Imagine if engineers could build a computer to be millions of times faster than anything that exists today, yet so small it’s microscopic. John Preskill, a theoretical physicist at the California Institute of Technology, explains the science behind quantum computing, the next great frontier in computer science. "Science Behind the News" is produced in partnership with the National Science Foundation.
Science Behind the News – Quantum Computing
ANNE THOMPSON reporting:
Whether at home, the office, or in the palms of our hands, computer technology is getting smaller, faster, and more inseparable from our everyday lives. But imagine if engineers could build a computer to be millions of times faster than anything that exists today, yet so small it's microscopic. In October 2012, the Nobel Prize in Physics was awarded to Serge Haroche and David Wineland for their research on a new type of computer that may revolutionize the way information is processed-the quantum computer.
Prof. JOHN PRESKILL (California Institute of Technology): It's really a qualitatively different way of encoding, using, processing information than the way we do it in the computers we have today.
THOMPSON: Dr. John Preskill is an NSF funded theoretical physicist at the California Institute of Technology, who works in the field of quantum computing. A quantum computer is made up of two or more atoms or electrons, called quantum bits, or "qubits." These qubits, like all atomic particles, operate according to the laws of quantum mechanics.
PRESKILL: The word quantum refers to the laws of physics that describe microscopic objects, the laws of physics that hold sway at the scale of individual atoms, single electrons.
THOMPSON: While quantum computers sound complex, in reality, the way qubits represent information is the same as in traditional computers-- by using binary digits, or bits, designated as 0's or 1's. Scientists can control how these qubits exchange information from one to another by using the laws of physics to manipulate their state, spin, or vibration. The first method involves isolating two individual atoms and altering their energy state.
PRESKILL: We can shine lasers on the atoms and in a controlled way change the state of an atom from say to ground state to some combination of the ground state and the excited state.
THOMPSON: Normally an atom's electrons occupy the "ground state", which is the lowest level of energy an electron can occupy. Its configuration is represented on the Periodic Table of the Elements. If an atom's electrons do not match the ground state, then it's considered to be in the "excited state." By manipulating the state of an atom's electrons, scientists can make them represent either the 0 or 1 bit.
PRESKILL: And we could store a bit, like we do in digital computers today, by preparing each atom in either its ground state or an excited state.
THOMPSON: The second method for building a quantum computer involves controlling the spin of two isolated electrons. This spin can either be up or down, allowing them to also represent either the 0 or 1 bit.
PRESKILL: Electrons are like little magnets. And so the electron has a north pole and a south pole. And so we could store just an ordinary bit by saying that the electron's spin, its magnet, is oriented either up or down.
THOMPSON: David Wineland received the Nobel Prize for devising a third type of quantum computer, by isolating charged atoms, or ions, in an ion trap.
PRESKILL: The trap is like a bowl, and the ion sits at the bottom of the bowl, and it can rock back and forth around the bottom. And we can excite those vibrational modes, depending on whether the atom is in its ground state or its excited state. And that allows the two atoms to talk to one another.
THOMPSON: Though today's quantum computers are only a few qubits long, scientists hope they will reach the scale of thousands or even millions of qubits and be able to perform calculations too large and complex for today's traditional computers. Such breakthroughs could spark incredible advances in cybersecurity, medicine, science, and countless other fields.
PRESKILL: Probably the most important applications are ones that we just haven't thought of yet. Because quantum computing is a very new idea.
THOMPSON: Quantum computing, a new idea that could pave the way for big changes, by operating in very small ways.
Mathematics is integral to computers. Most computer processes and functions rely on mathematical principles. The word "computers" is derived from computing, meaning the process of solving a problem mathematically. Large complex calculations (or computing) in engineering and scientific research often require basic calculators and computers.
Science Behind the News, Computers, Quantum, Quantum Computers, Computing, Atoms, Electrons, Subatomic, Atomic, Particles, John Preskill, California Institute of Technology, Caltech, Bits, Quantum Bits, Qubits, Nobel Prize, Physics, David Wineland, Serge Haroche, Digits, Information, Data, Ground State, Excited State, Physical, Periodic Table, Elements, Spin, Vibration, Ions, Ion Trap, Electromagnetic, Field, Magnetic Poles, Cybersecurity, Cyber Security, National Science Foundation, NSF


Since there are four possibilities, her choice of operation represents two bits of classical information. Note that transforming just one bit of an entangled pair means performing the identity transformation on the other bit. Alice then sends her qubit to Bob who must deduce which Bell basis state the qubits are in. Bob first applies a controlled-NOT to the two qubits of the entangled pair.
Bob then measures the second qubit. If the measurement returns |0〉, the encoded value was either 0 or 3; otherwise the value was either 1 or 2. Bob now applies H to the first bit and measures that bit (see Table below).
This allows him to distinguish between 0 and 3, and 1 and 2, as shown in the table below.
In principle, dense coding can permit secure communication: the qubit sent by Alice will only yield the two classical information bits to someone in possession of the entangled partner qubit. But more importantly, it shows why quantum entanglement is an information resource. It reveals a relationship between classical information, qubits, and the information content of quantum entanglement.
Teleportation is the ability to transmit the quantum state of a given particle using classical bits and to reconstruct that exact quantum state at the receiver. The no-cloning principle, however, requires that the quantum state of the given particle be necessarily destroyed. Instinctively, one perhaps realizes that teleportation may be realizable by manipulating a pair of entangled particles; if we could impose a specific quantum state on one member of an entangled pair of particles, then we would be instantly imposing a predetermined quantum state on the other member of the entangled pair. The teleportation algorithm is due to Charles Bennett and his team (1993)34.
