First Generation (1941-1956)
World War gave rise to numerous developments and started off the computer age. Electronic Numerical Integrator and Computer (ENIAC) was produced by a partnership between University of Pennsylvania and the US government. It consisted of 18,000 vacuum tubes and 7000 resistors. It was developed by John Presper Eckert and John W. Mauchly and was a general purpose computer. "Von Neumann designed the Electronic Discrete Variable Automatic Computer (EDVAC) in 1945 with a memory to hold both a stored program as well as data." Von Neumann's computer allowed for all the computer functions to be controlled by a single source.
Then in 1951 came the Universal Automatic Computer (UNIVAC I), designed by Remington rand and collectively owned by US census bureau and General Electric. UNIVAC amazingly predicted the winner of 1952, presidential elections, Dwight D. Eisenhower.
In first generation computers, the operating instructions or programs were specifically built for the task for which computer was manufactured. The Machine language was the only way to tell these machines to perform the operations. There was great difficulty to program these computers and more when there were some malfunctions. First Generation computers used Vacuum tubes and magnetic drums (for data storage).
The IBM 650 Magnetic Drum Calculator
Second Generation Computers (1956-1963)
The invention of Transistors marked the start of the second generation. These transistors took place of the vacuum tubes used in the first generation computers. First large scale machines were made using these technologies to meet the requirements of atomic energy laboratories. One of the other benefits to the programming group was that the second generation replaced Machine language with the assembly language. Even though complex in itself Assembly language was much easier than the binary code.
Second generation computers also started showing the characteristics of modern day computers with utilities such as printers, disk storage and operating systems. Many financial information was processed using these computers.
In Second Generation computers, the instructions (program) could be stored inside the computer's memory. High-level languages such as COBOL (Common Business-Oriented Language) and FORTRAN (Formula Translator) were used, and they are still used for some applications nowadays.
The IBM 7090 Console in the Columbia Computer Center machine room, 1966. Pictured: A group of particle physicists who discovered the violation of charge-conjugation invariance in interactions of intermediate strength: Charles Baltay and Lawrence Kirsch of Nevis Lab (back row); Juliet Lee-Franzini of SUNY Stony Brook and team leader Paulo Franzini of Nevis Lab [V1#7].
Photo: Columbia Computer Center Newsletter, V1#7, Aug 1966, Columbiana Archive.
Although transistors were great deal of improvement over the vacuum tubes, they generated heat and damaged the sensitive areas of the computer. The Integrated Circuit(IC) was invented in 1958 by Jack Kilby. It combined electronic components onto a small silicon disc, made from quartz. More advancement made possible the fittings of even more components on a small chip or a semi conductor. Also in third generation computers, the operating systems allowed the machines to run many different applications. These applications were monitored and coordinated by the computer's memory.
The IBM 360/91
Fourth Generation (1971-Present)
Fourth Generation computers are the modern day computers. The Size started to go down with the improvement in the integrated circuits. Very Large Scale (VLSI) and Ultra Large scale (ULSI) ensured that millions of components could be fit into a small chip. It reduced the size and price of the computers at the same time increasing power, efficiency and reliability. "The Intel 4004 chip, developed in 1971, took the integrated circuit one step further by locating all the components of a computer (central processing unit, memory, and input and output controls) on a minuscule chip."
Due to the reduction of cost and the availability of the computers power at a small place allowed everyday user to benefit. First, the minicomputers which offered users different applications, most famous of these are the word processors and spreadsheets, which could be used by non-technical users. Video game systems like Atari 2600 generated the interest of general populace in the computers.
In 1981, IBM introduced personal computers for home and office use. "The number of personal computers in use more than doubled from 2 million in 1981 to 5.5 million in 1982. Ten years later, 65 million PCs were being used." Computer size kept getting reduced during the years. It went down from Desktop to laptops to Palmtops. Mackintosh introduced Graphic User Interface in which the users don’t have to type instructions but could use Mouse for the purpose.
The continued improvement allowed the networking of computers for the sharing of data. Local Area Networks (LAN) and Wide Area Network (WAN) were potential benefits, in that they could be implemented in corporations and everybody could share data over it. Soon the internet and World Wide Web appeared on the computer scene and fomented the Hi-Tech revolution of 90's.
Fifth generation computers
Fifth generation computers are mainly future computers. Of course some modern computers also belong to this generation. The aim of these computers is to develop devices that respond to natural language input and are capable of learning and self-organization. In these computers massive numbers of CPUs are used for more efficient performance. Voice recognition is a special feature in these computers. By using superconductors and parallel processing computer geeks are trying to make artificial intelligence a reality. Quantum computing, molecular and nanotechnology will change the face of computers in the coming years.Fifth generation computer.


Researchers at Princeton have developed a method to cause perovskite particles to self-assemble. They say this produces more efficient, stable and durable perovskite LEDs that would be easier to manufacture than current LEDs, while emitting very strong light, that is easily tuned to display different colours. The crystal and diamond structure of perovskite exhibits either superconductivity or semi-conductivity depending on structure. The researchers’ advance was to add long-chain ammonium halide to the perovskite solution during processing, which constrained the formation of crystal in the film. Instead, what were formed were 5-10 nanometre crystallites which made the halide perovskite films far thinner and smoother. This meant that the LEDs emitted more photons per number of electrons entering the device than using alternative production methods.
Kyoto University, working with Osaka Gas, has built a proof-of-concept nanoscale semiconductor that narrows wavelength bandwidth to concentrate light energy in solar cells. Kyoto researchers claim that current solar cells are not good at converting visible light into electrical power, having just 20% efficiency. The scientists wanted to capture and convert light produced by gas flames, so they chose silicon as it can withstand temperatures of up to 1000 degrees Celsius. They etched silicon plates to create a grid of identical, equidistant rods the structure of which could be altered to catch different wavelength bandwidths. Using this material, the scientists showed that they could raise the conversion efficiency of light to electricity by 40%.
Scientists believe that misshapen proteins, called amyloids, can clump together and form masses in the brain which block normal cell function, leading to neurodegenerative disorders such as Alzheimer’s. A team of researchers from the University of Michigan and the University of Fribourg have developed a technique to measure amyloids’ shapes, volume, electrical charge, rotation speed and binding propensity. They call this information a ‘5D fingerprint’. Having more measurement categories could enable doctors to better understand, treat and predict problems associated with amyloids. The researchers created a nanopore (holes of 10-30 nanometres diameter, small enough that only one protein molecule can pass through at a time) on a substrate. The nanopore was sandwiched between saline solution layers to which an electric current was applied. By reading fluctuations in the current as the molecule passes through the pore researchers were able to determine the molecule’s ‘5D fingerprint’.
Scientists from the Daegu Gyeongbuk Institute of Science and Technology in Korea have discovered a way to control colour changes by adding a coating of nanometres thick semiconducting materials to a metal substrate. Through the addition of a thin germanium film of 5-25 nanometres to a gold substrate the team could control the colour produced (through thin-film interference) – such as yellow, orange, blue and purple. The scientists hope that in the future a similar method could be used to create patterns or symbols on the substrate.
Researchers at Northwest University have created a new type of nanomaterial called a COF colloid. Covalent organic frameworks (COFs) are strong polymers with many tiny pores which can be used to store for example energy, drugs or other cargo. These COFs usually come as a powdery substance which is, according to NWU, almost useless. However, the NWU team suspended the COF in a liquid ink which allows the material to be engineered to arbitrary sizes and thicknesses – opening up their potential use as designed carriers of drugs or other cargo to specific locations within the body. Moreover, the team discovered that they could watch the process of how the molecules come together to create COF colloids by using a transmission electron microscope.
Researchers at Aalto University in Finland have created a nanoscale laser using nanoparticles. The device uses silver nanoparticles arranged in a periodic array. The optical feedback needed to generate the laser light is provided by radiative coupling (bouncing the captured light back and forth) between silver nanoparticles which effectively act as antennas. To produce a strong laser light the distance between particles was matched with the lasing wavelength to that they all radiate in unison. To provide the input energy for the laser organic fluorescent molecules were added. The benefits of such devices are that the laser can be made very small and very fast, which will be of use for chip-scale light sources in optical components.
Scientists at the University of Massachusetts Amherst have discovered a type of conductive natural nanowire produced by bacteria. The wires, known as microbial nanowires, are protein filaments which bacteria use to make electrical connections with other microbes or minerals. The team has been looking at several species of geobacter bacteria for their potential use in electronics. In the most recent study the scientists used genetically modified G. Sulfurreducens which produces more filaments and expresses filament genes from many different types of bacteria, and discovered that the microbial nanowires are highly conductive (around 5 mS/cm) which the scientists claim is comparable to that of metallic nanostructures. The scientists attribute the conductivity to a large amount of aromatic amino acid allowing for improved conductivity along the filament. As a result they believe these have good potential for use in electronics.
