Diamond memory, drinkable seawater and energy through the air. This week’s coolest things make the most of the elements.
What is it? Scientists in Japan made a 2-inch-diameter diamond wafer that could store 25 million terabytes of quantum data, theoretically enough to record a billion Blu-ray discs.
Why does it matter? Diamond could be a very useful material for quantum computing and memory storage. But so far, researchers have been able to produce only 4-millimeter wafers of the necessary purity, while industrial uses require wafers of at least 2 inches — 14 times larger.
How does it work? Although diamond is a form of carbon, its ability to store information comes from nitrogen, a common impurity. In particular, scientists take advantage of a defect called nitrogen-vacancy center, where a nitrogen atom sits next to an empty space in the crystal lattice. A little nitrogen goes a long way, and too much is problematic. It’s a difficult balance to strike, and researchers have failed to make industrial-size wafers without an excess of nitrogen. The scientists, from Saga University and Adamant Namiki Precision Jewel Co., devised a new method for creating the diamond wafers by growing crystals on a stepped substrate surface instead of a flat one. That reduced strain on the material, resulting in improved quality and limiting nitrogen contamination to a minuscule 3 parts per billion. “This new technology is expected to propel the advancement of quantum applications,” Adamant Namiki said in a statement. The company plans to commercialize the product in 2023.
Top and above: Engineers were able to send microwave power more than 1 kilometer to a dish antenna. Scaled up, this technology could enable energy to be delivered from space to troops on the ground. Image and video credits: Naval Research Laboratory.
What is it? Scientists from the Naval Research Laboratory wirelessly beamed 1.6 kilowatts (kW) of electrical energy across more than 1 kilometer (km).
Why does it matter? The Pentagon tasked NRL researchers with demonstrating the delivery of 1 kW of power at a distance of 1 km, explained principal investigator Chris Rodenbeck. The test showed the possibility of sending electricity power to remote locations, such as on-the-ground military operations. In the long run, the technology could be used to deliver energy from space to Earth.
How does it work? Engineers generated electricity, converted it to a 10-gigahertz microwave beam, and sent it through a dish antenna aimed at a receiver more than a kilometer away. The receiver consisted of a highway-sign-size array of tens of thousands of antennas working in what’s known as the X-band frequency (commonly used for police speed radar guns). Diodes converted the microwave power into DC power.
What is it? Researchers from Virginia Tech and the U.S. Department of Energy homed in on an unappreciated factor in what causes batteries to decay.
Why does it matter? Rechargeable batteries degrade over time. The research team discovered that it’s not just the properties of the electrode particles that cause decay, but also the interactions between them. “If you want to build a better battery, you need to look at how to put the particles together,” said Yijin Liu, a senior author of a paper in Science.
How does it work? The researchers used X-ray tomography to create 3D images of battery cathodes at different ages. They identified more than 2,000 particles and described their size, shape and surface roughness, as well as how often they came into contact with one another. They found that after 10 charging cycles, traits such as surface-to-volume ratio and roundness of particles contributed most to their decay. But after 50 charging cycles, breakdown was driven primarily by interactions between particles, including how far apart they were, how varied their shapes and whether they were oriented similarly. Manufacturers could account for these particle-particle interactions to design longer-lasting batteries.
What is it? Tufts University neuroscientists discovered a previously unknown ability of astrocytes, which make up nearly half of all brain cells.
Why does it matter? Scientists knew that astrocytes were important in helping neurons grow and transmit signals in the brain. The research could open ways to attack ailments like epilepsy and Alzheimer’s.
How does it work? The team programmed mice with genetically encoded voltage indicators that allowed them to visualize electrical activity with light. The study showed for the first time that astrocytes are electrically active, like neurons, and that the two cell types affect each other’s activity. “Neurons and astrocytes talk with each other in a way that has not been known about before,” said Chris Dulla, an author on a paper in Nature Neuroscience. Because there is so much that is not known about how the brain works, he added, discovering new fundamental processes that control brain function is key to developing novel treatments for neurological diseases.
This portable unit, which weighs less than 22 pounds and does not require the use of filters, can be powered by a small, portable solar panel. Image credit: Video credit: MIT.
What is it? MIT researchers developed a portable, filter-free desalination system the size of a small suitcase.
Why does it matter? Portable devices for purifying water typically require a steady supply of energy to pump water through filters that need to be periodically replaced. At a mere 20 pounds, the new system, described in Environmental Science and Technology, eliminates filters and needs only as much energy as a phone charger.
How does it work? The device uses a low-power pump to run water between two charged membranes that attract or repel particles such as salt ions, bacteria and viruses. Then it uses electrodialysis to remove any remaining salt. “It was successful even in its first run, which was quite exciting and surprising. But I think the main reason we were successful is the accumulation of all these little advances that we made along the way,” said senior author Jongyoon Han.


(April 3, 2019) -- Building on the Air Force’s need to develop tech devices that require minimal charging in the field, the University of Texas at San Antonio (UTSA) is using principles in quantum science and engineering to build a graphene-based logic device. This new technology will improve the energy efficiency of battery-dependent devices from cell phones to computers.
“We are developing devices that can operate almost battery-less,” said Ethan Ahn, UTSA assistant professor in electrical engineering.
UTSA engineers are using spintronics, the study of an electron’s intrinsic quantum mechanical property called spin, to allow low-power operation with a possible application in quantum computing.
“An electron is a little, but very strong magnet,” said Ahn. “Just imagine that an electron spins on its own axis, either up or down.”
Traditional tech devices use the electronic charge of electrons for power. In spintronics, researchers are tapping the inherent spin of electrons as a new power source. With this new approach, devices will require fewer electrons to operate.
There are hurdles, however, in harnessing the power of spin. In quantum computing that harnesses spin of electrons to transmit information, the challenge for researchers is how to capture spin as efficiently as possible.
“If you have 100 electrons injected to the channel to power the next logic circuit, you may only get to use one or two spins because the injection efficiency is very low. This is 98 percent spin lost,” said Ahn.
To prevent the loss of spin, Ahn has developed the new idea of the “zero-power carbon interconnect” by using nanomaterials as both the spin transport channel and the tunnel barrier. These nanomaterials are like a sheet of paper, a two-dimensional layer of carbon atoms just a few nanometers in thickness, and it’s the point of contact where spin injection is inputted into the device. Ahn’s prototype is an interconnect built with a reduced graphene oxide layer.
“It’s novel because we are using graphene, a nanomaterial, to enhance spin injection. By controlling the amount of oxide on the graphene layers, we can fine tune electrons’ conductivity,” said Ahn.
Graphene has widespread appeal because it’s the world's strongest nanomaterial. In fact, the room temperature conductivity of graphene is higher than that of any other known material.
If successful, the zero-power carbon interconnect that Ahn is creating with his collaborators at UT-Austin and Michigan State University would be integrated into the logic component of a computer chip.
The device, once developed, will be submitted to the U.S. Air Force Office of Scientific Research, which is supporting UTSA’s work with a three-year grant.
“The military needs smaller devices that can operate in remote fields without need to recharge batteries,” said Ahn. “If our zero-power carbon interconnect is successful, it will improve the efficiency of graphene spintronics — a crucial step in advancing the next generation of low-power electronics like quantum computing.”
This interconnect could also be highly beneficial to the cloud computing industry. According to the Data Knowledge Center, on-demand cloud computing platforms such as Amazon Web Services alone consume about two percent of the nation’s energy. If the zero-power carbon interconnect is successful, cloud servers such as those that offer streaming services like Netflix or host data, could operate faster and with less electricity.
Learn more about the UTSA Nano Lab.
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Celebrate UTSA’s 50th Anniversary and share social media posts about the 50th using the hashtag #UTSA50.