Teleportation of a laser beam consisting of millions of photons was achieved in 1998. In June 2002, an Australian team reported a more robust method of teleporting a laser beam. Teleportation of trapped ions was reported in 200435. In May 2010, a Chinese research group reported that they were able to “teleport” information 16 kilometers36. In July 2017, a Chinese team reported “the first quantum teleportation of independent single-photon qubits from a ground observatory to a low Earth orbit satellite – through an up-link channel – with a distance up to 1400 km”37. This experiment is an important step forward in establishing a global scale quantum internet in the future. In theory, there is no distance limit over which teleportation can be done. But since entanglement is a fragile thing, there are technological hurdles to be overcome.
To see how teleportation works, let Alice possess a qubit of unknown state |Ø〉 = a |0〉 + b |1〉. She wishes to send the state of this qubit to Bob through classical channels. In addition, Alice and Bob each possess one qubit of an entangled pair in the state
Alice applies the decoding step of dense coding to the qubit ∅ to be transmitted and her half of the entangled pair. The initial state is
of which Alice controls the first two qubits and Bob controls the last qubit. She now applies Cnot⊗ I and H⊗ I⊗ I to this state:
Alice measures in the Bell basis the first two qubit to get one of |00〉, |01〉, |10〉, or |11〉 with equal probability. That is, Alice’s measurements collapse the state onto one of four different possibilities, and yield two classical bits. Alice sends the result of her measurement as two classical bits to Bob. Depending on the result of the measurement, the quantum state of Bob’s qubit is projected to a(|0〉 + b|1〉, a(|1〉 + b|0〉, a(|0〉- b|1〉, or a(|1〉 -b|0〉 respectively38. Note that Alice’s measurement has irretrievably altered the state of her original qubit ∅ , whose state she is trying to send to Bob. Thus, the no-cloning principle is not violated. Also, Bob’s particle has been put into a definite state.
When Bob receives the two classical bits from Alice he knows how the state of his half of the entangled pair compares to the original state of Alice’s qubit.
Bob can reconstruct the original state of Alice’s qubit ∅ by applying the appropriate decoder to his part of the entangled pair. Note that this is the encoding step of dense coding.
The interesting facts to note are as follows. First, the state that is transmitted is completely arbitrary (not chosen by Alice and unknown to her). Second, a message with only binary classical information, such as the result of the combined experiment made by Alice is definitely not sufficient information to reconstruct a quantum state; in fact, a quantum state depends on continuous parameters, while results of experiments correspond to discrete information only. Somehow, in the teleportation process, binary information has turned into continuous information! The latter, in classical information theory, would correspond to an infinite number of bits.
It also happens that Alice cannot determine the state of her particle with state ∅ by making a measurement and communicating the result to Bob because it is impossible to determine the unknown quantum state of a single particle (even if one accepts only an a posteriori determination of a perturbed state); one quantum measurement clearly does not provide sufficient information to reconstruct the whole state, and several measurements will not provide more information, since the first measurement has already collapsed the state of the particle. Note also that without the classical communication step, teleportation does not convey any information at all. The original qubit ends up in one of the computational basis states |0〉 or |1〉 depending on the measurement outcome.
Quantum teleportation can be used to move quantum states around, e.g., to shunt information around inside a quantum computer or indeed between quantum computers. Quantum information can be transferred with perfect fidelity, but in the process the original must be destroyed. This might be especially useful if some qubit needs to be kept secret. Using quantum teleportation, a qubit could be passed around without ever being transmitted over an insecure channel. In addition, teleportation inside a quantum computer can be used as a security feature wherein only one version of sensitive data is ensured to exist at any one time in the machine. We need not worry about the original message being stolen after it has been teleported because it no longer exists at the source location. Furthermore, any eavesdropper would have to steal both the entangled particle and the classical particle in order to have any chance of capturing the information.
11. Conclusion of Part II
Thus far we have, by a variety of examples, shown the power of quantum computing. In Section 10 we concluded Part II by describing some of the prized algorithms.
Readers desirous of getting some hands-on experience with a few of the algorithms presented in Part II can visit https://acc.digital/Quantum_Algorithms/Quantum_Algorithms_June2018.zip . This material is provided by Vikram Menon using the IBM Q Experience for Researchers (see https://quantumexperience.ng.bluemix.net/qx/experience).
34 Bennett, et al (1993). See also: Rieffel & Polak (2000).
35 Riebe, et al (2004). Barrett, et al (2004).
36 Jin, et al (2010).
37 Ren, et al (2017). A report appears in: Emerging Technology from the arXiv. First Object Teleported from Earth to Orbit. MIT Technology Review, 10 July 2017, https://www.technologyreview.com/s/608252/first-object-teleported-from-earthto- orbit of the states a(|0〉 + b|1〉, a(|1〉 + b|0〉, a(|0〉- b|1〉, or a(|1〉 – b|0〉.
38 Note that due to the measurement Alice made, the measured qubits have collapsed. Hence only Bob’s qubit can be in one


Jefferson Lab's Free-Electron Laser explores promise of carbon nanotubes
Webs of nanotubes form on collector plates during the collaboration's FEL experiment (image not actual size).
Jefferson Lab's Free-Electron Laser used to explore the fundamental science of how and why nanotubes form, paying close attention to the atomic and molecular details
Scientists and technologists of all stripes are working intensively to explore the possibilities of an extremely strong and versatile cylinder so tiny that millions — which in bunches look like an ebony snowflake — could fit easily on the tip of a pin. The objects in question are known as carbon nanotubes, first discovered in 1991 as the elongated form of an all-carbon molecule.
Sometimes called CNTs, nanotubes take up an extremely small space but can connect together materials with different properties, even as their own properties can be adjusted depending on formulation. The tubes' "aspect ratio" is enormous: that is, they are very long but not wide, and like an ultra-strong rope, can be extended without sacrificing strength. CNTs have potential applications in molecular and quantum computing and as components for microelectromechanical sensors, or MEMS. The tubes could also function as a "lab on a chip," with attached microelectronics and components that could detect toxins and nerve agents in vanishingly small concentrations.