A microscopic mechanical drum – a vibrating aluminium membrane – has been cooled to less than one-fifth of a single quantum (packet of energy), which is lower than quantum physics would predict. The work from the National Institute of Standards and Technology (NIST) provides the possibility of cooling an object to absolute zero which would make it more sensitive as a sensor, store information for longer, or even be used in quantum computing according to NIST scientists. To achieve this effect the scientists manipulated the resonance of the cavity through the application of a microwave tone at a frequency below the cavity’s resonance. The beating of the drum’s surface releases photons; with each photon that leaves the drum as a result of the microwave excitation the drum loses heat.
Scientists at The University of Manchester have braided multiple molecular strands to enable the tying of a very tight knot. The knot has eight crossings in a 192-atom closed loop which is about 20 nanometres long. The knot was created by a technique known as self-assembly, in which molecular strands are woven around metal ions causing crossing points. The ends of the strands were then fused by a chemical catalyst to close the loop and create the knot.
The scientists think that this will enable further study into how molecular knotting affects strength and elasticity of materials which could lead to the knowledge of how to weave polymer strands to create new materials.
The Rosetta Disk’s goal is to make a catalogue of languages and important documents to be preserved for the long term. On the small wearable pendant can be found microscopic pages. With the help of a microscope the preamble to the universal declaration of human rights can be read in 327 languages, a Swadesh Vocabulary List by PanLex Project (a phrasebook listing identical words and phrases in 719 languages), The Clock of The Long Now by Steward Brand and diagrams for the 10,000-year clock. This ‘wearable’ is made using a process similar to microchip lithography, which uses a laser bean to write onto a photosensitive material coated on a glass plate. These recorded features are then developed like a film, after which the plate is electroformed, which results in a disk made of solid nickel. The text is slightly raised from the surface, and requires optical magnification to read.


When we make the move to quantum computers, we’ll need a quantum internet. And that’s why a team of researchers at Tsinghua University in China have built what they call the world’s first quantum router.
Often called the holy grail of the tech world, a quantum computer uses the seemingly magical principles of quantum mechanics to achieve speeds well beyond today’s machines. At the moment, these counterintuitive contraptions are little more than lab experiments, but eventually, they’ll instantly handle calculations that would take years on today’s machines.
The trick is that whereas the bits of a classical computer can only hold one value at any given time, a quantum bit — or qubit — can hold multiple simultaneous values, thanks to the superposition principle of quantum mechanics.
But if we build a world of quantum computers, we’ll also need a way of transporting quantum data — the multiple values so delicately held in those qubits — from machine to machine. Led by post doctoral researcher Xiuying Chang, the Tsinghua University team seeks to provide such transportation, and though their work is still largely theoretical, they’ve taken an important step in the right direction.
“Their router isn’t practical right now,” says Ari Dyckovsky, a researcher with National Institute of Standards and Technology (NIST) who specializes in quantum entanglement, “but it adds another reason that people should keep researching in this area.”
Yes, there are already ways of moving quantum data between two places. Thanks to quantum entanglement — another mind-bending principle of quantum mechanics — you can move data between two quantum systems without a physical connection between them. And you can send quantum data across a single fiber-optic cable using individual photons.
“Their router isn’t practical right now. But it adds another reason that people should keep researching in this area.”
But for a true quantum internet, you need a way of routing quantum data between disparate networks — i.e., from one fiber-optic cable to another — and at the moment, that’s not completely possible. The problem is that if you look at a qubit, it’s no longer a qubit.
In a classic computer, a transistor stores a single “bit” of information. If the transistor is “on,” for instance, it holds a “1.” If it’s “off,” it holds a “0.” But with quantum computer, information is represented by a system that can an exist in two states at the same time. Thanks to the superposition principle, such a qubit can store a “0” and “1” simultaneously. But if you try to read those values, the qubit “decoheres.” It turns into a classical bit capable of storing only one value. To build a viable quantum computer, researchers must work around this problem — and they must solve similar problems in building a quantum internet.
The internet is all about routing data between disparate networks. A router uses a “control signal” to route a “data signal” from network to network. The trouble with a quantum router is that if you read the control signal, you break it. But in a paper recently published to the net, Xiuying Chang and her team describe an experiment in which they build a quantum router — complete with a quantum control signal — using two entangled photons.
“This leads to more freedom to control the route of quantum data,” Luming Duan, who worked on the paper, tells Wired, “and I believe it is a useful device for future quantum internet.”
As described by Technology Review, the team begins the experiment with a photon that exists in two quantum states at the same time: both a horizontal and a vertical polarization. Then they convert this single photon into two entangled protons — which means they’re linked together even though they’re physically separate — and both of these are also in a superposition of two quantum states. One photon serves as the control signal, and it routes the other photon — the data signal.
The rub is that the method isn’t suited to large-scale quantum routing. You can’t expand it beyond the photons. “It is a nice check that coherence is maintained while converting between polarization and path entanglement, which will be an important operation for a large-scale quantum network,” says Steven Olmschenk, an assistant professor of physics and astronomy at Denison University. “But as the authors are careful to point out, the implementation that they have demonstrated cannot be scaled up, and is missing some of the key — and hard — features that will be necessary in a more general implementation.”
In other words, the experiment only transmits one qubit at a time — and the quantum internet needs a bit more bandwidth than that.
But this will come.Go Back to Top. Skip To: Start of Article.


Trapping light means either stopping the light temporally or confining the light in space. Scientists have also been able to trap a light pulse in a tiny enclosure bounded by metamaterials; the light pulse retains its form but is kept from moving away.
Previously only light of a short frequency interval could be trapped in this way. Now a group of scientists at Nanjing University in China have shown how a rather wide spectrum of light -- a rainbow of radiation -- can be trapped in a single structure. They propose to do this by sending the light rays into a self-similar-structured dielectric waveguide (SDW) -- essentially a light pipe with a cladding of many layers. Light of different colors propagates separately in (or is contained within) different layers, the layers each being tailored by color. They replace the conventional periodically-spaced, identical cladding layers with a non-periodic, self-similar pattern of successive layers made from two materials, A and B, with slightly different thicknesses and indices of refraction. Self similarity, in this case, means that the pattern of layers successively outwards would be as follows: A, AB, ABBA, ABBABAAB, and so forth.
"The effect might be applied for on-chip spectroscopy or on-chip 'color-sorters,'" says Ruwen Peng, one of the Nanjing researchers. "It might also be used for photon processing and information transport in optical communications and quantum computing." Peng and her associates, who published their results in the American Institute of Physics' journal Applied Physics Letters, expect that they can create trapped "rainbows" for light in many portions of the electromagnetic spectrum, including microwave, terahertz, infrared, and even visible.
The article "'Rainbow' trapped in a self-similar coaxial optical waveguide" by Qing Hu, Jin-Zhu Zhao, Ru-Wen Peng, Feng Gao, Rui-Li Zhang, and Mu Wang was published online in the journal Applied Physics Letters in April, 2010. See: http://link.aip.org/link/APPLAB/v96/i16/p161101/s1
Journalists may request a free PDF of this article by contacting email@example.comABOUT APPLIED PHYSICS LETTERS
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What is a ruby and why is it red? Why is the friction so low on a sled? On a plot of P versus T, plot out the the phases of helium-three....
A favorite professor loved to craft simply stated preliminary exam questions that happened rhyme. Parts were often difficult - here the second question is still not fully answered. The ruby question is good as there are layers of depth to show how much you have thought about it.
Sapphire, ruby and corundum are all very stable crystalline forms of Al2O3 - aluminum oxide.1 In ruby and sapphire a percent or so of the aluminum atoms are replaced by something else - chromium in the case of ruby. Chromium is a bit larger and has a different shape than aluminum. The result is a small distortion of the arrangement of oxygens around the chromiums. The most obvious visual difference is how the two crystals absorb light. The distortions change how visual light is absorbed. Pure corundum doesn't strongly absorb, ruby absorbs in the violet and yellow-green making it appear red.2
Structure is one of the features used to categorize solids. A crystal is a solid with a structure of atoms or molecules that repeat in three dimensions with a regular pattern called a lattice - single crystal snowflakes, table salt, diamonds... Groupings of smaller crystals form polycrystals - most metals, large snowflakes, ice and ceramics are polycrystals. Amorphous solids lack such order .. glass and almost anything organic for example.
Impurities in crystals lead to changes in physical properties like the colors of gem stones. But there are many ways to disrupt a pure crystal lattice. Some locations can be empty, filled with some impurity or dislocations to the pattern of the crystal can lead to strong steel. Impurities create different electrical properties that allow semiconductors to exist - without ongoing theoretical and experimental work from the 40s, the integrated circuit wouldn't exist.
Steel is largely iron with a few other things thrown in. Carbon turned out to be a big winner, but you have to get the recipe right and there are tens of thousands of variations giving a wide range of properties. Successful recipes were carefully guarded secrets .. the special steels used in Japanese swords, steels from Toledo and Damascus became legendary. Sometimes there was a bit of odd baggage - one recipe involved adding the urine from red-haired boys. Serious progress had to wait for real science.
It is possible to have two dimensional structures with regular repeating patterns - graphene is a single layer of hexagonally packed carbon atoms. Amazing properties that lead in a recent Nobel prize in physics. You can easily make some yourself with a pencil and a bit of scotch tape.3
But it gets stranger...
