass of protons and neutrons using computer simulations, Dürr’s team used months of time on parallel computer network at Jülich. The network can handle 200 teraflops or 200 trillion arithmetical calculations per second. Dürr says- “We spent an enormous effort to make sure our code would make optimum use of the machine”. Without accounting for the Virtual Quarks, the simulations got proton mass wrong by about 10%, with them, Dürr gets a figure within 2% of the value measured by experiments.

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References:
1) https://arxiv.org/pdf/0906.3599.pdf

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