Nanotubes could also lead to an entirely new generation of materials: as strong or stronger than steel, but very lightweight. CNTs are amazingly damage-tolerant, generally displaying nearly total "elastic recovery," even under high-deformation conditions. If bent, buckled or creased the tubes are usually able to reassume their original shape once external stressors are removed.
"Nanotubes take up a very small amount of space but can connect a lot of material together," says Brian Holloway, an assistant professor in the College of William & Mary's Department of Applied Science. "You can imagine replacing metal components with nanotubes that could weigh maybe a tenth as much. One of the big reasons NASA is interested is obviously because of the cost of getting to space."
Brian Holloway, William & Mary professor, prepares the nanotube oven, a component that helps produce nanotubes with light from JLab's Free-Electron Laser.
A research team led by Holloway is also intrigued by the tubes' potential. Holloway's group has used Jefferson Lab's Free-Electron Laser (FEL) to explore the fundamental science of how and why nanotubes form, paying close attention to the atomic and molecular details. Already, in experiments, the William & Mary/NASA Langley collaboration has produced tubes as good as if not better than those at other laboratories or in industry.
The next step will be to increase quantity while holding costs down, which Holloway believes will be possible using the Lab's upgrade of the FEL to 10 kilowatts.
"Right now we're interested in making more nanotubes," Holloway says. "The FEL offers a way to efficiently and cost-effectively make large amounts of high-quality tubes. Nanotubes come in a variety of flavors; the thought is we could eventually control what we call 'tube chiralities,' [properties like] structure, length and diameter."
The CNT collaboration makes the tubes by striking a metal-impregnated carbon target with FEL light. The laser vaporizes layers of a graphite annulus, essentially a thick ring mounted on a spinning quartz rod. Atoms discharge from the annulus surface, creating a plume, a kind of nanotube "spray." Under the right conditions trillions upon trillions of nanotubes can be so formed within an hour.
Conventional means of nanotube production involves a tabletop laser. In this more traditional manufacturing approach, perhaps 10 milligrams — about one-tenth of an aspirin-bottle full — of the tubes can be produced per hour at costs up to $200 per gram. Conversely, with a one-kilowatt FEL, up to two grams per hour, or about 100 times more nanotubes can be made, at a cost of $100 per gram. A 10-kilowatt FEL could radically alter that equation. To that end, Holloway is seeking funding from NASA and the Office of Naval Research for a three-year project whose goal would be to optimize nanotube production with the upgraded FEL in order to manufacture large quantities quickly and cheaply.
According to Gwyn Williams, FEL Basic Research Program manager, researchers are anticipating learning much more about the details of the photochemical processes involved in nanotube production once the new FEL comes back on line in 2003. Demand for the tubes is intense and growing. Whoever finds a way to make them reliably and affordably could reap the rewards, financially and otherwise, as commercial interests beat a figurative path to researchers' doors.
"A lot of people can make nanotubes. Very few can make grams or kilograms of nanotubes on time scales less than weeks," Holloway points out. "Factors other than price can drive demand. Right now there's no one who could sell you one kilogram of nanotubes per month all of the same quality, at any price."
Jefferson Science Associates, LLC, a joint venture of the Southeastern Universities Research Association, Inc. and PAE, manages and operates the Thomas Jefferson National Accelerator Facility, or Jefferson Lab, for the U.S. Department of Energy's Office of Science.
DOE’s Office of Science is the single largest supporter of basic research in the physical sciences in the United States and is working to address some of the most pressing challenges of our time. For more information, visit https://energy.gov/science.


The big goal: a large quantum computer
Solving the puzzles and challenges posed in Quantum Moves will allow the team of physicists in Aarhus University to take an important step towards building a large-scale quantum computer.
A quantum computer is a computer built using the some of the smallest physical building blocks, such as single atoms. It operates under the rules of quantum physics, making is very different from the normal computers we are used to encountering.
Why all the fuss about quantum computers?
There are essentially two answers.
The first reason is practical. Moore's law, introduced in 1965, Gordon E. Moore, makes the observation that the computational power of the machines doubles every 18 months. This leads to an ever-decreasing size of fundamental logical units. The fact that this decrease cannot go on indefinitely poses the fundamental challenges that chip manufacturers currently face in achieving more computational power. Very soon the size of a chip will be comparable to a single atom.
Why is this such a challenge? The law's of physics change radically when we enter the world of atoms and other small things. In this world, all physical rules are dictated by quantum mechanics. These rules forbid some things that we are used to, such as certain positions of atoms or electrons. On the other hand, they allow things that are impossible in our everyday life, like being in many places at the same time and walking though walls!
Shrinking a computer to this size means that the computer is not just small, it's also pretty crazy. Scientists have to word hard to make sure that their new minuscule computers do all the calculations they are supposed to do, despite the quantum rules.
The second reason to get excited about quantum computers is exactly all the quirkiness of quantum objects! Used right, all the new features of the quantum computer can be harnessed to make totally different types of computing machines that are much more powerful than ordinary computers.
Take the ability of an atom to be in two places simultaneously, or to be in two states at the same time. This is known as the superposition principle and it's pretty much like seeing the head-side and the tail-side of a coin at the same time. It enables the creation of qubits (quantum bits), bits that can be 'zero' and 'one' at the same time.
All computations are based on operations on bit strings, long chains of 'zeros' and 'ones'. If we have a string of qubits, we can code gigantic amounts of information into reasonable short chains. This is because a string of, say, three qubits, can be in a state '000' at the same time as it is in a state '001', '011', '111' and so on - in fact, we can express 2^3=8 bit stings in a 3-qubit string. Four qubits can express 2^4=16 bit strings, 10 qubits express a whopping 1024 strings and if we have a qubit string of just 260 qubits, it can contain more information than there are atoms in the universe. This quantum property allows huge parallel computations and means that just one quantum computer would have more computational power than all conventional computers combined!