It is natural for a physicist to think in more than three dimensions. Space-time, the structure of space and time we live in, has four dimensions. Other more abstract hypotheses have eight, nine, eleven, twenty six. Calculations can have large numbers of dimensions. Sometimes this is practical in the real world - cryptology and cellphone modulation schemes both make use of higher dimensionalities.
So it is natural to think of a four dimensional crystal -- one in space and time. And usually, for a variety of reasons, you quickly rule it out as non-physical. Afew years ago Frank Wilczek didn't throw it away and presented the idea of a time crystal that exists in four dimensions. The physical pattern is be stable, but a property of it repeats in time. Instead of regularly repeating atoms there would be a regularly repeating internal motion.
It was very controversial - it looked like a perpetual motion machine, but loophole was spotted. Properties like electron spin might bunch up in direction at regular intervals in time .. a repeating lattice in time. As crazy as it sounds a few groups tried to make their own time crystals and two appear to have succeeded with papers passing peer review and due out in the near future. Here's one of the early papers and a high level description. Much more is likely to emerge in the next few months.
Apart from being beautiful it has the potential to be incredibly useful. Quantum computing has the fundamental challenge of maintaining entanglement over time in a macroscopic object. It could be that time crystals are a mechanism to successfully address the problem and who knows what else... perhaps years, perhaps decades, perhaps never...
ah the frontier
1 In pure corundum three electrons from each aluminum join with six O2- ions in an octahedral group. The aluminums are left without unpaired electrons and their energy levels are filled. This configuration is exceptionally stable and strong and is also colorless.
2 There is also a fluorescent emission in the red making the crystals beautifully red. This emission property is central to making lasers out of rubies.
3 rather than tell you, just watch this:)
Not a recipe, but a bit of technique. It's Winter and that means reasoning with hard Winter squashes. I find it's much easier if you par-cook (not boil) them for a few minutes. Find a big enough pot and let it simmer for two or three minutes. If the squash is larger than the pot, just turn it over.
That's it. Now it should slice easily. Something frustrating becomes easy.


The problem comes in finding the dividing line between the two worlds -- or even in establishing that such a line exists. To that end, Keith Schwab, associate professor of physics who moved to Cornell this year from the National Security Agency, and colleagues have created a device that approaches this quantum mechanical limit at the largest length-scale to date.
And surprisingly, the research also has shown how researchers can lower the temperature of an object -- just by watching it.
The results, which could have applications in quantum computing, cooling engineering and more, appear in the Sept. 14 issue of the journal Nature.
The device is actually a tiny (8.7 microns, or millionths of a meter, long; 200 nanometers, or billionths of a meter, wide) sliver of aluminum on silicon nitride, pinned down at both ends and allowed to vibrate in the middle. Nearby, Schwab positioned a superconducting single electron transistor (SSET) to detect minuscule changes in the sliver's position.
According to the Heisenberg uncertainty principle, the precision of simultaneous measurements of position and velocity of a particle is limited by a quantifiable amount. Schwab and his colleagues were able to get closer than ever to that theoretical limit with their measurements, demonstrating as well a phenomenon called back-action, by which the act of observing something actually gives it a nudge of momentum.
"We made measurements of position that are so intense -- so strongly coupled -- that by looking at it we can make it move," said Schwab. "Quantum mechanics requires that you cannot make a measurement of something and not perturb it. We're doing measurements that are very close to the uncertainty principle; and we can couple so strongly that by measuring the position we can see the thing move."
The device, while undeniably small, is -- at about ten thousand billion atoms -- vastly bigger than the typical quantum world of elementary particles.
Still, while that result was unprecedented, it had been predicted by theory. But the second observation was a surprise: By applying certain voltages to the transistor, the researchers saw the system's temperature decrease.
"By looking at it you cannot only make it move; you can pull energy out of it," said Schwab. "And the numbers suggest, if we were to keep going on with this work, we would be able to cool this thing very cold. Much colder than we could if we just had this big refrigerator."
The mechanism behind the cooling is analogous to a process called optical or Doppler cooling, which allows atomic physicists to cool atomic vapor with a red laser. This is the first time the phenomenon has been observed in a condensed matter context.
Schwab hasn't decided if he'll pursue the cooling project. More interesting, he says, is the task of figuring out the bigger problem of quantum mechanics: whether it holds true in the macroscopic world; and if not, where the system breaks down.
For that he's focusing on another principle of quantum mechanics -- the superposition principle -- which holds that a particle can simultaneously be in two places.
"We're trying to make a mechanical device be in two places at one time. What's really neat is it looks like we should be able to do it," he said. "The hope, the dream, the fantasy is that we get that superposition and start making bigger devices and find the breakdown."
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Quantum mechanical phenomena . Quantum Mechanics. The study between quanta and elementary particles. Quanta – an indivisible entity of a quantity that has the same value as Planck’s constant which is related to energy and momentum of elementary particles.
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Quantum mechanical phenomena
The study between quanta and elementary particles.
Quanta – an indivisible entity of a quantity that has the same value as Planck’s constant which is related to energy and momentum of elementary particles.
Elementary Particle – a particle not known to have substructure or be composed of smaller particles.
Quantum Mechanics (cont.)
It generalizes all classical theories (excluding general relativity), results are typically only observable on the atomic and subatomic scales.
The foundations of quantum mechanics were established during the first half of the twentieth century by Werner Heisenburg, Max Planck, Albert Einstein, Neils Bohr, Erwin Schrodinger, and Wolfgang Pauli
The modern world of physics is notably founded on two tested and demonstrably sound theories of general relativity and quantum mechanics; theories which appear to contradict one another. However, while they do not directly contradict each other theoretically, they are resistant to being incorporated within one model.
Quantum Mechanics (cont.)
Einstein himself is well known for rejecting some of the claims of quantum mechanics. While clearly inventive in this field, he did not accept the more philosophical consequences and interpretations of quantum mechanics
…these consequences are know as Quantum Mechanical Phenomena.
Quantum Mechanical Phenomena
Quantum mechanical phenomena include things such as:
--the EPR paradox
Quantum Teleportation is a quantum protocol where quantum information can be transmitted using an entangled pair of qubits.
Qubit - a two dimensional vector that measures quantum information.
Quantum Teleportation cannot teleport matter, energy, or information at a speed faster than light, but it is useful for quantum communication and calculations.
Quantum Teleportation (cont.)
Assume that A and B share an entangled qubit AB. Let C denote the qubit A wishes to transmit to B.
A applies a unitary operation on the qubits AC and measures the result to obtain two classical bits. In this process, the two qubits are destroyed. B's qubit, B now contains information about C however the information is somewhat randomized. More specifically, B's qubit is in one of four states uniformly chosen at random and B cannot obtain any information about C from his qubit.
A provides her two measured qubits, which indicate which of the four states B possesses. B applies a unitary transformation which depends on the qubits he obtains from A, transforming his qubit into an identical copy of the qubit C.
The EPR Paradox
The EPR paradox is a dichotomy, which means it yields two results but they’re coincide with each other.
EPR stands for Einstein, Podolsky, and Rosen; who are the people that introduced the thought to show that quantum mechanics isn’t totally physical.
The EPR paradox draws on a phenomenon predicted by quantum mechanics to show that measurements performed on spatially separated parts of a quantum system can apparently have an instantaneous influence on one another. This result is known as “nonlocal behavior” or as Einstein put “a spooky action at a distance”.
The EPR Paradox (cont.)
The EPR paradox relates to the concept of locality.
Locality states that a physical process at one location should have no immediate effect on something at a different location.
Usually information cannot be transferred faster than the speed of light without contradicting causality, however if you combine quantum mechanics with classical views of physics you can contradict locality without contradicting locality, thus resulting in The EPR Paradox!
Quantum Entanglement is a quantum mechanical phenomena where the quantum states of two or more objects are linked so one object can’t be completely described without mentioning the other(s) even thought they may be spatially separated.
In theory this results in correlations between physical properties of remote systems.
The distance between the two
particles is irrelevant. Some
physicists have theorized that
there are hidden variables that
are determined when the pair of
particles are entangled.
The rules of quantum mechanics curiously appear to prevent an outsider from using these methods to actually transmit information, and therefore do not appear to allow for time travel or Faster Than Light communication.
This misunderstanding seems to be widespread in popular press coverage of quantum teleportation experiments. The ideas are commonly used in science fiction literature without the complicated explanation of course.
The assumption that time travel or superluminal communications is impossible allows one to derive interesting results such as the no cloning theorem, and how the rules of quantum mechanics work to preserve causality is an active area of research.


Higher Education Education
All Higher Education Education Resources
- Air Pollution Model (aerial)
Explore the connections between point-source pollution, geography, and wind on regional air quality.
- Air Pollution Model (cross-section)
Explore the connections between pollution sources, weather, geography, and air quality.
- Atomic Structure
Explore ion formation, isotopes, and electron orbital placement using interactive models of atomic structure.
- Boiling Point
This model allows you to explore why polar and non-polar substances have very different boiling points.
- Can We Feed the Growing Population?
Explore the interconnected resources that make up our agricultural system as you consider food production.
Explore the effects of homogeneous catalysts.