Adult Mental Health First Aid consists of 6 hours of instructor-led training, in which teaches adults how to recognize the signs and symptoms that suggest a potential mental health challenge, how to listen nonjudgmentally and give reassurance to the individual, student/colleague, who may be experiencing a mental health challenge, and how to refer a person to appropriate professional support and services at UTSAJohn Peace Library (4.04.12C), Main Campus
Refusing to Forget is a collaborative effort to examine and expose the devastating impact of state-sanctioned racial violence throughout the early 20th century in the Texas Borderlands. This will be a two-day workshop.Gregory Luna Room, Buena Vista Building, Downtown Campus
Join fellow UTSA accounting alumni for this fun-filled event that includes breakfast, a round of golf, an awards luncheon and great prizes. All proceeds from the tournament benefit student scholarships.Canyon Springs Golf Club, 24405 Wilderness Oak, San Antonio, TX 78260
The Faculty Coffee Chat is designed to provide faculty members the space to discuss current issues they are facing in an inclusive and supportive environment.Virtual Event
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Part 1 of our Career Skills Summer Workshop Series! Jeffrey Patten from the UTSA Career Center will be presenting on how to build a resume.Virtual Event
Week 2 of our Career Skills Summer Workshop series.Virtual Event
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Bell's TheoremJohn Bell showed in 1964 how the 1935 "thought experiment" of Einstein, Podolsky, and Rosen (EPR) could be made into a real experiment. Einstein was especially bothered by the "nonlocal" aspect of quantum mechanics exhibited by a measurement at one place instantaneously determining the properties (position and momentum, and later spin) of a particle detected at another place. The spacelike separation between the two measurements implied something "travelling" faster than the speed of light between the two. Actually, at the 1927 Solvay Conference, Einstein had already complained about "action at a distance" and faster-than-light effects when, in a single-slit version of the two-slit experiment, the detection of a single particle at one place instantaneously collapsed the probability (Ψ2) of finding it at a distant place. And we now know that Einstein probably saw this implicit violation of his theory of special relativity as early as 1905, when he formulated both relativity theory and the light-quantum hypothesis. See our history of Einstein's thought. EPR proposed the existence of supplementary parameters or "local hidden variables" that could communicate information between the two measurements. Einstein's colleagues Erwin Schrödinger, Max Planck, David Bohm, and others hoped that the hidden variables would allow a return to deterministic physics. They wanted to eliminate mysterious quantum phenomena like superposition of states, quantum entanglement and nonlocality, action at a distance, and - perhaps most important for Schrödinger - the irreducible statistical chance associated with the collapse of the wave function. Einstein's famous remark on quantum indeterminacy was that "God does not play dice." According to Wolfgang Pauli (in correspondence with Max Born), Einstein was less concerned with the return of determinism than he was with the restoration of "local reality" and the elimination of "action at a distance." In 1964, John Bell put limits on any supplementary parameters or "hidden variables" that might eliminate nonlocality and restore a deterministic physics in the form of what he called an "inequality," the violation of which would confirm standard quantum mechanics. Bell also described his key assertions in the simple idea that "local hidden variables" will never be found that give the same results as quantum mechanics. This has come to be known as Bell's Theorem. In a 1990 lecture at CERN, shortly before his untimely death, Bell made it plain that the violation of his inequality had shown the "Einstein program" to be a failure.
It just is a fact that quantum mechanical predictions and experiments, in so far as they have been done, do not agree with [my] inequality. And that's just a brutal fact of nature... No action at a distance led you to determinism, in the case of parallel polarisers, but determinism, in the case of off-parallel polarisers, leads you back to action at a distance. Now, in my opinion, in answer to the question that you posed at the beginning, I don't know this phrase is too strong and active an assertion, I cannot say that action at a distance is required in physics. But I can say that you cannot get away with no action at a distance. You cannot separate off what happens in one place and what happens in another. Somehow they have to be described and explained jointly. Well, that's just the fact of the situation; the Einstein program fails, that's too bad for Einstein, but should we worry about that?Bell's Theorem has been tested in numerous real EPR experiments over the years, by John Clauser, Alain Aspect, Michael Horne, Albert Shimony, and Richard Holt (in various CHSH-type experiments) and most recently by Nicolas Gisin and his colleagues in Geneva with entangled photons sent over miles of fiber optics. In the 1989 book, Sixty-two Years of Uncertainty, Abner Shimony summarized the significance of various versions of Bell's Theorem.
All versions of Bell's theorem are variations, and usually generalizations, of the pioneering paper of J.S. Bell of 1964, entitled "On the Einstein-Podolsky-Rosen Paradox." All of them consider an ensemble of pairs of particles prepared in a uniform manner, so that statistical correlations may be expected between outcomes of tests performed on the particles of each pair. If each pair in the ensemble is characterized by the same quantum state Φ, then the quantum mechanical predictions for correlations of the outcomes can in principle be calculated when the tests are specified. On the other hand, if it is assumed that the statistical behavior of the pairs is governed by a theory which satisfies certain independence conditions (always similar to the Parameter and Outcome Independence conditions stated below, though the exact details vary from version to version of Bell's theorem), then it is possible to derive a restriction upon the statistical correlations of the outcomes of tests upon the two particles. The restriction is stated in the form of an inequality, known by the collective name of "Bell's Inequality." Each version of Bell's theorem exhibits a choice of Φ and of the tests upon the two particles such that the quantum mechanical predictions of correlations violates one of the Bell's Inequalities. The theorem therefore asserts that no physical theory satisfying the specified independence conditions can agree in all circumstances with the predictions of quantum mechanics. The theorem becomes physically significant when the Experimental arrangement is such that relativistic locality prima facie requires that the independence conditions be satisfied. Because such arrangements are in principle possible (and, in fact, actually realizable, if certain reasonable assumptions are made), one can restate Bell's Theorem more dramatically as follows: no local physical theory can agree in all circumstances with the predictions of quantum mechanics.
The reason philosophers like Shimony have difficulty with two-particle wave-function collapses is clear from his exposition. It is quite wrong to describe two distinct particles, 1 and 2, with 1 entering the right analyzer and 2 entering the left analyzer. Just as a single particle cannot be localized in the two-slit experiment, neither particle in an EPR experiment is localizable until there is a measurement, at which time both become localized (to within the usual quantum indeterminacy) however far apart they are at that time (in the rest frame of the experiment). The reason we know everything about the "other" particle as soon as we measure one is, as Einstein knew well, but later writers often ignore, found in the various conservation laws (of energy, momentum, spin, etc.). If Bell's inequalities were not violated, the much more fundamental laws of conservation of momentum, angular momentum and spin would be violated. For a correct description of how quantum mechanics describes two particles in an entangled quantum state, see our description of the EPR experiment.Fig. 1. An ensemble of particle pairs 1 + 2 is emitted in a uniform manner from the source. Particle 1 enters an analyzer with a controllable parameter a, and the possible outcomes are sm (m = 1,2,...). Particle 2 enters an analyzer with controllable parameter b, and the possible outcomes are tn (n = 1,2,...).Figure 1 shows a source from which particle pairs, labeled 1 and 2, are emitted in a uniform manner. The complete state of a pair 1+2 is denoted by k, where k belongs to a space K of complete states. No assumption is made about the structure of K, except that probability measures can be defined on it. Because of the uniform experimental control of emission, it is reasonable to suppose that there is a definite probability measure w defined over K which governs the ensemble of pairs; but the uniformity need not be such that w is a delta-function, i.e., that every pair of the ensemble is in the same complete state k. Particle 1 enters an analyzer with a controllable parameter a, which the experimenter can specify, for instance, by turning a knob. Likewise, particle 2 enters an analyzer with a controllable parameter b.


Modern construction is an effort of precision. Manufacturers must use components manufactured to meet specific standards - such as beams of a desired composition or rivets of a specific size. The building industry relies on manufacturers to create these components reliably and reproducibly to build secure bridges and healthy skyscrapers.
Now imagine a construction on a smaller scale - less than 1 / 100th of the thickness of a piece of paper. It's the nanoscale. It is at this scale that scientists are working to develop potentially revolutionary technologies in areas such as quantum computing. It's also a scale where traditional manufacturing methods simply will not work. Our standard tools, even miniaturized, are too bulky and too corrosive to make nano-scale reproducible components.
Researchers at the University of Washington have developed a method for reproducible nanoscale fabrication. The team adapted light-based technology widely used in biology, known as an optical trap or optical tweezer, to operate in a water-free liquid environment containing carbon-rich organic solvents, thus enabling potential new applications.
As the team reports in an article published Oct. 30 in Nature Communications, optical tweezers act as a light-based "pulling beam" capable of assembling nanoscale semiconductor materials into larger structures. Unlike sci-fi tractor bundles, which catch spaceships, the team uses optical tweezers to trap materials nearly a billion times less than one meter.
"This is a new approach to manufacturing at the nanoscale," said Peter Pauzauskie, associate author and associate professor of materials science and engineering, faculty member of the Molecular Engineering & Sciences Institute and from the Institute for Nano-engineering systems. scientist at the Pacific Northwest National Laboratory. "The manufacturing process does not involve any chamber surface that minimizes the formation of deformations or other defects." All components are suspended in solution and we can control the size and shape of the nanostructure when assembled piece by piece . "
"The use of this technique in an organic solvent allows us to work with components that would deteriorate or corrode on contact with water or air," said Vincent Holmberg, co-lead author, assistant professor of chemical engineering at the University of Washington, professor at Clean Energy. Institute and Institute of Engineering and Molecular Sciences. "Organic solvents also help us to overheat the material we work with, allowing us to control material transformations and stimulate chemistry."
To demonstrate the potential of this approach, researchers used optical precelles to construct a new nanowire heterostructure, which is a nanowire consisting of discrete sections made of different materials. The starting materials of the heterostructure of nanowires were shorter "nanorodes" in crystalline germanium, each one hundred nanometers long and several tens of nanometers in diameter, about 5,000 times thinner than a hair human. Each is capped with a metallic bismuth nanocrystal.
The researchers then used the light-based "tractor beam" to capture one of the germanium nanorods. The beam energy also overheats the nanodod, melting the bismuth plug. They then guide a second nanoref in the "tractor beam" and weld them end to end, thanks to the molten bismuth cap. The researchers could then repeat the process until they assembled a patterned heterostructure of nanowires with repeating semiconductor metal junctions five to ten times longer than the different building blocks.
"We started to call this optically-oriented" photon nanosocket "assembly process, which is to weld two components together at the nanoscale using light," said Holmberg.
Nanowires that contain junctions between materials, such as the Germanium-bismuth junctions synthesized by the UW team, could possibly be a means of creating topological qubits for applications in quantum computing.
The tractor beam is actually a highly focused laser that creates a type of optical trap, a Nobel Prize winning method developed by Arthur Ashkin in the 1970s. To date, optical traps have been used almost exclusively in water-based or vacuum-based environments. The Pauzauskie and Holmberg teams adapted optical trapping to work in the more volatile environment of organic solvents.