Prototypes of quantum computers are currently developed in physics labs all around the world. The problem they face is the immense difficulty of making them big enough to be really interesting. The quantum objects used to create qubits are badly behaved rascals and rarely do the exact things they are told to do. The best available prototypes can tame strings of about 10-20 qubits, which is not yet enough to unleash the full power of quantum computing.
Our contribution in Aarhus
Quantum Moves is based on an idea of storing single atoms in a very specific trap, where each atom sits in a well like an egg in an egg tray. With such a trap, physicists can store around 300 atoms in a neat configuration. Just imagine being able to use each of these atoms as a qubit! This is, in fact, possible, and with such a configuration we are getting tantalisingly close to having a quantum computer with the superpowers everyone is fussing over.
The missing piece is doing operations and calculations on this large qubit string. Operations are done by picking up individual atoms, moving them around the egg tray trap and merging them with other atoms. This has to be done with great care to preserve the state of the atom (whether it's 'zero, 'one' or a superposition of both) - but also fast, to avoid outside noise and keep calculations efficient.
Sound familiar? This is exactly the challenge posed in the Quantum Moves game! Players move and merge atoms with the goal of ending up in very specific final shapes (which are actually just different states). Our engines take this information and translate it to the way a laser beam is used to pick up and move around an atom in the lab. Different challenges in Quantum Moves correspond to different operations on the qubit strings. Once we have a whole toolbox of operations, we are ready to turn on the 300-qubit quantum computer and start addressing the hugely important and impactful task of working on problems that have been "impossible" to solve for the best present-day supercomputers.


Earth emits gravitational waves as it orbits the Sun, though the amount of energy lost is imperceptible over the lifetime of the Solar System. Binary black holes are a different matter: Once they are relatively close, they shed a tremendous amount of energy, bringing them closer together with each orbit. (Binary black stars are thought to emit more gravitational energy as they merge than regular stars emit in the form of UV, IR, and visible light over their entire lifetimes of billions of years.) Eventually their event horizons will touch, and the system emits a lot more gravitational waves in a phase known as “ring-down,” as the lumpy, uneven merged mass becomes a smooth, perfectly symmetrical black hole. [Read more…]
(OK, it doesn’t scan. So sue me.) Quantum entanglement is a challenging topic, and one which has tripped up a lot of people (including many physicists!) over the decades. In brief, entanglement involves two (or more) particles constituting a single system: measurement on one particle instantly determines the result of similar measurements on the second, no matter how far they are separated in space. While no information is transferred in this process, it’s still at odds with our everyday experience with how the world should work. I updated my earlier explanation of entanglement, which hopefully can help clear up some of the confusion.
Recent work either assumes entanglement is real and probes some of the more interesting implications, or tests some mathematical relations known as Bell’s inequalities. The latter are aimed at quantifying the difference between the predictions of quantum physics and certain alternative models. In that spirit, a group of researchers proposed using light from quasars to randomize the measurement apparatus in entanglement experiments, to eliminate the tiny possibility of a weird loophole in quantum theory.
If a detector has some correlation with the hidden variables of the particles being measured, then the two detectors don’t act independently. That’s true even if only a very tiny amount of information is exchanged less than a millisecond before measurements take place. The interaction would create the illusion that the particles are entangled in a quantum sense, when in fact they are influencing the detectors, which in turn dictate what measurements are being taken. This is known as the “detector settings independence” loophole—or somewhat facetiously as the “free will” loophole, since it implies the human experimenter has little or no choice over the detector settings. [Read more…]
Final note: this is probably the first paper I’ve covered that involves both my undergraduate research focus (quantum measurement) and my PhD work (cosmology), albeit in a much different way than both.
Cassiopeia A (abbreviated Cas A) is a historical oddity. The supernova was relatively close to Earth—a mere 11,000 light-years distant—and should have been visible around CE 1671, yet no astronomers of any culture recorded it. That’s in stark contrast to famous earlier explosions: Tycho’s supernova, Kepler’s supernova, and of course the supernova that made the Crab Nebula. This mysterious absence has led some astronomers to speculate that some unknown mechanism diffused the energy from the explosion, making the supernova far less bright than expected. [Read more…]
“Dark energy” is one of the more unfortunate names in science. You’d think it has something to do with dark matter (itself a misnomer), but it has the opposite effect: while dark matter drives the clumping-up of material that makes galaxies, dark energy pushes the expansion of the Universe to greater and greater rates. Though we should hate on the term “dark energy”, we should respect Michael Turner, the excellent cosmologist who coined the phrase. He is also my academic “grand-advisor”: he supervised Arthur Kosowsky’s PhD, and Arthur in turn supervised mine.
And of course, I worked on dark energy as a major part of my PhD research. In my latest piece for Slate, I describe a bit of my dysfunctional relationship with cosmic acceleration, and why after 16 years dark energy is still a matter of frustration for many of us.
Because dark energy doesn’t correspond easily to anything in the standard toolkit of physics, researchers have been free to be creative. The result is a wealth of ideas, some that are potentially interesting and others that are frankly nuts. Some string theorists propose that our observable universe is the result of a vast set of parallel universes, each with a different, random amount of dark energy. Other physicists think our cosmos is interacting with a parallel universe, and the force between the two drives cosmic acceleration. Still others suspect that dark energy is a sign that our currently accepted theory of gravity—Einstein’s general theory of relativity—is incomplete for the largest distances. [Read more…]
For the upcoming ScienceOnline 2014 meeting, I’m leading a session titled “Reporting Incremental Science in a World that wants Big Results“. It’s an important topic. We who communicate science to the general public have to evaluate stories to see if they’re worth covering, then translate them in such a way that conveys their significance without hyping them (ideally at least). That’s challenging to do on deadline, and we’re not always or maybe even usually experts on the topics we report. I know a fair amount about cosmology and gravitational physics, but very little about galactic astronomy or planetary science — yet I must write about them, because it’s my job.