- Cellular Respiration
Explore how your body converts the chemical energy of glucose into the chemical energy of ATP.
- Ceramic Forces
Explore what happens when a force is exerted on a ceramic material.
- Charged and Neutral Atoms
Explore the role of charge in interatomic interactions.
- Comparing Attractive Forces
Explore different attractive forces between various molecules.
- Comparing Dipole-Dipole to London Dispersion
Investigate the difference in the attractive force between polar and non-polar molecules.
- Concentrating Charge and Electric Fields
Take the same amount of charge and try spreading it out or concentrating it. What effect does that have on other moving charged particles?
- Crookes Tube
Experiment with a simulated Crookes tube for qualitative results similar to Thomson's experiments in which the electron was discovered.
- DC Circuits: Parallel Resistances
Learn about parallel circuits by interacting with a virtual breadboard.
- DC Circuits: Series Resistances
Learn about series circuits by interacting with a virtual breadboard.
- DC Circuits: Series-Parallel Resistances
Learn about series-parallel circuits by interacting with a virtual breadboard.
- Diffusion Across a Semipermeable Membrane
Explore the role of pore size in the diffusion of a substance across a membrane.
- Diffusion and Molecular Mass
Explore the role of a molecule's mass with respect to its diffusion rate.
- Diffusion and Temperature
Explore the role of temperature in the rate of diffusion of a substance.
- Diffusion of a Drop
Explore the random molecular motion of a dye in water.
- Diffusion, Osmosis and Active Transport
Explore how water and ions can diffuse both passively and actively through cell membranes.
- DNA to Protein (HTML5 Model)
Explore how the code embedded in DNA is translated into a protein. DNA transcription and mRNA translation are modeled.
- DNA to Protein (Java-based Activity)
Explore what DNA is and how proteins are synthesized from the genetic information stored in it.
- Electrons in Atoms and Molecules
The interactions of electrons with matter are central to many technologies from transistors to sophisticated quantum computing.
Discover how atoms can be charged, and manipulate charge and distance to examine Coulomb's Law.
- Excited States and Photons
Investigate how atoms can be excited to give off radiation.
- Exploring Electron Properties
Compare the behavior of electrons to that of other charged particles to discover properties of electrons such as charge and mass.
- Factors Affecting London Dispersion Attractions
Explore the role of size and shape in the strength of London dispersion attractions.
- Global Climate Change Model: Making Predictions About Future Climate
Explore how changing human emissions may affect Earth's temperature in the future.
- How Electrons Move
Discover the forces affecting the movement of electrons, including electric and magnetic fields.
- Hydraulic Fracturing Model
Explore how hydraulic fracturing is used to extract oil and natural gas and how the process may affect local aquifers.
- Hydrogen Bonds: A Special Type of Attraction
Explore the polar molecule interactions known as hydrogen bonds.
- Intermolecular Attractions and States of Matter
Explore how states of matter are related to the strength of intermolecular attractions.
- Introduction to Quantum Mechanics
Discover the quantum nature of electrons including their wave nature, tunneling abilities, and their bound and excited states.
- Land Management Model
Explore the effects of different land management strategies, terrain, and climate on erosion rate and soil quality.
- Metal Forces
Explore what happens when a force is exerted on a metallic material.
- Modeling Transcription
Explore how an mRNA copy is made of DNA.
- Modeling Translation
Explore how a protein is made from an mRNA sequence.
- Molecular View of a Gas
Explore the structure of a gas at the molecular level.
- Molecular View of a Liquid
Explore the structure of a liquid at the molecular level.
- Molecular View of a Solid
Explore the structure of a solid at the molecular level.
Explore how changing the DNA sequence can change the amino acid sequence of a protein.
- Oil and Water
Explore the interactions that cause water and oil to separate from a mixture.
Explore the factors that affect a pendulum's motion.
- Pendulum and Spring
Explore the motion of a pendulum suspended by a spring.
- Phase Change
Explore what happens at the molecular level during a phase change.
- Planet Hunting Model
Explore how a star's movement and light intensity are affected by an orbiting planet. Explore some characteristics of stars and planets that are important to habitability potential.
- Plastic Forces
Explore what happens when a force is exerted on a polymeric plastic material.
- Polarity and Attractive Strength
Explore the role of polarity in the strength of intermolecular attractions.
- Protein Folding
Explore how hydrophobic and hydrophilic interactions cause proteins to fold into specific shapes.
- Quantum Tunneling
Explore the unique concept of quantum tunneling and its importance to modern technology.
- Scanning Tunneling Microscopy
Use a virtual scanning tunneling microscope to explore the quantum tunneling effect.
- Seeing Intermolecular Attractions
Explore different types of attractions between molecules.
- Seismic Explorer
Explore the pattern of earthquakes on Earth, including magnitude, depth, location, and frequency.
Explore the structure and behavior of natural and doped semiconductors.
Explore why excited atoms emit different wavelengths of radiation and learn how to identify atoms based on their unique atomic spectra.
- Spring Model
Explore the factors that affect a spring's motion.
- Sunlight, Infrared, CO2 and the Ground
Explore how solar radiation interacts with Earth’s surface and atmosphere.
- The Temperature-Pressure Relationship
Explore the relationship between the temperature of a gas and the pressure it exerts on its container.
- The Temperature-Volume Relationship
Explore the relationship between the temperature of a gas and its volume.
- The Volume-Pressure Relationship
Investigate the relationship between the volume of a gas and the pressure it exerts on its container.
- Tire Forces
Explore what happens when a force is exerted on a rubber tire.
- Transistors: The Field Effect
The field effect transistor is the most common type of transistor.
- Troubleshooting DC Circuits
Find the faulted resistor in a simulated circuit.
- Water Model
Explore how water moves through Earth’s layers and determine whether wells can produce sustainable amounts of water while maintaining the health of the underlying aquifer.
- What Are Our Energy Choices?
Explore the advantages and disadvantages of using renewable and non-renewable sources to generate electricity.
- What is Pressure?
Explore pressure at the atomic level.
- What Is the Future of Earth's Climate?
Examine climate data and models to predict Earth's future climate.
- Will the Air Be Clean Enough to Breathe?
With more of the world becoming industrialized, will the air be clean enough to breathe?
- Will There Be Enough Fresh Water?
As the human population has grown, water use has increased. Explore water movement and predict water availability.


Will we ever realize the sci-fi dream of human teleportation? Physicists have already successfully teleported tiny objects. (See Beam Me Up, Schrödinger for more on the mechanics of quantum teleportation.) What will it take to extend the technique to a living, breathing human being?
Quantum teleportation is possible because of two quantum phenomena that are utterly foreign to our everyday experience: entanglement and superposition. Entanglement is the connection that links the quantum states of two particles, even when they are separated: The two particles can be described only by their joint properties.
Though there is no classical analogue for entanglement, in his book Dance of the Photons Zeilinger imagined how entanglement might work if it could be applied to a pair of ordinary dice instead of a pair of subatomic particles: “The science fiction Quantum Entanglement Generator produces pairs of entangled dice. These dice do not show any number before they are observed.” In other words, they are in a superposition of states where there is an equal chance of producing any number between one and six. “When one die is observed, it randomly chooses to show a number of dots. Then, the other distant die instantly shows the same number.”
This works no matter how far apart the dice are. They can be sitting beside each other or on opposite ends of the universe. In either case, when the particle over here is measured to be in one of many possible states, then we can infer the state of the particle over there, even though no energy, no mass, and no information travels between A and B when the first one is observed. The state of particle B simply is what it is. The difficult concept is that B’s state corresponds with the state of the measured particle A.
Entanglement is so confounding that in the early days of quantum theory, when entanglement was supported only by thought experiments and math on paper, Einstein famously derided it as “spooky action at a distance.” Today, though, entanglement has been thoroughly tested and verified. In fact, entangling particles isn’t even the hard part: For physicists, the most difficult task is maintaining the entanglement. An unexpected particle from the surrounding environment—something as insubstantial as a photon—can jostle one of the entangled particles, changing its quantum state. These interactions must be carefully controlled or else this fragile connection will be broken.
If entanglement is one gear in the quantum machinery of teleportation, the second critical gear is superposition. Remember the thought experiment about Schrödinger’s cat? A cat, a flask of poison, and a radioactive source are all placed in a sealed box. If the source decays and emits a particle, then the flask breaks and the cat dies. While the box is closed, we can’t know whether the cat is living or dead. Moreover, the cat can be considered both alive and dead until the box is opened: The cat will stay in a superposition of the two states until a “measurement is made—that is, until we look in the box and observe that the cat is either alive or dead.
Schrödinger never tried this on a real cat—in fact, he drew up the thought experiment just to demonstrate the apparently preposterous implications of quantum theory, and to force theorists to examine what constitutes a “measurement”—but today scientists have demonstrated that superposition is real using systems that are increasingly large (albeit still much smaller than a cat). In 2010, a group of researchers at the University of California, Santa Barbara demonstrated superposition in a tiny mechanical resonator—like a tuning fork, it vibrates at a characteristic frequency, but just like the cat it doesn’t exist in a single position until measured. Last year, another group of researchers demonstrated quantum superposition in systems of as many as 430 atoms.