"Generating a stable optical trap in any type of environment is a delicate balancing act and we were fortunate to have two very talented graduate students working together on this project," said Holmberg.
The photons that make up the laser beam generate a force on the objects in the immediate vicinity of the optical trap. Researchers can adjust the properties of the laser so that the force generated can trap or release an object, be it a germanium nanorode or a longer nanowire.
"This is the type of precision needed for reliable and reproducible nanofabrication methods without chaotic interaction with other surfaces or materials that can introduce defects or deformations into nanomaterials," said Pauzauskie.
The researchers believe that their nanosoldering approach could allow the additive manufacturing of nanoscale structures with different sets of materials for other applications.
"We hope this demonstration will inspire researchers to use optical trapping for the manipulation and assembly of a broader set of nanoscale materials, whether or not these materials are compatible with water," he said. Mr. Holmberg.
The lead co-authors of the paper are Elena Pandres, a UW graduate student in chemical engineering, and Matthew Crane, a UW PhD and postdoctoral researcher in UW's Department of Chemistry. Co-author is E. James Davis, Professor Emeritus of Chemical Engineering at the University of Washington. The research was funded by the National Science Foundation, the UW Molecular Engineering Materials Center, the UW Molecular Engineering & Sciences Institute, the UW Institute for Nano-engineering Systems, the UW Clean Energy Institute, Washington State, Washington Research Foundation and the Air Force's Scientific Research Office.
Matthew J. Crane, Elena P. Pandres, E. James Davis, Vincent C. Holmberg, Peter J. Pauzauskie. Optically oriented attachment of nanoscale metal-semiconductor heterostructures in organic solvents via photonic nanosoldering. Nature Communications, 2019; 10 (1) DOI: 10.1038/s41467-019-12827-w


A research team with the Technical University of Munich (TUM) have designed a quantum cryptography chip aimed at the security demands of the quantum computing revolution. The RISC-V chip, which was already sent to manufacturing according to the researchers' design, aims to be a working proof of concept for protecting systems against quantum computing-based attacks, which are generally considered to be one of the most important security frontiers of the future. Alongside the RISC-V based hardware implementation (which includes ASIC and FPGA structures), the researchers also developed 29 additional instructions for the architecture that enable the required workloads to be correctly processed on-chip.
Traditional cryptography is generally based on both the sender and receiver holding the same "unlock" key for any given encrypted data. These keys (which may include letters, digits, and special characters) have increased in length as time passes, accompanying increases in hardware performance available in the general computing sphere. The idea is to thwart brute-force attacks that would simply try out enough character combinations that would allow them to eventually reach the correct answer that unlocks the encrypted messages' contents. Given a big enough size of the security key (and also depending on the encryption protocol used), it's virtually impossible for current hardware — even with the extreme parallelization enabled by the most recent GPUs — to try out enough combinations in a short enough timeframe to make the effort worthwhile.
A piece of information cryptographically encoded by one of the most popular encryption algorithms used today, AES-128, would be impossible to crack by even the most powerful distributed computing efforts of today, Bitcoin. For reference, it would take the network around 70,000,000,000,000,000,000,000,000 years to do so (kudos if you can count that high a number) and it's estimated our universe has existed for only 14 billion years, comparatively speaking. Encryption-breaking algorithms on the quantum computing sphere would require quantum systems with an estimated 2,953 logical qubits for near-instant decryption of an AES-128 key, and 6,681 logical qubits for AES-256.
Current quantum technology has achieved a "mere" 100 qubits total, so we're still somewhat far-off from a security collapse. But quantum computing is advancing at a breakneck speed since the first actual first quantum computer manifestation — a dual-qubit system showcased in 1998 by Isaac Chuang of the Los Alamos National Laboratory, Neil Gershenfeld of the Massachusetts Institute of Technology (MIT), and Mark Kubinec of the University of California at Berkeley that could be loaded with data and output a solution. The acceleration in qubit counts for new quantum systems and the potential appearance of new decryption algorithms could upend current encryption techniques much faster than expected, and that's the reason why the TUM research team is focussing on pre-empting security challenges that are expected to eventually materialize.
In designing their quantum-security chip, the TUM researchers took a cohesive (and world first) hardware and software co-design approach, with purpose-designed hardware that accelerates the current poster-child for quantum cryptography, the lattice-based Kyber algorithm. The researchers say they've achieved a 10x performance increase compared to current software Kyber encryption solutions, while using around eight times less energy. The chip also features support and a 21x performance increase for an even more advanced form of quantum encryption, Supersingular Isogeny Key Encapsulation (SIKE), which is expected to be deployed when lattice-based approaches, such as Kyber, no longer cut it.
In addition to the Kyber and SIKE acceleration, the research team is also using this chip as an accelerator for smart hardware Trojan detection. Hardware Trojan is a term that refers to the addition of hardware-based solutions that aim to circumvent typical security mechanisms by offering backdoors that either siphon information to a remote attacker, or enable silent, undetected access to the compromised system's processing. These hardware Trojans can be secretly implemented in various stages of hardware fabrication (such as in the design or manufacturing stages), and concerns regarding this potential attack vector hit the public space with the (fake) reports of certain Supermicro-manufactured motherboards allegedly featuring purpose-built chips that siphoned data to China.
To fill the void of information on this novel security exploit, the TUM researchers have also fitted their chip with four distinct hardware Trojans. These will literally destroy their proof-of-concept chip layer by layer while feeding each step of the process to newly-developed machine learning algorithms, training them in identifying hardware functions even in the absence of technical information regarding what the hardware does exactly. This helps to identify components (Trojans) that perform functions unrelated to the chip’s actual tasks that may have made their way into the final design. This research will also likely provide lasting effects in the reverse-engineering space, and it's likely that it's being pursued by other parties (academic or otherwise).
Quantum computing stands at the forefront of a brave new world in the technology sphere. As I wrote this article, I was reminded of Arthur C. Clarke's Third Law: “Any sufficiently advanced technology is indistinguishable from magic”. I for one am having difficulty in distinguishing one from the other.


What is quantum computing?
Quantum computers have the ability to certain computations exponentially faster than any classically designed (super) computers ever could. This could lead to unprecedented advances in artificial intelligence disease eradication and much more. However, in the wrong hands these computers will also have the ability to break the current encryption algorithms keeping the internet, and our data, safe.
Classical computers (which you are probably currently viewing this page on) work on bits that can be either 1 or 0. You can think of this as a light switch turning a lightbulb on or off. On a quantum computer, the quantum bit (or qubit) can be 1, 0, or anything in between. This means the “light switch” can be on, off, or both at the same time. For data information, this means that a quantum computer can not only store multiple bits of data on the same qubits at the same time, but it can also compute all of that data at the same time also, making them exponentially more powerful than a classical computer.
For example, lets say you have four classical bits to store a number. Four bits allows you store any decimal number from 0 to 15, but only one at a time. If you wanted to store all 16 numbers you would need 16*4 classical bits. A quantum computer can store all 16 numbers on the same four bits at the same time, and do any calculation on them requested. This means a quantum computer with just 32 qubits, you could be in 232 = 4,294,967,296 states simultaneously which could translate to approximately 500 MB of data.
Are quantum computers available?
Governments around the world and high-tech giants such as Microsoft, Google, IBM, and more have pledged or already invested millions and even billions of dollars to develop large-scale quantum computers and there does not seem to be any reason to slow down now.
Google has recently announced it has achieved quantum supremacy, which is a term that signifies a single task was done on a quantum computer that would take thousands of years (even if possible) on a classical computer. This is another leap forward for quantum computing and moves us ever closer to the day large-scale quantum computers are available. With high-tech companies such as Google, Microsoft, Amazon, IBM, and more having already build small-scale quantum computers and countries like the United States, China, Russia and more already pledging billions of dollars to be the first to build a large-scale quantum computer, the race is on.
It is expected that in as little as five years from now we could begin to see some of the benefits of quantum computers to the technology, science, health, and environmental sectors. However, quantum computers large enough to break current cryptographic algorithms are more likely a decade away.
If large scale quantum computers are not available, am I safe?
The short answer is no. While the cryptographic security used today cannot be broken with current methods, it can be stored, and broken in the future when quantum computers are available. This type of attack is called a ‘harvest and decrypt’ attack. If information being sent today is still sensitive more than a decade from now (like banking data and classified governmental documents) then that information is already in danger.
A longer answer is that today, you are more likely to be hacked by having an insecure password, or by having no security set up at all. Governments around the world are working on standardizing quantum-safe solutions and companies are beginning to invest money into testing these solutions on their devices. It will be years before the quantum-safe solutions are implemented on servers and clouds and other connected devices, but the sooner we begin this transition the sooner we will be ready.
What is at risk?
Any device connected to a network is vulnerable to a quantum-enabled attacked, one quantum-computers are available. A big concern of industry today is the expected transition period. It took more than 15 years for industries to adopt ECC (elliptic curve cryptography) over RSA and the transition to quantum-safe solutions is expected to be even more challenging.
How are we helping?
At PQSecure, we focus on the risks that quantum computers pose, and that threat is to cryptography. There are multiple layers of security and encryption in place on most websites and cloud servers today to keep your data safe. However, if a single layer is broken, all of your stored data could be a risk. By making sure these layers are quantum-safe, we can avoid the risk of quantum computers, when they arrive.