So Stephen Hawking’s recent talk on black holes is an interesting case study. I won’t rehash the whole story here, but I wrote not one but two articles on the subject yesterday. Article 1 was in Slate:
Hawking’s own thinking about black holes has changed over time. That’s no criticism: Evidence in science often requires us to reassess our thinking. In this case, Hawking originally argued that black holes violated quantum mechanics by destroying information, then backed off from that assertion based on ideas derived from string theory (namely, the holographic principle). Not everyone agrees with his change of heart, though: The more recent model he used doesn’t correspond directly to our reality, and it may not have an analog for the universe we inhabit. The new talk suggests he has now moved on from both earlier ideas. That’s partly what raises doubts in my mind about the “no event horizons” proposal in the online summary. Is this based on our cosmos or yet another imaginary one of the sort physicists are fond of inventing to guide their thinking? In my reading, it’s hard to tell, and in the absence of a full explanation we are free to project our own feelings about both Hawking and his science onto the few details available. [Read more…]
Article 2 was a follow-up on my own blog:
But at the same time, we have to admit that nobody—not Nature News, not Slate.com—would have covered a paper this preliminary had Hawking’s name not been attached. Other people are working on the same problem (and drawing different conclusions!), but they can’t command space on major science news sites. So, by covering Hawking’s talk, we are back on that treacherous path: we’re showing how science works in a way, but we risk saying that a finding is important because somebody famous is behind it. [Read more…]
One new model, proposed by Anastasia Fialkov, Rennan Barkana, and Eli Visbal, suggests that energetic X-rays could have heated the primoridal gas to the point that reionization happened relatively rapidly. That’s in contrast with other hypotheses, which predict a more gradual reionization process. The X-rays in the new model were emitted by systems that include neutron stars or black holes. The nicest feature of the new proposal is that it predicts a unique pattern in light emission from the primordial gas, which could conceivably be measured by current radio telescopes. [Read more….]


New nanotechnology findings from physicists at the University of Maryland have moved us significantly closer to a "holy grail" of clean energy research – the efficient, cost effective generation of clean hydrogen fuel from sunlight.
The UMD team created a fundamentally new synthesis strategy for hybrid nanostructures that they and other scientists say make possible new nanostructures and nanotechnologies with huge potential applications ranging from clean energy and quantum computing advances to new sensor development.
The team demonstrated the power of their method by creating a photocatalyst that is almost 15 times more efficient in using solar energy to split water (H2O) into hydrogen and oxygen than conventional photocatalysts. Photocatalysts are substances that use light to boost chemical reactions. Chlorophyll is a natural photocatalyst used by plants.
"The ingenious nano-assemblies that Professor Ouyang and his collaborators have fabricated, which include the novel feature of a silver-gold particle that super-efficiently harvests light, bring us a giant step nearer to the so-far elusive goal of artificial photosynthesis: using sunlight to transform water and carbon dioxide into fuels and valuable chemicals," says Professor Martin Moskovits of the University of California at Santa Barbara, a recognized expert in this area of research and not affiliated with the paper.
Lighting the Way to Clean, Efficient Power
Hydrogen fuel cell has long been considered a tremendously promising, clean alternative to gasoline and other carbon based (fossil) fuels that are currently used for cars, electrical generation and most other energy applications. A fuel cell combines stored hydrogen gas with oxygen from the air to produce electricity that can power vehicles, homes and businesses. The only byproduct of hydrogen fuel cells is water. Combustion of gasoline and other carbon-based fuels emit pollutants, including carbon dioxide, the principle greenhouse gas contributing to climate change.
It's expected that in 2015, American consumers will finally be able to purchase fuel cell cars from Toyota and other manufacturers. Although these will be zero-emissions vehicles, most of the hydrogen fuel to power them currently is made from natural gas, a fossil fuel that contributes to climate change and increasingly is being produced by the controversial process known as fracking.
The cleanest way to produce hydrogen fuel is using solar energy to split water into hydrogen and oxygen. However, decades of research advances have not yielded photocatalytic methods with sufficient energy efficiency to be cost effective for use in large scale water splitting applications. Efficient creation of hydrogen fuel from sunlight is also critical to development of large scale solar energy plants because hydrogen fuel is an ideal way to store for later use, the energy generated by such facilities.
The UMD team's work advances the efficiency of photocatalysts and lays the foundation for much larger future advances by more fully realizing a light-generated nanoparticle effect first used by ancient Romans to create glass that changes color based on light. This effect, known as surface plasmon resonance, involves the generation of high energy electrons using light.
UMD team leader Min Ouyang, an associate professor in the department of physics and the Maryland NanoCenter., explains that plasmon resonance is the generation of a collective oscillation of low energy electrons by light. The light energy stored in such a "plasmonic oscillator" then can be converted to energetic carriers (i.e., "hot" electrons) for use in photocatalysis and many other applications.
"Using our new modular synthesis strategy, our UMD team created an optimally designed, plasmon-mediated photocatalytic nanostructure that is an almost 15 times more efficient than conventional photocatalysts," says Ouyang.
In studying this new photocatalyst, Min and his colleagues identified a previously unknown "hot plasmon electron-driven photocatalysis mechanism with an identified electron transfer pathway."
It is this new mechanism that makes possible the high efficiency of the UMD team's new photocatalyst. And it is a finding made possible by the precise materials control allowed by the team's new general synthesis method.
The UMD team says their findings hold great promise for future advances to make water splitting cost effective for large-scale use in creating hydrogen fuel. And the team's newly-discovered mechanism for creating hot (high energy) electrons should also be applicable to research involving other photo-excitation processes.