Before superposition and entanglement appear in a human-scale teleporter, if ever, they will be harnessed for multiple applications in computing. Quantum cryptography uses entanglement to encode messages and detect eavesdropping. Because observation perturbs entanglement, eavesdropping destroys information carried by entangled particles. And if two people each receive entangled particles, they can generate an entirely secure key. Quantum cryptography is an active area of research and some systems are already on the market.
Quantum mechanical superposition and entanglement could also be exploited to make faster and more powerful computers that store information in quantum states, known as “qubits,” instead of traditional electronic bits. Quantum computers could solve problems that are intractable for today’s computers. Whether it’s possible to make a working quantum computer is still in question, but roughly two dozen research groups around the world are avidly investigating methods and architectures.
So we know how to teleport one particle. But what if we want to make like Captain Kirk and teleport an entire human being?
Remember that we wouldn’t be moving Kirk’s molecules from one place to another. He would interact with a suite of previously-entangled particles, and when we read the quantum state we would destroy the complex quantum information that makes his molecules into him while instantly providing the information required to recreate his quantum state from other atoms in a distant location.
Quantum mechanics doesn’t forbid it. The rules of quantum mechanics still apply whether you’re talking about a system of two particles or human being made of 1027 atoms. “The size doesn’t matter in and of itself,” says Andrew Cleland, a physicist at the University of California, Santa Barbara. Macroscopic systems like superconductors and Bose-Einstein condensates show quantum effects while arbitrarily large.
From an engineering standpoint, though, teleporting larger objects becomes an increasingly tough problem. Cleland comments, “Taking any object and putting it in a quantum state is hard. Two is multiply hard.” Maintaining entanglement between particle requires isolating them from interactions that would break their entanglement. We don’t want Captain Kirk to end up like The Fly, so we need to keep the particles absolutely isolated.
What if we start with something simpler: Instead of teleporting a person, can we teleport a much smaller living thing—like a virus?
In 2009, Oriol Romero-Isart of the Max-Planck-Institut fur Quantenoptik in Germany and his colleagues proposed just such an experiment. Using current technology, it should be possible to demonstrate superposition in a virus, they argued. They didn’t try it, but laid out a procedure: First, store the virus in a vacuum to reduce interactions with the environment, and then cool it to its quantum ground state before pumping it with enough laser light to create a superposition of two different energy states.
This is possible in theory because some viruses can survive cold and vacuum. But humans are hot, and that thermal energy is a problem. “We have quadrillions of quantum states superimposed at the same time, dynamically changing,” says Cleland. Not only are we hot, but we interact strongly with our environment: We touch the ground, we breathe. Ironically, our need to interact with our environment, our sheer physicality, could come between us and the dream of human teleportation.


Quantum Computing and the Cryptography Conundrum
By leveraging existing networking infrastructure and adding suitable post-quantum key distribution techniques, it is possible to take a “quantum leap” in securing your data.
By: Anand Patil
On October 23, 2019, researchers from Google made an official announcement of a major breakthrough – one that scientists compared to the Wright Brothers’ first flight, or even man’s first moon landing. They said to have achieved Quantum Supremacy, meaning that they had created a Quantum Computer that could perform a calculation that is considered impossible by the classical computers of today. The announcement was a landmark, highlighting the possibilities of Quantum Computing.
The concept of Quantum Computing itself isn’t new. It is a field that has been a point of interest of physicists and computer researchers since the 1980s. Google’s announcement, however, has brought it to the mainstream, and shone a spotlight on the promise that this niche field of innovation holds. Of course, like someone once said, with great power comes with great responsibility, so this field isn’t without complexities.
The Possibilities of Quantum Computing
Quantum Computing is a branch of computer science that is focused on leveraging the principles of quantum physics to develop computer technology. Quantum Computers hold the promise to power major advances in various fields that require complex calculations – from materials science and pharmaceuticals to aerospace and artificial intelligence (AI).
So far, Quantum Computers have been nothing more than fancy laboratory experiments – large and expensive – but they have successfully demonstrated that the underlying principles are sound and have the potential to transform industries and accelerate innovation like never before. This has spurred scientific and industrial interest in this nascent field, giving rise to multiple projects across the world in pursuit of creating a viable, general-use Quantum Computer. That said, it may still be many years before Quantum Computers are commercially and generally available.
So Why Does It Matter Today?
The possibility of Quantum Computers poses a serious challenge to cryptographic algorithms deployed widely today. Today’s key-exchange algorithms, like RSA, Diffie-Hellman, and others, rely on very difficult mathematical problems such as prime factorization for their security, which a Quantum computer would be able to solve much faster than a classical computer.
For example, it would take a classical computer centuries or even longer, to break modern algorithms like DH, RSA-2048 etc. by using brute-force methods. However, given the power and efficiency of quantum machines in calculations such as finding prime factors of large numbers – it may be possible for a quantum computer to break current asymmetric algorithms in a matter of days
So, while the encrypted internet is not at risk at the moment, all that a bad actor has to do is capture the encrypted data today including the initial key exchange, and then wait until a powerful enough quantum computer is available – to decrypt it. This is particularly a problem for organizations that have large amounts of sensitive data that they need to protect over the long term – such as Banks, Governments and Defense agencies.
What Can I Do Now?
For organizations that could be at risk in the future, this is the best time to start evaluating “post-quantum” cryptography. Simply put, this means moving to algorithms and/or keys that are a lot more robust and can withstand a brute-force attack by a quantum computer –i.e. quantum resistant.
The National Institute of Standards and Technology (NIST) in the US is leading the effort towards the standardization of post-quantum secure algorithms. However, given the lengthy process involved, this may take many years to fructify.
An alternative is to use “Quantum Key Distribution” (QKD) techniques with existing algorithms that are considered quantum-safe. This involves using a dedicated optical channel to exchange keys using the quantum properties of photons. Any attempt to “tap” this secure channel will lead to a change in the quantum state of the photon and can be immediately detected – and therefore the key is unhackable. One of the limitations of QKD in this method is the need for a dedicated optical channel that cannot span more than 50km between the two terminals. Of course, this also means that the existing encryption devices or routers should be capable of ingesting such “Quantum-Generated” keys.
Post-Quantum Cryptography and Cisco
Cisco is an active contributor to the efforts to standardize post-quantum algorithms. However, recognizing that an implementable standard may be some years away, there is work ongoing to ensure that organizations are able to implement quantum-resistant encryption techniques in the interim, that leverage existing network devices like routers – which are most commonly used as encryptors.
To start with, a team of veteran technical leaders and cryptography experts from Cisco US – David McGrew, Scott Fluhrer, Lionel Florit and the engineering team in Cisco India lead by Amjad Inamdar and Ramas Rangaswamy developed an API interface called the “Secure Key Import Protocol” – or SKIP – through which Cisco routers can securely ingest keys from an external post-quantum key source. This allows existing Cisco routers to be quantum-ready, with just the addition of an external QKD system. Going forward, this team is working on a way to deliver quantum-safe encryption keys without the need for short-range point-to-point connections.
The advantage of this method is that organizations can integrate post-quantum key sources with existing networking gear in a modular fashion – without the need to replace anything already installed. In this manner, you could create a quantum-ready network for all traffic with minimal effort.
Getting Ready for the Post-Quantum World
Quantum Supremacy is an event which demonstrates that a quantum machine is able to solve a problem that no classical computer can solve in a feasible amount of time. This race has gathered momentum in the recent past with several companies joining the bandwagon, and some even claiming to have achieved it.
There is an unprecedented amount of attention focused on making a commercially viable quantum computer. Many believe it is inevitable, and only a question of time. When it does happen, the currently used cryptography techniques will become vulnerable, and therefore be limited in their security. The good news is, there are methods available to adopt strong encryption techniques that will remain secure even after quantum computers are generally available.
If you are an organization that wants to protect its sensitive data over the long term, you should start to evaluate post-quantum secure encryption techniques today. By leveraging existing networking infrastructure and adding suitable post-quantum key distribution techniques, it is possible to take a “quantum leap” in securing your data.
(The author is Director, Systems Engineering, Cisco India and SAARC and the views expressed in this article are his own)


The story so far: The allure of quantum computers (QC) is their ability to take advantage of quantum physics to solve problems too complex for computers that use classical physics. The 2022 Nobel Prize for physics was awarded for work that rigorously tested one such ‘experience’ and paved the way for its applications in computing – which speaks to the contemporary importance of QCs. Several institutes, companies and governments have invested in developing quantum-computing systems, from software to solve various problems to the electromagnetic and materials science that goes into expanding their hardware capabilities. In 2021 alone, the Indian government launched a National Mission to study quantum technologies with an allocation of ₹8,000 crore; the army opened a quantum research facility in Madhya Pradesh; and the Department of Science and Technology co-launched another facility in Pune. Given the wide range of applications, understanding what QCs really are is crucial to sidestep the misinformation surrounding it and develop expectations that are closer to reality.
How does a computer use physics?
A macroscopic object – like a ball, a chair or a person – can be at only one location at a time; this location can be predicted accurately; and the object’s effects on its surroundings can’t be transmitted faster than at the speed of light. This is the classical ‘experience’ of reality.