PQSecure creates quantum-safe solutions that are designed to be power and energy efficient which makes them ideal for small, embedded devices such as IoT. With the fast growth of the IoT industry, these devices pose additional risks to your home or work networks. Each new devices adds an additional entry point for quantum-enabled hackers to access your data. And with the focus on these devices to be cheaper and faster, many of these IoT companies cannot find a viable solution, and thus are selling IoT devices without these crucial built-in security features.


In 1994, Peter Shor, a mathematician then at Bell Labs in New Jersey, proved that a quantum computer would have the power to solve some problems exponentially faster than a classical machine. The question was: Could one be built? Skeptics argued that quantum states were too delicate — the environment would inevitably jumble the information in the quantum computer, making it not quantum at all.
A year later, Shor responded. Classical error-correcting schemes measured individual bits to check for errors, but that approach wouldn’t work for quantum bits, or “qubits,” since any measurement would destroy the quantum state, and hence the calculation. Shor figured out a way to detect whether an error had occurred without measuring the state of the qubit itself. Shor’s code marked the beginning of the field of quantum error correction.
The field has flourished. Most physicists see it as the only path to building a commandingly powerful quantum computer. “We won’t be able to scale up quantum computers to the degree that they can solve really hard problems without it,” said John Preskill, a physicist at the California Institute of Technology.
As with quantum computing in general, it’s one thing to develop an error-correcting code, and quite another to implement it in a working machine. But at the beginning of October, researchers led by Chris Monroe, a physicist at the University of Maryland, reported that they had demonstrated many of the ingredients necessary to run an error-corrected circuit like Shor’s.
So how did Shor crack the conundrums he faced? He used the added complexity of quantum mechanics to his advantage.
Repeat Repeat Repeat
Shor modeled his protocol after the classical repeater code, which involves making copies of each bit of information, then periodically checking those copies against each other. If one of the bits is different from the others, the computer can correct the error and continue the calculation.
Shor designed a quantum version of this. He used three individual “physical” qubits to encode a single qubit of information — the “logical” qubit. Shor’s quantum repeater code couldn’t be exactly the same as the classical version, though. The essential power of quantum computation comes from the fact that qubits can exist in a “superposition” of being in a combination of 0 and 1 at the same time. Since measuring a quantum state would destroy the superposition, there wasn’t a straightforward way to check to see whether an error had occurred.
Instead, he found a way to tell if the three physical qubits were in the same state as one another. If one of the qubits was different, it would indicate that an error had occurred.
The task is not unlike solving a simple logic puzzle. You’re given three balls that look identical, but one of the balls might have a different weight. You also have a simple balance scale. What measurements will let you determine whether there is an oddball in the mix, and if so, which one it is?
The answer is to first pick two balls and compare their weights, then replace one of the balls with the remaining ball and check again. If the scale was balanced both times, then all balls are identical. If it was balanced only once, then one of the replaced balls is the odd one out. If the scales are imbalanced both times, the ball that stayed still is the culprit.
Shor’s code replaces the scales with two extra “ancilla” qubits. The first of these compares the first and second physical qubits; the other compares the second and third. By measuring the states of these ancillary qubits, you learn if the three information-containing qubits are in identical states without disturbing the state of any of them.
This code protects against a bit flip, which is the only possible error that can occur in classical computing. But qubits have one more potential source of error.
Superpositions are the key to quantum computing, but it’s not just the value of the qubit that’s important. The relative “phase” between qubits matters too. You can think of this phase as a wave — it tells you the location of the wave’s peaks and troughs. When two waves are in phase, their ripples are synchronized. If they collide, they will constructively interfere, merging into a single wave double the size. But if the waves are out of phase, then when one wave is at its peak, the other is at its nadir, and they will cancel each other out.
A quantum algorithm takes advantage of this phase relationship among its qubits. It sets up a situation where the correct answer to a calculation constructively interferes and is therefore amplified, while the incorrect answer gets suppressed by destructive interference.
But if an error causes the phase to flip, then destructive interference can switch to constructive interference, and the quantum computer will start amplifying the wrong answer.
Shor found that he could correct for phase errors using a similar principle to the one he used for bit flips. Each logical qubit gets encoded into three qubits, and ancilla qubits check to see if one of the phases has flipped.
Shor then combined the two codes. The result was a code that translated one logical qubit into nine physical qubits that offered both bit and phase checks.
Tolerant to a Fault
Shor’s code would in principle protect a single logical qubit from errors. But what if there was a mistake in the error measurements themselves? Then, in your attempt to correct the nonexistent error, you would flip a bit and unwittingly introduce a real error. In some cases, this could cause a cascade of errors to propagate through the code.
Shor’s code also didn’t consider how he would operate a quantum computer built from his logical qubits. “We need some way to do computations on the encoded states, without losing that protection. And that’s not straightforward,” said Daniel Gottesman, a theoretical computer scientist at the University of Maryland.
So in 1996, his third consecutive year of blazing trails, Shor came up with the notion of fault tolerance. A fault-tolerant code can deal with errors introduced by the environment, by imperfect operations on those qubits, and even by the error-correction steps themselves — provided the rate at which these errors occur is below a certain threshold.
Last month, Monroe and his group announced that they had used a fault-protected version of Shor’s code called the Bacon-Shor code to demonstrate nearly all the tools necessary for a fully fault-tolerant quantum computer. They encoded a logical qubit into the quantum states of nine ions, then, using four ancilla qubits, they showed that they could fault-tolerantly perform all single-qubit operations necessary for quantum computing. The result shows that a fault-tolerant quantum computer is possible.
This goal remains distant, though. Monroe thinks the advantage granted by error correction won’t be seen until quantum computers have reached about 100 logical qubits. Such a machine would require about 1,300 physical qubits, since each logical qubit needs nine physical qubits plus four ancillas. (The current largest quantum processor, IBM’s newly announced Eagle, has 127 physical qubits.) At that point, “we’re going to start making a qubit factory and then we’ll introduce error correction,” said Monroe. “But not before.”


What is end-to-end encryption?
End-to-end encryption (E2EE) is a method of secure communication that prevents third parties from accessing data while it's transferred from one end system or device to another.
In E2EE, the data is encrypted on the sender's system or device, and only the intended recipient can decrypt it. As it travels to its destination, the message cannot be read or tampered with by an internet service provider (ISP), application service provider, hacker or any other entity or service.
Many popular messaging service providers use end-to-end encryption, including Facebook, WhatsApp and Zoom. These providers have faced controversy around the decision to adopt E2EE. The technology makes it harder for providers to share user information from their services with authorities and potentially provides private messaging to people involved in illicit activities.
How does end-to-end encryption work?
The cryptographic keys used to encrypt and decrypt the messages are stored on the endpoints. This approach uses public key encryption.
Public key, or asymmetric, encryption uses a public key that can be shared with others and a private key. Once shared, others can use the public key to encrypt a message and send it to the owner of the public key. The message can only be decrypted using the corresponding private key, also called the decryption key.
In online communications, there is almost always an intermediary handing off messages between two parties involved in an exchange. That intermediary is usually a server belonging to an ISP, a telecommunications company or a variety of other organizations. The public key infrastructure E2EE uses ensures the intermediaries cannot eavesdrop on the messages that are being sent.
The method for ensuring a public key is the legitimate key created by the intended recipient is to embed the public key in a certificate that has been digitally signed by a recognized certificate authority (CA). Because the CA's public key is widely distributed and known, its veracity can be counted on; a certificate signed by that public key can be presumed authentic. Since the certificate associates the recipient's name and public key, the CA would presumably not sign a certificate that associated a different public key with the same name.
How does E2EE differ from other types of encryption?
What makes end-to-end encryption unique compared to other encryption systems is that only the endpoints -- the sender and the receiver -- are capable of decrypting and reading the message. Symmetric key encryption, which is also known as single-key or secret key encryption, also provides an unbroken layer of encryption from sender to recipient, but it uses only one key to encrypt messages.
The key used in single-key encryption can be a password, code or string of randomly generated numbers and is sent to the message recipient, enabling them to unencrypt the message. It may be complex and make the message look like gibberish to intermediaries passing it from sender to receiver. However, the message can be intercepted, decrypted and read, no matter how drastically the one key changes it if an intermediary gets ahold of the key. E2EE, with its two keys, keeps intermediaries from accessing the key and decrypting the message.
Another standard encryption strategy is encryption in transit. In this strategy, messages are encrypted by the sender, decrypted intentionally at an intermediary point -- a third-party server owned by the messaging service provider -- and then reencrypted and sent to the recipient. The message is unreadable in transit and may use two-key encryption, but it is not using end-to-end encryption because the message has been decrypted before reaching its final recipient.
Encryption in transit, like E2EE, keeps messages from being intercepted on their journey, but it does create potential vulnerabilities at that midpoint where they are decrypted. The Transport Layer Security encryption protocol is an example of encryption in transit.
How is end-to-end encryption used?
End-to-end encryption is used when data security is necessary, including in the finance, healthcare and communications industries. It is often used to help companies comply with data privacy and security regulations and laws.