A Fundamental Nanotechnology Advance
The findings of Min and his colleagues were published recently in Nature Communications. Their primary discovery is a fundamentally new synthesis strategy for hybrid nanostructures that uses a connector, or "intermedium," nanoparticle to join multiple different nanoparticles into nanostructures that would be very difficult or perhaps even impossible to make with existing methods. The resultant mix and match modular component approach avoids the limitations in material choice and nanostructure size, shape and symmetry that are inherent in the crystalline growth (epitaxial) synthesis approaches currently used to build nanostructures.
"Our approach makes it possible to design and build higher order [more complex and materially varied] nanostructures with a specifically designed symmetry or shape, akin to the body's ability to make different protein oligomers each with a specific function determined by its specific composition and shape," says Ouyang. "Such a synthesis method is the dream of many scientists in our field and we expect researchers now will use our approach to fabricate a full class of new nanoscale hybrid structures," he says.
One of the many scientists excited about the new UMD method is the University of Delaware's Matt Doty, an associate professor of materials science and engineering, physics, and electrical and computer engineering and associate director of the UD Nanofabrication Facility. "The work of Weng and coauthors provides a powerful new tool for the 'quantum engineering' of complex nanostructures designed to implement novel electronic and optoelectronic functions. [Their] new approach makes it feasible for researchers to realize much more sophisticated nanostructure p designs than were previously possible." he says.
Support for this research was provided by the Office of Naval Research, the U.S. Department of Energy, the National Science Foundation, and the Research Corporation for Science Advancement.
Hierarchical synthesis of non-centrosymmetric hybrid nanostructures and enabled plasmon-driven photocatalysis, Lin Weng, HuiZhang, Alexander O. Govorov and Min Ouyang. Nature Communications; Article number: 4792; doi:10.1038/ncomms5792
September 15, 2014
Hydrogen & Solar Power Boosted by New Ability to Shape Nanostructures
Did You Know
UMD's Neutral Buoyancy Research Facility, which simulates weightlessness, is one of only two such facilities in the U.S.


Seth Lloyd, a professor of mechanical engineering at MIT, is among the pioneers of quantum computing: he proposed the first technologically feasible design for a quantum computer. If humans ever build a useful, general-purpose quantum computer, it will owe much to Lloyd. Earlier this year, he published a popular introduction to quantum theory and computing, titled Programming the Universe, which advanced the startling thesis that the universe is itself a quantum computer.
Technology Review:In your new book, you are admirably explicit: you write, “The Universe is indistinguishable from a quantum computer.” How can that be true?
Seth Lloyd: I know it sounds crazy. I feel apologetic when I say it. And people who have reviewed the book take it as a metaphor. But it’s factually the case. We couldn’t build quantum computers unless the universe were quantum and computing. We can build such machines because the universe is storing and processing information in the quantum realm. When we build quantum computers, we’re hijacking that underlying computation in order to make it do things we want: little and/or/not calculations. We’re hacking into the universe.
TR: Your critics can be forgiven for thinking you wrote metaphorically. In every era, scientists have likened the universe to the most complicated technology they knew. Newton thought the universe was like a clock.
SL: You could be more blunt: “Lloyd builds quantum computers; therefore, Lloyd thinks the universe is a quantum computer.” But I think that’s unfair.
TR: You famously believe in “it from bit”: that is, that information is a physical property of the universe, and that information generates more-complex information – and with it, all the phenomenal world.
SL: Imagine the electron, which an ordinary computer uses to store data. How can it have information associated with it? The electron can be either here or there. So it registers a bit of information, one of two possibilities: on or off.
TR: Sure, but how does the quantity of information increase?
SL: If you’re looking for places where the laws of physics allow for information to be injected into the universe, then you must look to quantum mechanics. Quantum mechanics has a process called “decoherence” – which takes place during measurement, for instance. A qubit [or quantum bit] that was, weirdly, both here and there is suddenly here or there. Information has been added to the universe.
TR: And why does the universe tend to complexity?
SL: This notion of the universe as a giant quantum computer gets you something new and important that you don’t get from the ordinary laws of physics. If you look back 13.8 billion years to the beginning of the universe, the Initial State was extremely simple, only requiring a few bits to describe. But I see on your table an intricate, very beautiful orchid – where the heck did all that complex information come from? The laws of physics are silent on this issue. They have no explanation. They do not encode some yearning for complexity.
TR: [Utterly bemused] Hmmm …
SL: Could the universe have arisen from total randomness? No. If we imagine that every elementary particle was a monkey typing since time began at the maximum speed allowed by the laws of physics, the longest stretch of Hamlet that could have been generated is something like “To be or not to be, that is the – .” But imagine monkeys typing at computers that recognize the random gibberish as a program. Algorithmic information theory shows that there are short, random-looking programs that can cause a computer to write down all the laws of physics. So for the universe to be complex, you need random generation, and you need something to process that information according to a few simple rules: in other words, a quantum computer.
TR: More practically: how far are we from widely used, commercial applications of quantum computing?
SL: Today, the largest general-purpose quantum computer is only a dozen bits. So we’re at least a decade or two away. But we’ve already built quantum computers that simulate other quantum systems: you could call them quantum analog computers. These little machines can perform computations that would require an ordinary computer larger than the universe.
TR: What’s the next big thing that needs to be done in quantum computing?
SL: From the techno-geek, experimentalist point of view, it’s the pacification of the microscopic, quantum world. It’s the Wild West down there.
TR: Programming the Universe concludes with a personal note. You describe how your friend Heinz Pagels, a renowned physicist, fell to his death while hiking with you in Colorado. You find some consolation in your theory of universal quantum computation: “But we have not entirely lost him. While he lived, Heinz programmed his own piece of the universe. The resulting computation unfolds in us and around us …”
SL: Well, it’s pretty poor consolation when someone you love is dead. But it’s a truer consolation than the idea that one day you might meet him in heaven.


A new technique for quantum computing could bust open our whole model of how time moves in the universe.