For example, you can observe a ball flying through the air and plot its trajectory according to Newton’s laws. You can predict exactly where the ball will be at a given time. If the ball strikes the ground, you will see it doing so in the time it takes light to travel through the atmosphere to you.
Quantum physics describes reality at the subatomic scale, where the objects are particles like electrons. In this realm, you can’t pinpoint the location of an electron. You can only know that it will be present in a given volume of space, with a probability attached to each point in the volume – like 10% at point A and 5% at point B. When you probe this volume in a stronger way, you might find the electron at point B. If you repeatedly probe this volume, you will find the electron at point B 5% of the time.
There are many interpretations of the laws of quantum physics. One is the ‘Copenhagen interpretation’, which Erwin Schrödinger popularised using a thought-experiment he devised in 1935. There is a cat in a closed box with a bowl of poison. There is no way to know whether the cat is alive or dead without opening the box. In this time, the cat is said to exist in a superposition of two states: alive and dead. When you open the box, you force the superposition to collapse to a single state. The state to which it collapses depends on the probability of each state.
Similarly, when you probe the volume, you force the superposition of the electrons’ states to collapse to one depending on the probability of each state. (Note: This is a simplistic example to illustrate a concept.)
The other ‘experience’ relevant to quantum-computing is entanglement. When two particles are entangled and then separated by an arbitrary distance (even more than 1,000 km), making an observation on one particle, and thus causing its superposition to collapse, will instantaneously cause the superposition of the other particle to collapse as well. This phenomenon seems to violate the notion that the speed of light is the universe’s ultimate speed limit. That is, the second particle’s superposition will collapse to a single state in less than three hundredths of a second, which is the time light takes to travel 1,000 km. (Note: The ‘many worlds’ interpretation has been gaining favour over the Copenhagen interpretation. Here, there is no ‘collapse’, automatically removing some of these puzzling problems.)
How would a computer use superposition?
The bit is the fundamental unit of a classical computer. Its value is 1 if a corresponding transistor is on and 0 if the transistor is off. The transistor can be in one of two states at a time – on or off – so a bit can have one of two values at a time, 0 or 1.
The qubit is the fundamental unit of a QC. It’s typically a particle like an electron. (Google and IBM have been known to use transmons, where pairs of bound electrons oscillate between two superconductors to designate the two states.) Some information is directly encoded on the qubit: if the spin of an electron is pointing up, it means 1; when the spin is pointing down, it means 0.
But instead of being either 1 or 0, the information is encoded in a superposition: say, 45% 0 plus 55% 1. This is entirely unlike the two separate states of 0 and 1 and is a third kind of state.
The qubits are entangled to ensure they work together. If one qubit is probed to reveal its state, so will some of or all the other qubits, depending on the calculation being performed. The computer’s final output is the state to which all the qubits have collapsed.
One qubit can encode two states. Five qubits can encode 32 states. A computer with N qubits can encode 2N states – whereas a computer with N transistors can only encode 2 × N states. So a qubit-based computer can access more states than a transistor-based computer, and thus access more computational pathways and solutions to more complex problems.
How come we’re not using them?
Researchers have figured out the basics and used QCs to model the binding energy of hydrogen bonds and simulate a wormhole model. But to solve most practical problems, like finding the shape of an undiscovered drug, autonomously exploring space or factoring large numbers, they face some fractious challenges.
A practical QC needs at least 1,000 qubits. The current biggest quantum processor has 433 qubits. There are no theoretical limits on larger processors; the barrier is engineering-related.
Qubits exist in superposition in specific conditions, including very low temperature (~0.01 K), with radiation-shielding and protection against physical shock. Tap your finger on the table and the states of the qubit sitting on it could collapse. Material or electromagnetic defects in the circuitry between qubits could also ‘corrupt’ their states and bias the eventual result. Researchers are yet to build QCs that completely eliminate these disturbances in systems with a few dozen qubits.
Error-correction is also tricky. The no-cloning theorem states that it’s impossible to perfectly clone the states of a qubit, which means engineers can’t create a copy of a qubit’s states in a classical system to sidestep the problem. One way out is to entangle each qubit with a group of physical qubits that correct errors. A physical qubit is a system that mimics a qubit. But reliable error-correction requires each qubit to be attached to thousands of physical qubits.
Researchers are also yet to build QCs that don’t amplify errors when more qubits are added. This challenge is related to a fundamental problem: unless the rate of errors is kept under a certain threshold, more qubits will only increase the informational noise.
Practical QCs will require at least lakhs of qubits, operating with superconducting circuits that we’re yet to build – apart from other components like the firmware, circuit optimisation, compilers and algorithms that make use of quantum-physics possibilities. Quantum supremacy itself – a QC doing something a classical computer can’t – is thus at least decades away.
The billions being invested in this technology today are based on speculative profits, while companies that promise developers access to quantum circuits on the cloud often offer physical qubits with noticeable error rates.
The interested reader can build and simulate rudimentary quantum circuits using IBM’s ‘Quantum Composer’ in the browser.


Silicon is a material widely used in computing: It is used in computer chips, circuits, displays and other modern computing devices. Silicon is also used as the substrate, or the foundation of quantum computing chips.
Researchers at the Superconducting Quantum Materials and Systems Center, hosted by the U.S. Department of Energy’s Fermi National Accelerator Laboratory, demonstrated that silicon substrates could be detrimental to the performance of quantum processors. SQMS Center scientists have measured silicon’s effect on the lifespan of qubits with parts-per-billion precision. These findings have been published in Physical Review Applied.
New approaches to computing
Calculations once performed on pen and paper have since been handed to computers. Classical computers rely on bits, 1 or 0, which have limitations. Quantum computers offer a new approach to computing that relies on quantum mechanics. These novel devices could perform calculations that would take years or be practically impossible for a classical computer to perform.
Using the power of quantum mechanics, qubits—the basic unit of quantum information held within a quantum computing chip—can be both a 1 and a 0 at the same time. Processing and storing information in qubits is challenging and requires a well-controlled environment. Small environmental disturbances or flaws in the qubit’s materials can destroy the information.
Qubits require near-perfect conditions to maintain the integrity of their quantum state, and certain material properties can decrease the qubit lifespan. This phenomenon, called quantum decoherence, is a critical obstacle to overcome to operate quantum processors.
Disentangling the architecture
The first step to reduce or eliminate quantum decoherence is to understand its root causes. SQMS Center scientists are studying a broadly used type of qubit called the transmon qubit. It is made of several layers of different materials with unique properties. Each layer, and each interface between these layers, play an important role in contributing to quantum decoherence. They create “traps” where microwave photons—key in storing and processing quantum information—can be absorbed and disappear.
Researchers cannot unequivocally distinguish where the traps are located or which of the various materials or interfaces are driving decoherence based on the measurement of the qubit alone. Scientists at the SQMS Center use uniquely sensitive tools to study these effects from the materials that make up the transmon qubits.
“We are disentangling the system to see how individual sub-components contribute to the decoherence of the qubits,” said Alexander Romanenko, Fermilab’s chief technology officer, head of the Applied Physics and Superconducting Technology Division and SQMS Center quantum technology thrust leader. “A few years ago, we realized that our [superconducting radio frequency] cavities could be tools to assess microwave losses of these materials with a preciseness of parts-per-billion and above.”
Measurements at cold temperatures
SQMS Center researchers have directly measured the loss tangent—a material’s ability to absorb electromagnetic energy—of high-resistivity silicon. These measurements were performed at temperatures only hundreds of a degree above absolute zero. These cold temperatures offer the right conditions for superconducting transmon qubits to operate.
“The main motivation for why we did this experiment was that there were no direct measurements on this loss tangent at such low temperatures,” said Mattia Checchin, SQMS Center scientist and the lead researcher on this project.
No material is perfect. Through rigorous testing and studies, researchers are building a more comprehensive understanding of the materials and properties best suited for quantum computing.
Checchin cooled a metallic niobium SRF cavity in a dilution refrigerator and filled it with a standing electromagnetic wave. After placing a sample of silicon inside the cavity, Checchin compared the time the wave dissipated without the silicon present to the time with it present. He found that the waves dissipated more than 100 times faster with the silicon present—from 100 milliseconds without silicon to less than a millisecond with it.
“The silicon dissipation we measured was an order of magnitude worse than the number widely reported in the [quantum information science] field,” said Anna Grassellino, director of the SQMS Center. “Our approach of disentangling the problem by studying each qubit sub-component with uniquely sensitive tools has shown that the contribution of the silicon substrate to decoherence of the transmon qubit is substantial.”
Companies developing quantum computers based on quantum computing chips often use silicon as a substrate. SQMS Center studies highlight the importance of understanding which of silicon’s properties have negative effects. This research also helps define specifications for silicon that would ensure that substrates are useful. Another option is to substitute the silicon with sapphire or another less lossy material.
“Sapphire, in principle, is like a perfect insulator—so much better than silicon,” said Checchin. “Even sapphire has some losses at really low temperatures. In general, you would like to have a substrate that is lossless.”