For example, an electronic point-of-sale (POS) system provider would include E2EE in its offering to protect sensitive information, such as customer credit card data. Including E2EE would also help a retailer comply with the Payment Card Industry Data Security Standard (PCI DSS), which mandates that card numbers, magnetic stripe data and security codes are not stored on client devices.
What does end-to-end encryption protect against?
E2EE protects against the following two threats:
- Prying eyes. E2EE keeps anyone other than the sender and intended recipient from reading message information in transit because only the sender and recipient have the keys to decrypt the message. Although the message may be visible to an intermediary server that is helping move the message along, it won't be legible.
- Tampering. E2EE also protects against tampering with encrypted messages. There is no way to predictably alter a message encrypted this way, so any attempts at altering would be obvious.
What doesn't end-to-end encryption protect against?
Although the E2EE key exchange is considered unbreakable using known algorithms and current computing power, there are several identified potential weaknesses of the encryption scheme, including the following three:
- Metadata. While E2EE protects the information inside a message, it does not conceal information about the message, such as the date and time it was sent or the participants in the exchange. This metadata could give malicious actors with an interest in the encrypted information clues as to where they may be able to intercept the information once it has been unencrypted.
- Compromised endpoints. If either endpoint has been compromised, an attacker may be able to see a message before it is encrypted or after it is decrypted. Attackers could also retrieve keys from compromised endpoints and execute a man-in-the-middle attack with a stolen public key.
- Vulnerable intermediaries. Sometimes, providers claim to offer end-to-end encryption when what they really offer is closer to encryption in transit. The data may be stored on an intermediary server where it can be accessed.
Advantages of end-to-end encryption
The main advantage of end-to-end encryption is a high level of data privacy, provided by the following features:
- Security in transit. End-to-end encryption uses public key cryptography, which stores private keys on the endpoint devices. Messages can only be decrypted using these keys, so only people with access to the endpoint devices are able to read the message.
- Tamper-proof. With E2EE, the decryption key does not have to be transmitted; the recipient will already have it. If a message encrypted with a public key gets altered or tampered with in transit, the recipient will not be able to decrypt it, so the tampered contents will not be viewable.
- Compliance. Many industries are bound by regulatory compliance laws that require encryption-level data security. End-to-end encryption can help organizations protect that data by making it unreadable.
Disadvantages of end-to-end encryption
Although E2EE generally does a good job of securing digital communications, it does not guarantee data security. Shortcomings of E2EE include the following:
- Complexity in defining the endpoints. Some E2EE implementations allow the encrypted data to be decrypted and reencrypted at certain points during transmission. This makes it important to clearly define and distinguish the endpoints of the communication circuit.
- Too much privacy. Government and law enforcement agencies express concern that end-to-end encryption can protect people sharing illicit content because service providers are unable to provide law enforcement with access to the content.
- Visible metadata. Although messages in transit are encrypted and impossible to read, information about the message -- date sent and recipient, for instance -- is still visible, which may provide useful information to an interloper.
- Endpoint security. If endpoints are compromised, encrypted data may be revealed.
- Not future-proof. Although end-to-end encryption is a strong technology now, there is speculation that eventually quantum computing will render cryptography obsolete.
Applications that use E2EE
The first widely used E2EE messaging software was Pretty Good Privacy, which secured email and stored files and digital signatures. Text messaging applications frequently use end-to-end encryption, including Apple's iMessage, Jabber and Signal Protocol (formerly TextSecure Protocol). POS providers, like Square, also use E2EE protocols to help maintain PCI compliance.
In 2019, Facebook announced that all three of its messaging services would begin using E2EE. However, law enforcement and intelligence agencies argue that encryption limits Facebook's ability to police illegal activity on its platforms. The debate often focuses on how E2EE can make it more difficult to identify and disrupt child abuse on private messaging platforms.
Encryption is just one piece of data security in the enterprise. Learn more about all aspects of data security and compliance in our comprehensive guide.
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SANTA FE, N.M. Researchers at Los Alamos National Laboratories claim to have originated a blueprint for room-temperature quantum computers using such optical components as beam splitters, phase shifters and photodetectors. While some scientists contend that new kinds of nonlinear optical components must be invented before economical quantum computers can be realized, the Los Alamos team counters that artful use of feedback makes it possible to use existing optical components instead.
The new approach, currently at the simulation stage, suggests that a more practical route can be followed to build effective quantum computers. Current methods use bulky and expensive equipment such as nuclear magnetic-resonance imaging systems, and the quantum states used to encode quantum bits, or "qubits,"are maintained at temperatures close to absolute zero.
However, at room temperature, photons exhibit quantum behavior, and a lot of known technology can manipulate them. "The double-slit experiment, where a single photon goes through whichever parallel slit you put a photodetector behind, clearly demonstrates the quantum-mechanical aspects of photons," said Los Alamos National Laboratories researcher Emanuel Knill. "Others thought you needed a new kind of nonlinear optical component to make quantum computers with photons. We have shown that all you need is feedback."
Knill's work was done with another Los Alamos researcher, Raymond Laflamme, and with professor Gerard Milburn of the University of Queensland, St. Lucia, Australia.
Photons can act as the data in quantum computers by virtue of their dual wave/particle nature. The famous double-slit experiment sends a single photon toward two parallel slits and locates a single photodetector behind first one slit and then the other. No matter which slit the photodetector is put behind, it always detects the single photon.
How does the photon "know"which slit to go through? The answer is that it is acting as a wave instead of a particle, and thus goes through both until it is measured by the photodetector. The act of measurement instantaneously localizes the "particle" aspect of the photon essentially causing it to "condense" behind whichever slit the measurement is made.
For the optical quantum computer blueprint provided by the labs, the phase state as polarized either vertically or horizontally works off the ability of photons to represent 1s and 0s. With all quantum bits, the phase of a photon's wave can simultaneously represent both 1 and 0, since its phase can differ depending on the exact moment it is measured. Afterward that is no longer possible; the phase has become fixed as one or the other by the very act of measurement.
"Until our work, it was thought that the only way to get photons to interact with each other was with nonlinear optics, which is very difficult to implement,"said Knill. "Nonlinear media work fine if you send laser beams through them, but if you only send single photons through, essentially nothing happens."
To provide the necessary nonlinear coupling among qubits, using photons, the team of Knill, Laflamme and Milburn fell back on one of the most useful engineering techniques ever invented feedback.
By employing feedback from the outputs of the photodetectors, they were able to simulate the effect of nonlinear media without the disadvantages of actually using them. Essentially, the optical components capable of handling single photons were bent to the service of nonlinear couplings through feedback.
"People never thought to use feedback from the result of a photodetector, but that is where our nonlinearity comes from it was there all along," Knill explained. This technique was not tried because researchers assumed they could not reuse measurements in quantum computations.
"We discovered that you can use feedback, and that you can replace a nonlinear component with it," said Laflamme.
As in all quantum-mechanical systems, the most important principle has been to preserve "coherence" that is, to make sure that the qubits remain "unobserved" in their nebulous superposition of both 1 and 0 during a calculation. Once a measurement is made of a quantum-mechanical state, the system reverts to a normal digital system and the advantage of quantum computations is lost. That was why it was thought that feedback could not work because it would destroy the quantum coherence that forms the basis for quantum algorithms.
However, Knill, Laflamme and Milburn have shown that systems that combine qubits with ordinary bits in the feedback loop can simulate nonlinear optical components. "What we do essentially is destroy coherence in one place and manage to indirectly reintroduce it elsewhere so that only the coherence we don't care about gets lost in the measurement," said Knill.
The basic idea is that the original qubits to be used in a calculation can be prepared ahead of time by entangling them with what the researchers call "helper" qubits. Entangling ensures that the helper bits maintain the same state as the originals, even after they have gone through a quantum calculation. The helper qubits can then be independently processed with standard optical components, and after the calculation, they can be measured without destroying the coherence of the originals.
The results of measuring the helper qubits are introduced into the feedback loop, which then simulates a nonlinear optical component for a single photon. There is a price for the destroyed coherence of the helper bits, however. According to the researchers, the labs' quantum computer blueprint will make more errors than the already error-prone quantum computers designed elsewhere. To compensate, the team carefully architected their design to use built-in error correction in two subsequent stages.
"The most important discovery in quantum computing in the last five years has been quantum error correction," said Laflamme. "Using quantum error correction, we can mitigate the effect of the errors we introduce with our measurements."
The resulting architecture uses three distinct stages. In stage one, helper photons are generated by entanglement and teleported to a circuit running in parallel with the main calculation. Measurement of the helper bits, after the main calculation, is then introduced into the feedback loop to simulate the effect of a nonlinear coupling between two photons.
"We know when it succeeds by measuring the helper qubit. If the outcome is good, then we go on with whatever else we are going to do in the calculations, but if it fails then we forget about what we just did and start over," said Knill.
But calculations made in this way are successful only with a quantum probability of 1/4, which necessitates the second stage of the architecture.
In stage two, the success probability of stage one can be tuned arbitrarily close to 1. Unfortunately, however, the computing resources needed to achieve 100 percent accuracy can grow exponentially. To solve this problem, the researchers used a third error-correction stage drawing on the recent work of other scientists.
By freely providing the blueprint to the research community, they hope to interest engineers in setting up real-world experiments.


█ BRIAN HOYLE
A supercomputer is a powerful computer that possesses the capacity to store and process far more information than is possible using a conventional personal computer.