Here's what's long seemed to be true: Time works in one direction. The other direction? Not so much.
That's true in life. (Tuesday rolls into Wednesday, 2018 into 2019, youth into old age.) And it's true in a classical computer. What does that mean? It's much easier for a bit of software running on your laptop to predict how a complex system will move and develop in the future than it is to recreate its past. A property of the universe that theorists call "causal asymmetry" demands that it takes much more information — and much more complex calculations — to move in one direction through time than it does to move in the other. (Practically speaking, going forward in time is easier.)
This has real-life consequences. Meteorologists can do a reasonably good job of predicting whether it will rain in five days based on today's weather radar data. But ask the same meteorologists to figure out whether it rained five days ago using today's radar images? That's a much more challenging task, requiring a lot more data and much bigger computers. [The 18 Biggest Unsolved Mysteries in Physics]
Information theorists suspected for a long time that causal asymmetry might be a fundamental feature of the universe. As long ago as 1927, the physicist Arthur Eddington argued that this asymmetry is the reason we only move forward through time, and never backward. If you understand the universe as a giant computer constantly calculating its way through time, it's always easier — less resource-intensive — for things to flow forward (cause, then effect) than backward (effect, then cause). This idea is called the "arrow of time."
But a new paper, published July 18 in the journal Physical Review X, opens the door to the possibility that that arrow is an artifact of classical-style computation — something that's only appeared to us to be the case because of our limited tools.
A team of researchers found that in certain circumstances causal asymmetry disappears inside quantum computers, which calculate in an entirely different way— Unlike classical computers in which information is stored in one of two states (1 or 0), with quantum computers, information is stored in subatomic particles that follow some bizarre rules and so can each can be in more than one state at the same time. And, even more enticingly, their paper points the way toward future research that could show causal asymmetry doesn't really exist in the universe at all.
Very orderly and very random systems are easy to predict. (Think of a pendulum — ordered — or a cloud of gas filling a room — disordered.) In this paper, the researchers looked at physical systems that had a goldilocks' level of disorder and randomness — not too little, and not too much. (So, something like a developing weather system.) These are very difficult for computers to understand, said study co-author Jayne Thompson, a complexity theorist and physicist studying quantum information at the National University of Singapore. [Wacky Physics: The Coolest Little Particles in Nature]
Next, they tried to figure out those systems' pasts and futures using theoretical quantum computers (no physical computers involved). Not only did these models of quantum computers use less memory than the classical computer models, she said, they were able to run in either direction through time without using up extra memory. In other words, the quantum modelshad no causal asymmetry.
"While classically, it might be impossible for the process to go in one of the directions [through time]," Thompson told Live Science, "our results show that 'quantum mechanically,' the process can go in either direction using very little memory."
And if that's true inside a quantum computer, that's true in the universe, she said.
Quantum physics is the study of the strange probabilistic behaviors of very small particles — all the very small particles in the universe. And if quantum physics is true for all the pieces that make up the universe, it's true for the universe itself, even if some of its weirder effects aren't always obvious to us. So if a quantum computer can operate without causal asymmetry, then so can the universe.
Of course, seeing a series of proofs about how quantum computers will one day work isn't the same thing as seeing the effect in the real world. But we're still a long way off from quantum computers advanced enough to run the kind of models this paper describes, they said.
What's more, Thompson said, this research doesn't prove that there isn't any causal asymmetry anywhere in the universe. She and her colleagues showed there is no asymmetry in a handful of systems. But it's possible, she said, that there are some very bare-bones quantum models where some causal asymmetry emerges.
"I'm agnostic on that point," she said.
The next step for this research, she said, is to answer that question — to figure out whether causal asymmetry exists in any quantum models.
This paper doesn't prove that time doesn’t exist, or that we’ll one day be able to slip backward through it. But it does appear to show that one of the key building blocks of our understanding of time, cause and effect, doesn't always work in the way scientists have long assumed — and might not work that way at all. What that means for the shape of time, and for the rest of us, is still something of an open question.
The real practical benefit of this work, she said, is that way down the road quantum computers might be capable of easily running simulations of things (like the weather) in either direction through time, without serious difficulty. That would be a sea change from the current classical-modeling world.
Originally published on Live Science.


Computers learn to imagine the future
by Garrett Kenyon
In many ways, the human brain is still the best computer around. For one, it’s highly efficient. Our largest supercomputers require millions of watts, enough to power a small town, but the human brain uses approximately the same energy as a 20-watt bulb. While teenagers may seem to take forever to learn what their parents regard as basic life skills, humans and other animals are also capable of learning very quickly. Most of all, the brain is truly great at sorting through torrents of data to find the relevant information to act on.
At an early age, humans can reliably perform feats such as distinguishing an ostrich from a school bus, for instance – an achievement that seems simple, but illustrates the kind a task that even our most powerful computer vision systems can get wrong. We can also tell a moving car from the static background and predict where the car will be in the next half-second. Challenges like these, and far more complex ones, expose the limitations in our ability to make computers think like people do. But recent research at Los Alamos National Laboratory is changing all that.
Brain neuroscientists and computer scientists call this field neuromimetic computing – building computers inspired by how the cerebral cortex works. The cerebral cortex relies on billions of small biological “processors” called neurons. They store and process information in densely interconnected circuits called neural networks. In Los Alamos, researchers are simulating biological neural networks on supercomputers, enabling machines to learn about their surroundings, interpret data and make predictions much the way humans do.
This kind of machine learning is easy to grasp in principle, but hard to implement in a computer. Teaching neuromimetic machines to take on huge tasks like predicting weather and simulating nuclear physics is an enterprise requiring the latest in high-performance computing resources.
Los Alamos has developed codes that run efficiently on supercomputers with millions of processing cores to crunch vast amounts of data and perform a mind-boggling number of calculations (over 10 quadrillion!) every second. Until recently, however, researchers attempting to simulate neural processing at anything close to the scale and complexity of the brain’s cortical circuits have been stymied by limitations on computer memory and computational power.