Researchers often use the same techniques for fabricating silicon-based microelectronic devices to place qubits on silicon substrate. So sapphire has rarely been used for quantum computing.
“It has taken years of material science and device physics studies to develop the niobium material specifications that would ensure consistently high-performances in SRF cavities,” said Romanenko. “Similar studies need to be done for materials that comprise superconducting qubits. This effort includes researchers working together with the material industry vendors.”
Regardless of which material is used for qubits, eliminating losses and increasing coherence time is crucial to the success of quantum computing. No material is perfect. Through rigorous testing and studies, researchers are building a more comprehensive understanding of the materials and properties best suited for quantum computing.
This loss tangent measurement is a substantial step forward in the search for the best materials for quantum computing. SQMS Center scientists have isolated a problem and can now explore whether a more refined version of silicon or sapphire will harness the computational power of a qubit.
The Superconducting Quantum Materials and Systems Center is one of the five U.S. Department of Energy National Quantum Information Science Research Centers. Led by Fermi National Accelerator Laboratory, SQMS is a collaboration of 23 partner institutions—national labs, academia and industry—working together to bring transformational advances in the field of quantum information science. The center leverages Fermilab’s expertise in building complex particle accelerators to engineer multiqubit quantum processor platforms based on state-of-the-art qubits and superconducting technologies. Working hand in hand with embedded industry partners, SQMS will build a quantum computer and new quantum sensors at Fermilab, which will open unprecedented computational opportunities. For more information, please visit sqms.fnal.gov.
Fermi National Accelerator Laboratory is supported by the Office of Science of the U.S. Department of Energy. The Office of Science is the single largest supporter of basic research in the physical sciences in the United States and is working to address some of the most pressing challenges of our time. For more information, please visit science.energy.gov.


The world of technology is fast. We see innovations happening every single day and trying to keep up with all of the new buzzwords is far from easy. Our aim simplifies learning some of the latest or maybe most confusing technology. This is the second installment in Frequently Asked Questions in Technology. If you want to see the ideas or concepts, we discussed in the first part, check it out here: Frequently Asked Questions in Technology (Part 1). This month we will be discussing net neutrality, big data, quantum computing, and more.
Net neutrality is the idea and principle that Internet Service Providers treat all content and all data the same. It’s the concept that all Internet Service Providers should charge the same prices for all users, all content, and all websites. Old net-neutrality laws didn’t let ISPs play favorites. They weren’t allowed to slow down certain websites that didn’t align with their beliefs or charge more for sites that used more data. In 2018, the Federal Communications Commission, which handles the law, voted to repeal net neutrality.
Net neutrality lasted from 2015 until 2018. And while we may not see the repercussions of not having net neutrality in a blatant form. It’s important to understand this concept. This continues to be argued over in court and in within politics. Net neutrality supports the concept of free speech. It believes in uncensored voices. Certain states are looking to reintroduce some form of net neutrality in 2021.
The latest buzzword or buzz phrase in technology is quantum computing. Before we get into what quantum computing is, we should first define what quantum mechanics is. Quantum mechanics is also referred to as quantum physics or quantum theory. It explains how the particles that make up atoms work.
Quantum computing employs the ideas of quantum mechanics to enhance the processing power of computers. Using quantum computing can help data analysts solve computational problems faster. For some equations, quantum computing can be more beneficial than even supercomputers. Quantum computers use the properties of quantum physics to store and compute data. A quantum computer also uses different units of memory called a quibit (short for a quantum bit). These computers calculate based on the probability of an object’s state before it’s measured instead of using 1s and 0s. This means it can theoretically process more data than traditional supercomputers. While still in their early stages, quantum computers are all the buzz and could potentially be the future of computational power.
The term big data is used to describe extremely large amounts of data collected by businesses, companies, and institutions. But the amount of data isn’t what is important to these entities. It is the analysis and the insights that come from the data collected which help improve an organization’s business.
There are several different examples of big data that we can see from the real world. The first is figuring out a consumer’s shopping habits. This can help strategists understand how to market to a regular customer and also how to market to potential consumers
Streaming services are also using big data as a way to predict what shows could be profitable or even the next big hit. The data they find from how their subscribers stream shows help them make the decisions. If you’re a Netflix subscriber, you will receive a curated list of recommended movies that will very different than the next subscriber. They are taking into account your viewing preferences and history and uses this data to inform them of what to market to you.
Big data is also used in TV advertisements, social media marketing, navigation applications, and more. The analysis of data helps companies predict what could be the next big thing. It informs them of the next steps for their business. If your business looking to store its data in a trusted data center, connect with us today.
Virtual Reality and Augmented Reality have been around for quite some time now, but the two different technologies are still confusing. The main thing to remember when it comes to VR and AR is the way it alters your vision. VR is a computer simulation that makes users feel like they are somewhere else. Today, virtual reality is used in video games and 3D movies. Augmented reality on the other hand combines the real world you are currently and adds virtual elements. Using a phone or a tablet, these computer augmentations are projected as a layer on top of your real-world setting.
Some examples of AR include Google Sky Map, Layar, and PokemonGO. It’s also to help users find what’s in and around them when they are visiting a new city. Some examples of VR include the Oculus Quest and the PlayStation VR. The resurgence of these two industries could be an indicator of where technology is headed. The virtual reality and augmented reality markets reached over 18.8 billion dollars in the US in 2020.
Machine learning is an integral part of Artificial Intelligence, which is a simulation of human intelligence processed by computer systems and machines. These machines are programmed to think like humans and simulate our actions.
Machine learning is an application within Artificial Intelligence that gives the system the capability of automatically learning and improving what it’s doing without that specific aspect being programmed. Machine learning technology is currently being applied to personal assistants like Google Home and Amazon Alexa. It’s also being used by various applications to help improve marketing and performance.
As mentioned earlier, streaming services are using data to push certain content to their users. Streaming service recommendation engines are an example of machine learning that we may see more frequently. As the world gets closer to smart cities and self-driving cars, artificial intelligence and machine learning will continue to play a vital role in these innovations.
The most exciting aspect of technology is the number of new ideas being applied every single day. And even before these ideas make it into mainstream consumption, these concepts can be quite intriguing. Keeping up with all of this information can be difficult. If you have any buzzwords, topics, or concepts that you want to know more about, leave us a message and we’ll include it in the next installment of Frequently Asked Questions in Technology.


Phonons radiated by artificial atoms
Science news with bad titles usually attract a lot of attention. A recent example is “The sound of an atom has been captured” 1]. Laypeople must know that atoms do not emit sound. Quantum acoustics study the propagation and the interaction of phonons, the analogues in sound to photons in light. An atom cannot emit phonons, but an artificial atom (a quantum dot or a superconducting qubit) can. Martin V. Gustafsson (Chalmers University of Technology, Göteborg, Sweden) and colleagues 2 have studied the free propagation of quantum information by phonons (specifically surface acoustic waves) strongly coupled to a superconducting qubit. In their experiments, phonons have a role similar to that of photons in quantum optics. A beautiful result in quantum acoustics that deserves our attention.
Surface Acoustic Waves (SAWs), also referred to as Rayleigh waves, where theoretically predicted in 1885 by Lord Rayleigh 3. He showed that an elastic medium can support surface vibration modes that are wavelike. They are surface waves because their amplitudes decay exponentially with increasing distance into the solid from the surface and their energy is peaked within a depth of approximately one wavelength 4. By using piezoelectric materials the electric energy in electronic circuits can be transduced to mechanical energy in the form of SAWs. The so-called InterDigital Transducers (IDTs) are capable of converting acoustic waves to electrical signals and vice versa. Today, SAW devices are extensively used in commercial mobile phones instead of the traditional quartz crystals (based on bulk waves) because they can operate at higher frequency.
From the quantum point of view, SAWs are made of phonons so they can be coupled to an artificial atom (a qubit) via piezoelectricity (see Fig. 1 for a circuit model). Thanks to SAWs a bidirectional communication with the qubit can be achieved. The great advantage is the low speed of sound, which allows the observation of the emission of phonons from the qubit in the time domain, i.e., to listen the sound of the artificial atom.
Gustafsson and colleagues  use an IDT with a GaAs substrate as piezoelectric material and two electrodes made of aluminium capped with palladium (see Fig. 2, left micrographs). The resulting SAWs propagate in the crystal at a speed of about 2900 m/s with a narrow bandwidth of ~1 MHz around an IDT carrier frequency of 4.8066 GHz. The IDT can both launch a SAW beam toward the artificial atom and pick up leftward-propagating SAW phonons produced by it. The device operates at a low temperature of about 20 mK to avoid the influence of spurious thermal phonons from the environment.
The artificial atom (see Fig. 2, right micrographs) is a superconducting qubit of the transmon type. A transmon consists of a Superconducting Quantum Interference Device (SQUID) shunted by a large geometric capacitance so the Josephson inductance forms a resonant circuit. This nonlinear inductance gives rise to the anharmonic energy spectrum characteristic for an (artificial) atom, i.e., a set of discrete energy levels. The transmon is well suited for coupling to SAWs since the shunt capacitance (about 85 fF in Ref. ) can be designed to strongly couple to the IDT thanks to their common finger structure (see Fig. 2 and compare left and right micrographs). The transitions between the energy levels of the qubit results in the emission of SAW phonons and, conversely, a SAW beam can excite energy level transitions in the artificial atom.