An illustrative comparison can be made between the hard drive capacity of a personal computer and a super-computer. Hard drive capacity is measured in terms of gigabytes. A gigabyte is one billion bytes. A byte is a unit of data that is eight binary digits (i.e., 0's and 1's) long; this is enough data to represent a number, letter, or a typographic symbol. Premium personal computers have a hard drive that is capable of storing on the order of 30 gigabytes of information. In contrast, a supercomputer has a capacity of 200 to 300 gigabytes or more.
Another useful comparison between supercomputers and personal computers is in the number of processors in each machine. A processor is the circuitry responsible for handling the instructions that drive a computer. Personal computers have a single processor. The largest supercomputers have thousands of processors.
This enormous computation power makes supercomputers capable of handling large amounts of data and processing information extremely quickly. For example, in April 2002, a Japanese supercomputer that contains 5,104 processors established a calculation speed record of 35,600 gigaflops (a gigaflop is one billion mathematical calculations per second). This exceeded the old record that was held by the ASCI White-Pacific supercomputer located at the Lawrence Livermore National Laboratory in Berkeley, California. The Livermore supercomputer, which is equipped with over 7,000 processors, achieves 7,226 gigaflops.
These speeds are a far cry from the first successful supercomputer, the Sage System CDC 6600, which was designed by Seymour Cray (founder of the Cray Corporation) in 1964. His computer had a speed of 9 megaflops, thousands of times slower than the present day versions. Still, at that time, the CDC 6600 was an impressive advance in computer technology.
Beginning around 1995, another approach to designing supercomputers appeared. In grid computing, thousands of individual computers are networked together, even via the Internet. The combined computational power can exceed that of the all-in-one supercomputer at far less cost. In the grid approach, a problem can be broken down into components, and the components can be parceled out to the various computers. As the component problems are solved, the solutions are pieced back together mathematically to generate the overall solution.
The phenomenally fast calculation speeds of the present day supercomputers essentially corresponds to "real time," meaning an event can be monitored or analyzed as it occurs. For example, a detailed weather map, which would take a personal computer several days to compile, can be complied on a supercomputer in just a few minutes.
Supercomputers like the Japanese version are built to model events such as climate change, global warming, and earthquake patterns. Increasingly, however, supercomputers are being used for security purposes such as the analysis of electronic transmissions (i.e., email, faxes, telephone calls) for codes. For example, a network of supercomputers and satellites that is called Echelon is used to monitor electronic communications in the United States, Canada, United Kingdom, Australia, and New Zealand. The stated purpose of Echelon is to combat terrorism and organized crime activities.
The next generation of supercomputers is under development. Three particularly promising technologies are being explored. The first of these is optical computing. Light is used instead of using electrons to carry information. Light moves much faster than an electron can, therefore the speed of transmission is greater.
The second technology is known as DNA computing. Here, recombining DNA in different sequences does calculations. The sequence(s) that are favored and persist represent the optimal solution. Solutions to problems can be deduced even before the problem has actually appeared.
The third technology is called quantum computing. Properties of atoms or nuclei, designated as quantum bits, or qubits, would be the computer's processor and memory. A quantum computer would be capable of doing a computation by working on many aspects of the problem at the same time, on many different numbers at once, then using these partial results to arrive at a single answer. For example, deciphering the correct code from a 400-digit number would take a supercomputer millions of years. However, a quantum computer that is about the size of a teacup could do the job in about a year.
█ FURTHER READING:
Stork, David G. (ed) and Arthur C. Clarke. HAL's Legacy: 2001's Computer Dream and Reality. Boston: MIT Press, 1998.
Cray Corporation. "What Is a Supercomputer?" Supercomputing. 2002. < http://www.cray.com/supercomputing >(15 December 2002).
The History of Computing Foundation. "Introduction to Supercomputers." Supercomputers. October 13, 2002. < http://www.thocp.net/hardware/supercomputers.htm >(15 December 2002).


In quantum mechanics, a singlet originally meant a linked set of particles whose net angular momentum is zero, that is, whose overall spin quantum number , though this meaning has since been generalized to include other situations. The link between the particles may be historical, such as two widely separated particles whose current angular momentum states originated in a single quantum event; or ongoing, such as two particles bound by charge. A set of linked particles that lacks net angular momentum is said to be in a singlet state.
Singlets and the related spin concepts of doublets and triplets occur frequently in atomic physics and nuclear physics, where one often needs to determine the total spin of a collection of particles. Since the only observed fundamental particle with zero spin is the extremely inaccessible Higgs boson, singlets in everyday physics are necessarily composed of sets of particles whose individual spins are non-zero, e.g. 1/2 or 1.
The origin of the term "singlet" is that bound quantum systems with zero net angular momentum emit photons within a single spectral line, as opposed to double lines (doublet state) or triple lines (triplet state). The number of spectral lines in this singlet-style terminology has a simple relationship to the spin quantum number: , and .
Singlet-style terminology is also used for systems whose mathematical properties are similar or identical to angular momentum spin states, even when traditional spin is not involved. In particular, the concept of isospin was developed early in the history of particle physics to address the remarkable similarities of protons and neutrons. Within atomic nuclei, protons and neutrons behave in many ways as if they were a single type of particle, the nucleon, with two states. The proton-neutron pair thus by analogy was referred to as a doublet, and the hypothesized underlying nucleon was assigned a spin-like doublet quantum number to differentiate between those two states. Thus the neutron became a nucleon with isospin , and the proton a nucleon with . The isospin doublet notably shares the same SU(2) mathematical structure as the angular momentum doublet. It should be mentioned that this early particle physics focus on nucleons was subsequently replaced by the more fundamental quark model, in which a proton or neutron is interpreted as bound systems of three quarks. The isospin analogy also applies to quarks, and is the source of the names up (as in "isospin up") and down (as in "isospin down") for the quarks found in protons and neutrons.
While for angular momentum states the singlet-style terminology is seldom used beyond triplets (spin 1), it has proven historically useful for describing much larger particle groups and subgroups that share certain features and are distinguished from each other by quantum numbers beyond spin. An example of this broader use of singlet-style terminology is the nine-member "nonet" of the pseudoscalar mesons.
The simplest possible angular momentum singlet is a set (bound or unbound) of two spin 1/2 (fermion) particles that are oriented so that their spin directions ("up" and "down") oppose each other; that is, they are antiparallel.
The simplest possible bound particle pair capable of exhibiting the singlet state is positronium, which consists of an electron and positron (antielectron) bound by their opposite electric charges. The electron and positron in positronium can also have identical or parallel spin orientations, which results in an experimentally distinct form of positronium with a spin 1 or triplet state.
An unbound singlet consists of a pair of entities small enough to exhibit quantum behavior (e.g. particles, atoms, or small molecules), not necessarily of the same type, for which four conditions hold: 1) the spins of the two entities are of equal magnitude; 2) the current spin values of both entities originated within a single well-defined quantum event (wave function) at some earlier location in classical space and time; 3) the originating wave function relates the two entities such a way that their net angular momentum must be zero, which in turn means that if and when they are detected experimentally, conservation of angular momentum will require their spins to be in full opposition (antiparallel); and 4) their spin states have remained unperturbed since the originating quantum event, which is equivalent to asserting that there exists no classical information (observation) of their status anywhere within the universe.
Any spin value can be used for the pair, but the entanglement effect will be strongest both mathematically and experimentally if the spin magnitude is as small as possible, with the maximum possible effect occurring for entities with spin 1/2 (e.g., electrons). Early thought experiments for unbound singlets usually assumed the use of two antiparallel spin 1/2 electrons. However, actual experiments have tended to focus instead on using pairs of spin 1 photons. While the entanglement effect is somewhat less pronounced with such spin 1 particles, photons are easier to generate in correlated pairs and (usually) easier to keep in an unperturbed quantum state.
The ability of positronium to form both singlet and triplet states is described mathematically by saying that the product of two doublet representations (meaning the electron and positron, which are both spin 1/2 doublets) can be decomposed into the sum of an adjoint representation (the triplet or spin 1 state) and a trivial representation (the singlet or spin 0 state). While the particle interpretation of the positronium triplet and singlet states is arguably more intuitive, the mathematical description enables precise calculations of quantum states and probabilities.
This greater mathematical precision for example makes it possible to assess how singlets and doublets behave under rotation operations. Since a spin 1/2 electron transforms as a doublet under rotation, its experimental response to rotation can be predicted by using the fundamental representation of that doublet, specifically the Lie group SU(2). Applying the operator to the spin state of the electron thus will always result in , or spin 1/2, since the spin-up and spin-down states are both eigenstates of the operator with the same eigenvalue.
Similarly, for a system of two electrons it is possible to measure the total spin by applying , where acts on electron 1 and acts on electron 2. Since this system has two possible spins, it also has two possible eigenvalues and corresponding eigenstates for the total spin operator, corresponding to the spin 0 and spin 1 states.
Singlets and Entangled States
It is important to realize that particles in singlet states need not be locally bound to each other. For example, when the spin states of two electrons are correlated by their emission from a single quantum event that conserves angular momentum, the resulting electrons remain in a shared singlet state even as their separation in space increases indefinitely over time, provided only that their angular momentum states remain unperturbed. In Dirac notation this distance-indifferent singlet state is usually represented as:
The possibility of spatially extended unbound singlet states has considerable historical and even philosophical importance, since considering such states eventually led to experimental exploration and verification of what is now called quantum entanglement. Quantum entanglement is the ability of quantum systems to maintain relationships that appear to violate the principle of locality, which Albert Einstein considered fundamental and defended throughout his life. Along with Podolsky and Rosen, Einstein proposed the EPR paradox thought experiment to help define his concerns with the non-locality of spatially distributed singlets, using it as a way to assert that quantum mechanics was incomplete.