A careful reader may wonder how the authors have verified that the quantum information between the qubit and the IDT is propagated by phonons instead of photons (in fact, the IDT is controlled by using microwave pulses). To solve this question, Gustafsson and colleagues  take advantage of the slow propagation of SAWs. After the excitation of the qubit to a high-energy level, its state decays emitting a signal than can be read by the IDT. Figure 3 illustrates that this signal takes about 40 ns to travel the distance of about 0.1 mm separating the IDT and the qubit (i.e., the speed of the signal is about 2500 m/s). Hence the signal is phononic. Another check developed by the authors is a careful comparison between the measurement of the signal, by using two-tone spectroscopy, and the numerical predictions of a theoretical model of the system.
From the point of view of future applications, SAW phonons have several striking features with respect to photons. Their slow speed of propagation allows that the qubits be tuned much faster than SAWs traverse inter-qubit distances on a chip; this property enables new dynamic schemes for processing quanta. Additionally, the SAW phonons wavelength at a given frequency is shorter than the size of the qubit (since it depends on sound speed instead of light speed), so new techniques for trapping quanta into cavities can be developed. In my opinion, the future for this technology in quantum information processing is bright.
In summary, the propagation of quantum information using quantum acoustics has been demonstrated by using SAW phonons. This achievement provides new tools for quantum information processing in regimes difficult (or even impossible) to reach using photons.
- “The sound of an atom has been captured” Phys.Org, Sep 11, 2014. ↩
- Gustafsson M.V., A. F. Kockum, M. K. Ekstrom, G. Johansson & P. Delsing (2014). Propagating phonons coupled to an artificial atom, Science, DOI: http://dx.doi.org/10.1126/science.1257219 ↩
- Lord Rayleigh, “On Waves Propagated along the Plane Surface of an Elastic Solid,” Proc. London Math. Soc. 4–11 (1885). DOI: 10.1112/plms/s1-17.1.4 ↩
- A. A. Maradudin, G. I. Stegeman, “Surface Acoustic Waves,” in Surface Phonons, edited by W. Kress, F. W. de Wette, Springer, 1991, pp 5–35. DOI: 10.1007/978-3-642-75785-3_2 ↩
[…] el tema, puedes leer mi post (en inglés) “Phonons radiated by artificial atoms,” Mapping Ignorance, 22 Sep 2014. El artículo técnico descrito es M. V. Gustafsson, A. F. Kockum, M. K. Ekstrom, G. […]
I’m confused because I always thought that the definition of a qubit cannot be associated to a physical thing. What really means an “artificial atom”?
Superconducting circuits are really artificial atoms because their resonance frequencies resembles those in atoms.
[…] Atomo baten soinua entzun dela iragartzen zuen berriak izan duen oihartzunaren aurrean, Francisco R. Villatoro atomo artifizial bat zer den azaltzera etorri zaigu. Eta, entzundako doinu hori fonoiez osatuta dagoela: Phonons radiated by artificial atoms. […]
[…] Ante la noticia que tuvo bastante eco de que se había escuchado el sonido de un átomo, Francisco R. Villatoro sale al paso y explica qué es realmente un átomo artificial y que ese sonido está constituido realmente por […]


The State of Quantum
The superiority of any computing technology zeroes down to its processing capabilities, and over the years the classical computer chip’s processing power has been pushed to limits by shrinking its components, in order to reduce the distance travelled by electric signals in between.
The famous Moore’s Law (by Gordon Moore) states “the number of transistors on a microchip double about every two years, though the cost of computers is halved”, helping us draw context on why billions of dollars are being invested into making these chips smaller and smaller. Apple’s 5-nanometre processor is a good example of where we are, but we’re seemingly hitting a wall in terms of marginal increases in processing power for every additional billion dollars invested. Furthermore, these classical computers require longer periods to solve complex problems and sometimes this can even go up to 10,000 years.
While we’re progressing towards smaller circuits and complex problems, we’ve reached the physical limits of materials and the threshold for classical laws of physics to apply, hence chip designers are going subatomic to solve this. The use of quantum physics in computing has shown some progress in terms of achieving better processing capabilities over supercomputers.
What exactly is quantum computing?
A quantum computer (QC) uses qubits (the fundamental unit of a QC) to store and process information. Unlike the classical bit which is either 0 or 1 at a time, a qubit can be both 0 and 1 at the same time (explained under ‘Superposition’) — a property which enables a QC to solve problems faster by evaluating solutions simultaneously. Fundamentally a QC derives its power from these 3 main principles of quantum particles:
- Superposition: The qubit’s ability to be 1 & 0 at the same time, i.e. in the state of probabilities (’x%’ probability of being 1 and ‘y%’ probability of being 0).
- Interference: The qubit can cross its own trajectory and interfere with the direction of its path.
- Entanglement: Two qubits are entangled if changing the state of 1 qubit instantaneously changes the state of the other in a predictable way, despite the amount of distance between them.
The number of computations a QC could make is 2^n, where ’n’ denotes the number of qubits used. Hence, with each additional qubit, a QC would attain an exponential increase in processing power, which would be much faster than what Moore’s law stated about doubling transistors. We must also bear in mind that QCs won’t replace our current classical computers (eg: PC, smartphones, etc.), rather they’d complement them in a particular area or application.
What does a quantum computer look like?
This is the IBM System One with a 127-qubit processor. To ensure longer coherence times (period of qubits being in a quantum state) and increase the accuracy of calculations (by reducing noise), QCs are equipped with superconductors made from elements such as Niobium and kept at 1/100th of a degree Celsius i.e., just above absolute zero, using super-fluids like liquid Helium.
Where can quantum computers add value?
With early use cases like optimization, simulation and encryption, QCs are capable of saving billions of dollars and years in time across industries, and these include:
- Process optimization: QC can help with supply chain optimization and manufacturing process optimization, thereby cutting down costs and establishing an efficient way. Volkswagen is using QC to optimize its manufacturing process, and Daimler is working towards making better automotive batteries.
- Drug simulation: QC can enable a significant reduction in R&D costs and time to market for a new drug. Riverlane & Astex Pharmaceuticals are working with Rigetti Computing to develop an integrated application for simulating molecular systems to enable drug discovery.
- Cryptography: A powerful enough quantum computer can break the most secure encryption ever created in a matter of seconds, thus emphasizing the need for post-quantum encryption to secure future use-cases. QuintessenceLabs, an Australian company, has been working on Quantum Random Number Generator (QRNG) & Quantum Key Distribution (QKD) technologies — the foundation for quantum encryption and data security.
- Other interesting use cases: IBM is working on improving weather forecasting, JP Morgan is exploring applications in financial modelling & options pricing, and Rigetti is improving machine learning.
Who’s who in quantum computing:
Source: Silicon Foundry
Various companies have been working towards achieving better QC performance and use cases. Essentially, the ecosystem is comprised of the following sub-verticals:
- Quantum hardware: Most challenging sub-vertical that requires millions of dollars in investments for building out the QC, with efforts from talented experts.
- Quantum software: Building software solutions for horizontal (or) industry-specific applications like molecular simulation, error correction, algorithm testing, etc.
- Quantum systems & firmware: Solving for hardware error and qubit instability arising from environmental disturbances and imperfect devices.
- Quantum encryption & AI: Working on technologies like QRNG & QKD to develop quantum-based encryption chips (or) software.
- Cloud computing: Providing direct access to emulators, simulators and quantum processors. Mostly offered by hardware players like IBM, Google, etc.
- Full-stack: These are companies that offer end-to-end quantum computing solutions. They already have a built QCs in house and provide access to it via the cloud.
Research shows that ~35% of QC revenues will be captured by QC software players and 26% by hardware players.
Geographically the U.S.A. has seen the most success in quantum computing, but the Chinese are also catching up. In October 2021, researchers from the University of Science and Technology of China (USTC), said one of the quantum computing systems, Zuchongzhi 2.1, is 100x more powerful than Google’s 53-qubit Sycamore.
The Govt. of India has shown its conviction through its National Mission on Quantum Technologies & Applications mission (NM-QTA) with an INR 8,000 Cr budget (to be deployed over a 5-year period). Top Indian universities including IIT Madras, IISc Bangalore, TIFR, and IISER Pune have been spearheading QC research. Other institutions like MeitY, ISRO, and the Indian Army have also taken initiatives in this space.
Quantum Computing is still years away from actual commercialization since we’re still in the Noisy Intermediate-Scale Quantum (NISQ) era. The creation of a 10,000 qubit QC and enough error correction would end the ‘NISQ era’ and mark the beginning of the ‘Universal Quantum’ era wherein QCs would be capable of breaking the RSA encryption (the bedrock of the internet’s encryption). Hence, overcoming challenges like error correction (by reducing noise), de-coherence (increase time period of a qubit’s quantum state), and output observance (reducing risk of data corruption while retrieving output) will help us transition towards the ‘Universal Quantum’ era.
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