The difficulty captured by the EPR thought experiment was that by perturbing the angular momentum state of either of the two particles in a spatially distributed singlet state, the quantum state of the remaining particle appears to be "instantaneously" altered, even if the two particles have over time become separated by light years of distance. A critical insight made decades later by John Stewart Bell, who ironically was a strong advocate of Einstein's locality-first perspective, showed that his Bell's theorem could be used to assess the existence or non-existence of singlet entanglement experimentally. The irony was that instead of disproving entanglement, which was Bell's hope, subsequent experiments instead established the reality of entanglement. In fact, there now exist commercial quantum encryption devices whose operation depends fundamentally on the existence and behavior of spatially extended singlets.
A weaker form of Einstein's locality principle remains intact, which is this: Classical, history-setting information cannot be transmitted faster than the speed of light c, not even by using quantum entanglement events. This weaker form of locality is less conceptually elegant than Einstein's absolute locality, but is sufficient to prevent the emergence of causality paradoxes.


Scientists capture the speediest ever motion in a molecule
The fastest ever observations of protons moving within a molecule open a new window on fundamental processes in chemistry and biology, researchers report today in the journal Science.
Their capturing of the movements of the lightest and therefore speediest components of a molecule will allow scientists to study molecular behaviour previously too fast to be detected. It gives a new in-depth understanding of how molecules behave in chemical processes, providing opportunities for greater study and control of molecules, including the organic molecules that are the building blocks of life.
The high speed at which protons can travel during chemical reactions means their motion needs to be measured in units of time called attoseconds, with one attosecond equating to one billion-billionth of a second. The teams observation of proton motion with an accuracy of 100 attoseconds in hydrogen and methane molecules is the fastest ever recorded. Dr John Tisch of Imperial College London says:
"Slicing up a second into intervals as miniscule as 100 attoseconds, as our new technique enables us to do, is extremely hard to conceptualise. Its like chopping up the 630 million kilometres from here to Jupiter into pieces as wide as a human hair."
Professor Jon Marangos, Director of the Blackett Laboratory Laser Consortium at Imperial, says this new technique means scientists will now be able to measure and control the ultra-fast dynamics of molecules. He says:
"Control of this kind underpins an array of future technologies, such as control of chemical reactions, quantum computing and high brightness x-ray light sources for material processing. We now have a much clearer insight into what is happening within molecules and this allows us to carry out more stringent testing of theories of molecular structure and motion. This is likely to lead to improved methods of molecular synthesis and the nano-fabrication of a new generation of materials."
Lead author Dr Sarah Baker of Imperial College believes that the technique is also exciting because of its experimental simplicity. She says:
"We are very excited by these results, not only because we have watched motion occurring faster than was previously possible, but because we have achieved this using a compact and simple technique that will make such study accessible to scientists around the world."
To make this breakthrough, scientists used a specially built laser system capable of producing extremely brief pulses of light. This pulsed light has an oscillating electrical field that exerts a powerful force on the electrons surrounding the protons, repeatedly tearing them from the molecule and driving them back into it.
This process causes the electrons to carry a large amount of energy, which they release as an x-ray photon before returning to their original state. How bright this x-ray is depends on how far the protons move in the time between the electrons removal and return. The further the proton moves, the lower the intensity of the x-ray, allowing the team to measure how far a proton has moved during the electron oscillation period.
Abigail Smith | EurekAlert!
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More and more automobile companies are focusing on body parts made of carbon fiber reinforced plastics (CFRP). However, manufacturing and repair costs must be further reduced in order to make CFRP more economical in use. Together with the Volkswagen AG and five other partners in the project HolQueSt 3D, the Laser Zentrum Hannover e.V. (LZH) has developed laser processes for the automatic trimming, drilling and repair of three-dimensional components.
Automated manufacturing processes are the basis for ultimately establishing the series production of CFRP components. In the project HolQueSt 3D, the LZH has...
Reflecting the structure of composites found in nature and the ancient world, researchers at the University of Illinois at Urbana-Champaign have synthesized thin carbon nanotube (CNT) textiles that exhibit both high electrical conductivity and a level of toughness that is about fifty times higher than copper films, currently used in electronics.
"The structural robustness of thin metal films has significant importance for the reliable operation of smart skin and flexible electronics including...
The nearby, giant radio galaxy M87 hosts a supermassive black hole (BH) and is well-known for its bright jet dominating the spectrum over ten orders of magnitude in frequency. Due to its proximity, jet prominence, and the large black hole mass, M87 is the best laboratory for investigating the formation, acceleration, and collimation of relativistic jets. A research team led by Silke Britzen from the Max Planck Institute for Radio Astronomy in Bonn, Germany, has found strong indication for turbulent processes connecting the accretion disk and the jet of that galaxy providing insights into the longstanding problem of the origin of astrophysical jets.
Supermassive black holes form some of the most enigmatic phenomena in astrophysics. Their enormous energy output is supposed to be generated by the...
Physicists in Garching observe novel quantum effect that limits the number of emitted photons.
The probability to find a certain number of photons inside a laser pulse usually corresponds to a classical distribution of independent events, the so-called...
Microprocessors based on atomically thin materials hold the promise of the evolution of traditional processors as well as new applications in the field of flexible electronics. Now, a TU Wien research team led by Thomas Müller has made a breakthrough in this field as part of an ongoing research project.
Two-dimensional materials, or 2D materials for short, are extremely versatile, although – or often more precisely because – they are made up of just one or a...


Putting a hole in the center of the donut--a mid-nineteenth-century invention--allows the deep-fried pastry to cook evenly, inside and out. As it turns out, the hole in the center of the donut also holds answers for a type of more efficient and reliable quantum information teleportation, a critical goal for quantum information science.
Quantum teleportation is a method of communicating information from one location to another without moving the physical matter to which the information is attached. Instead, the sender (Alice) and the receiver (Bob) share a pair of entangled elementary particles--in this experiment, photons, the smallest units of light--that transmit information through their shared quantum state.
In superdense teleportation of quantum information, Alice (near) selects a particular set of states to send to Bob (far), using the hyperentangled pair of photons they share. The possible states Alice may send are represented as the points on a donut shape, here artistically depicted in sharp relief from the cloudy silhouette of general quantum state that surrounds them. To transmit a state, Alice makes a measurement on her half of the entangled state, which has four possible outcomes shown by red, green, blue, and yellow points. She then communicates the outcome of her measurement (in this case, yellow, represented by the orange streak connecting the two donuts) to Bob using a classical information channel. Bob then can make a corrective rotation on his state to recover the state that Alice sent.
Image by Precision Graphics, copyright Paul Kwiat, University of Illinois at Urbana-Champaign
In simplified terms, Alice encodes information in the form of the quantum state of her photon. She then sends a key to Bob over traditional communication channels, indicating what operation he must perform on his photon to prepare the same quantum state, thus teleporting the information.
Quantum teleportation has been achieved by a number of research teams around the globe since it was first theorized in 1993, but current experimental methods require extensive resources and/or only work successfully a fraction of the time.
Now, by taking advantage of the mathematical properties intrinsic to the shape of a donut--or torus, in mathematical terminology--a research team led by physicist Paul Kwiat of the University of Illinois at Urbana-Champaign has made great strides by realizing "superdense teleportation".
This new protocol, developed by physicist and paper co-author Herbert Bernstein of Hampshire College in Amherst, MA, effectively reduces the resources and effort required to teleport quantum information, while at the same time improving the reliability of the information transfer.
With this new protocol, the researchers have experimentally achieved 88 percent transmission fidelity, twice the classical upper limit of 44 percent. The protocol uses pairs of photons that are "hyperentangled"--simultaneously entangled in more than one state variable, in this case in polarization and in orbital angular momentum--with a restricted number of possible states in each variable. In this way, each photon can carry more information than in earlier quantum teleportation experiments.
At the same time, this method makes Alice's measurements and Bob's transformations far more efficient than their corresponding operations in quantum teleportation: the number of possible operations being sent to Bob as the key has been reduced, hence the term "superdense."
Kwiat explains, "In classical computing, a unit of information, called a bit, can have only one of two possible values--it's either a zero or a one. A quantum bit, or qubit, can simultaneously hold many values, arbitrary superpositions of 0 and 1 at the same time, which makes faster, more powerful computing systems possible.
"So a qubit could be represented as a point on a sphere, and to specify what state it is, one would need longitude and latitude. That's a lot of information compared to just a 0 or a 1."
"What makes our new scheme work is a restrictive set of states. The analog would be, instead of using a sphere, we are going to use a torus, or donut shape. A sphere can only rotate on an axis, and there is no way to get an opposite point for every point on a sphere by rotating it--because the axis points, the north and the south, don't move. With a donut, if you rotate it 180 degrees, every point becomes its opposite. Instead of axis points you have a donut hole. Another advantage, the donut shape actually has more surface area than the sphere, mathematically speaking--this means it has more distinct points that can be used as encoded information."
Lead author, Illinois physics doctoral candidate Trent Graham, comments, "We are constrained to sending a certain class of quantum states called 'equimodular' states. We can deterministically perform operations on this constrained set of states, which are impossible to perfectly perform with completely general quantum states. Deterministic describes a definite outcome, as opposed to one that is probabilistic. With existing technologies, previous photonic quantum teleportation schemes either cannot work every time or require extensive experimental resources. Our new scheme could work every time with simple measurements."
This research team is part of a broader collaboration that is working toward realizing quantum communication from a space platform, such as the International Space Station, to an optical telescope on Earth. The collaboration--Kwiat, Graham, Bernstein, physicist Jungsang Kim of Duke University in Durham, NC, and scientist Hamid Javadi of NASA's Jet Propulsion Laboratory in Pasadena, CA--recently received funding from NASA Headquarter's Space Communication and Navigation program (with project directors Badri Younes and Barry Geldzahler) to explore the possibility.
"It would be a stepping stone toward building a quantum communications network, a system of nodes on Earth and in space that would enable communication from any node to any other node," Kwiat explains. "For this, we're experimenting with different quantum state properties that would be less susceptible to air turbulence disruptions."
The team's recent experimental findings are published in the May 28, 2015 issue of Nature Communications, and represent the collaborative effort Kwiat, Graham, and Bernstein, as well as physicist Tzu-Chieh Wei of State University of New York at Stony Brook, and mathematician Marius Junge of the University of Illinois.
Siv Schwink | EurekAlert!
New quantum liquid crystals may play role in future of computers
21.04.2017 | California Institute of Technology
Light rays from a supernova bent by the curvature of space-time around a galaxy
21.04.2017 | Stockholm University
The nearby, giant radio galaxy M87 hosts a supermassive black hole (BH) and is well-known for its bright jet dominating the spectrum over ten orders of magnitude in frequency. Due to its proximity, jet prominence, and the large black hole mass, M87 is the best laboratory for investigating the formation, acceleration, and collimation of relativistic jets. A research team led by Silke Britzen from the Max Planck Institute for Radio Astronomy in Bonn, Germany, has found strong indication for turbulent processes connecting the accretion disk and the jet of that galaxy providing insights into the longstanding problem of the origin of astrophysical jets.
Supermassive black holes form some of the most enigmatic phenomena in astrophysics. Their enormous energy output is supposed to be generated by the...
The probability to find a certain number of photons inside a laser pulse usually corresponds to a classical distribution of independent events, the so-called...
Microprocessors based on atomically thin materials hold the promise of the evolution of traditional processors as well as new applications in the field of flexible electronics. Now, a TU Wien research team led by Thomas Müller has made a breakthrough in this field as part of an ongoing research project.
Two-dimensional materials, or 2D materials for short, are extremely versatile, although – or often more precisely because – they are made up of just one or a...
Two researchers at Heidelberg University have developed a model system that enables a better understanding of the processes in a quantum-physical experiment...
Glaciers might seem rather inhospitable environments. However, they are home to a diverse and vibrant microbial community. It’s becoming increasingly clear that they play a bigger role in the carbon cycle than previously thought.
A new study, now published in the journal Nature Geoscience, shows how microbial communities in melting glaciers contribute to the Earth’s carbon cycle, a...
20.04.2017 | Event News
18.04.2017 | Event News
03.04.2017 | Event News
21.04.2017 | Physics and Astronomy
21.04.2017 | Health and Medicine
21.04.2017 | Physics and Astronomy


Simon Watson demystifies the complex world of quantum computing
Quantum computers are regularly heralded as the future of computing, harnessing the power of atoms and elementary particles to perform calculations that today’s computers could only dream of. Quite how this remarkable feat is achieved is either complicated with jargon such as ‘qubits’, ‘superposition’ and ‘entanglement’ with no further description, or dismissed as too complicated for a layman. This article aims to explain how quantum computers work, why they’re faster than classical computers, and why they’re not a replacement for them.
Before we can describe how a quantum computer works, we need to understand today’s classical computers. Currently, computers work by manipulating ‘bits’ of data. A bit is something that can take one of two values, commonly written as 0 or 1. For example, a coin can be either heads or tails, or a light-switch can be on or off. In the case of a computer, the values may be a charged or discharged capacitor in memory, or the presence or absence of a groove on a CD. Computers operate on strings of eight bits, termed a ‘byte’. These bytes form instructions sent to the computer’s processor, directing it to perform functions such as adding two numbers, printing to the screen, or writing to memory.
Quantum computers work fundamentally differently. Rather than using a difference in electric voltage to encode the bit values, they use the physical properties of fundamental particles or atoms. As long as there are two different measurable states, a bit value can be stored. For example, electrons are sub-atomic particles that have a property called spin. This can be imagined similar to the rotation of a ball around its axis; just as a ball can rotate clockwise or anti-clockwise, electrons can have a spin value of 1/2 or -1/2 (termed ‘up’ and ‘down’). The bit value can therefore be assigned by measuring the spin state of the electron. Another example would be the polarization state of light. Light travels through space as a transverse wave, oscillating perpendicular to its direction of motion. A wave travelling along for example the z-axis can be oscillating about either the x- or y-axis. We could therefore store the bit value by whether the light is horizontally- or vertically-linearly polarized.
Were the analogy to end there, quantum computing would be no more complicated than classical computing. However, in 1930 theoretical physicist Paul Dirac published the first edition of his book The Principles of Quantum Mechanics. In it, he introduced the world to the revolutionary concept of ‘quantum superposition’ that now forms the backbone of quantum mechanics. Dirac was trying to explain the baffling evidence that light acts as both a wave and a particle–the so-called ‘wave-particle duality’ theory. On the one hand, Thomas Young’s double-slit experiment showed that when a laser was shone through two parallel slits, it diffracted like a classical wave, with the two waves interfering with each other where they were out of phase. In contrast, alternative evidence, such as the emission of photoelectrons by atoms when they absorb light of a particular frequency, showed that light was composed of discrete particles with definite energy and momentum, termed photons.
Dirac considered the problem of a beam of light containing a single photon passing through a double-slit. For the light to pass through the apparatus and cause an interfering diffraction pattern the single photon must partly go through both slits, with each part interacting with the other–it is in a superposition! This idea of wave-particle duality and superposition was later shown to not be restricted to light, but universally extended to all particles. Quantum superposition therefore holds that a physical system exists at some probability in all possible states simultaneously.
This phenomenon of superposition becomes even more bizarre when you extend it to particles that originate from the same source or are brought to interact together. Such particles do not exist in superposition independent of each other, but rather their quantum states become ‘entangled’ so that their physical properties can only be described relative to each other. For example, a particle with spin 0 may decay into two particles, each with spin 1/2. These particles, because they are entangled, exist in superposition where in addition to both being spin up or down at some probability, they have a probability of being in their anti-correlated spin states up/down and down/up simultaneously. They therefore do not individually have a spin direction of their own, but rather their state is defined as being opposite each other.
A system with 10 qubits holds the same information as 1024 classical bits, while 300 qubits holds more information than there are particles in the universe!
If we return now to the quantum computer, quantum mechanics dictates that in addition to the quantum bit (termed a ‘qubit’) having two measurable states (for example, spin up or down), it exists in a superposition where it has both states at the same time. It therefore has some probability of being both 0 and 1 at the same time. This means that the amount of information each qubit can hold is significantly larger than its equivalent bit. Consider a computer consisting of two classical bits. To fully describe the possible states of the system (00, 01, 10, 11), only the values of each bit are required. So the computer has an information capacity of two. The corresponding quantum computer has its entangled qubits in a superposition of all states, with a separate probability of being in each state: the probability of being in state |00> (for example, both electrons have spin down) is a; the probability of them being in state |11> (for example both electrons have spin up) is b; and the probability of being in states |01+10> and |01-10> (that is in an entangled superposition) is c and d respectively. To fully describe this quantum system, four probability values (a, b, c, d) are required. This two-qubit system therefore holds double the amount of information as the classical two-bit system, with each additional qubit exponentially increasing the amount of information it can contain. A system with 10 qubits holds the same information as 1024 classical bits, while 300 qubits holds more information than there are particles in the universe!
However, accessing the information stored in these qubits is not a simple matter, as superposition doesn’t automatically make any computation faster than a classical computer. The quantum computer must be designed, and quantum algorithms written specially, to utilise the probabilities in the entangled qubits’ superimposed states and get the desired speedup. Otherwise it is nothing more than a very fancy, but expensive, classical computer containing only a few bits. This severely constrains its applicability to solving specific problems, such as using Shor’s quantum algorithm for factorising integers. While this doesn’t sound very exciting, the widely-used public-key cryptography relies on the intractable time it takes to factorize very large numbers in keeping messages encrypted. If quantum computers can factorise quickly, these encrypted messages can be easily read. However, to date the largest integer that has been successfully factorised by a quantum computer is 143! Much money and research is therefore being invested in this field; in 2013 Canadian company D-Wave claimed to have a 512-qubit computer that solved a Travelling Salesman problem over 3,600 times faster than a classical computer. So, while quantum computers will probably not replace personal computers, they are also not just a proof of concept.
Simon Watson is a postdoctoral researcher at the Wellcome Trust Sanger Institute.
Featured image: jurvetson