All that has changed with the new Trinity supercomputer at Los Alamos, which became fully operational in mid-2017. The fastest computer in the United States, Trinity has unique capabilities designed for the National Nuclear Security Administration’s stockpile stewardship mission, which includes highly complex nuclear simulations in the absence of testing nuclear weapons. All this capability means Trinity allows a fundamentally different approach to large-scale cortical simulations, enabling an unprecedented leap in the ability to model neural processing.
To test that capability on a limited-scale problem, computer scientists and neuroscientists at Los Alamos created a “sparse prediction machine” that executes a neural network on Trinity. A sparse prediction machine is designed to work like the brain: researchers expose it to data – in this case, thousands of video clips, each depicting a particular object, such as a horse running across a field or a car driving down a road.
Cognitive psychologists tell us that by the age of six to nine months, human infants can distinguish objects from background. Apparently, human infants learn about the visual world by training their neural networks on what they see while being toted around by their parents, well before the child can walk or talk.
Similarly, the neurons in a sparse prediction machine learn about the visual world simply by watching thousands of video sequences without using any of the associated human-provided labels – a major difference from other machine-learning approaches. A sparse prediction machine is simply exposed to a wide variety of video clips much the way a child accumulates visual experience.
When the sparse prediction machine on Trinity was exposed to thousands of eight-frame video sequences, each neuron eventually learned to represent a particular visual pattern. Whereas a human infant can have only a single visual experience at any given moment, the scale of Trinity meant it could train on 400 video clips simultaneously, greatly accelerating the learning process. The sparse prediction machine then uses the representations learned by the individual neurons, while at the same time developing the ability to predict the eighth frame from the preceding seven frames, for example, predicting how a car moves against a static background.
The Los Alamos sparse prediction machine consists of two neural networks executed in parallel, one called the Oracle, which can see the future, and the other called the Muggle, which learns to imitate the Oracle’s representations of future video frames it can’t see directly. With Trinity’s power, the Los Alamos team more accurately simulates the way a brain handles information by using only the fewest neurons at any given moment to explain the information at hand. That’s the “sparse” part, and it makes the brain very efficient and very powerful at making inferences about the world – and, hopefully, a computer more efficient and powerful, too.
After being trained in this way, the sparse prediction machine was able to create a new video frame that would naturally follow from the previous, real-world video frames. It saw seven video frames and predicted the eighth. In one example, it was able to continue the motion of car against a static background. The computer could imagine the future.
This ability to predict video frames based on machine learning is a meaningful achievement in neuromimetic computing, but the field still has a long way to go. As one of the principal scientific grand challenges of this century, understanding the computational capability of the human brain will transform such wide-ranging research and practical applications as weather forecasting and fusion energy research, cancer diagnosis and the advanced numerical simulations that support the stockpile stewardship program in lieu of real-world testing.
To support all those efforts, Los Alamos will continue experimenting with sparse prediction machines in neuromorphic computing, learning more about both the brain and computing, along with as-yet undiscovered applications on the wide, largely unexplored frontiers of quantum computing. We can’t predict where that exploration will lead, but like that made-up eighth video frame of the car, it’s bound to be the logical next step.
Garrett Kenyon is a computer scientist specializing in neurally inspired computing in the Information Sciences group at Los Alamos National Laboratory, where he studies the brain and models of neural networks on the Lab’s high-performance computers. Other members of the sparse prediction machine project were Boram Yoon of the Applied Computer Science group and Peter Schultz of the New Mexico Consortium.
This story first appeared in Discover.


Nobody has built a quantum computer much more powerful than a pocket calculator but that hasn’t stopped people worrying about the implications of the post-quantum computing world. Most worried are the people who rely on cryptographic codes to protect sensitive information. When the first decent-sized quantum computer is switched on, previously secure codes such as the commonly used RSA algorithm will become instantly breakable.
Which is why cryptographers are scurrying about looking for codes that will be secure in the post-quantum world. Today, Hang Dinh at the University of Connecticut and a couple of pals show that cryptographers have been staring at one all along. They say that a little-used code developed by the CalTech mathematician Robert McEliece in 1978 can resist all known attacks by quantum computers.
First, let’s a make a distinction between symmetric and asymmetric codes. Symmetric codes use identical keys for encrypting and decrypting a message. Quantum computers can dramatically speed up an attack against these kinds of codes. However, symmetric codes have some protection. Doubling the size of the key counteracts this speed up. So it is possible for code makers to stay ahead of the breakers, at least in theory. (Although in practice, the safe money would be on the predator in this cat and mouse game. )
Asymmetric codes use different keys for encrypting and decrypting messages. In so-called public key encryption systems such as the popular RSA algorithm, a public key is available to anyone who can use it to encrypt a message. But only those with a private key can decrypt the messages and this, of course, is kept secret.
The security of these systems relies on so-called trap door functions: mathematical steps that are easy to make in one direction but hard to do in the other. The most famous example is multiplication. It is easy to multiply two numbers together to get a third but hard to start with the third number and work out which two generated it, a process called factorisation.
But in 1994, the mathematician Peter Shor dreamt up a quantum algorithm that could factorise much faster than any classical counterpart. Such an algorithm running on a decent quantum computer could break all known public key encryption systems like a 4-year old running amok in Legoland.
Here’s a sense of how it works. The problem of factorisation is to find a number that divides exactly into another. Mathematicians do this using the idea of periodicity: a mathematical object with exactly the right periodicity should divide the number exactly, any others will not.
One way to study periodicity in the classical world is to use fourier analysis, which can break down a signal into its component waves. The quantum analogue to this is the quantum fourier sampling and Shor’s triumph was to find a way to use this idea to find the periodicity of the mathematical object that reveals the factors.
Thanks to Shor, any code that relies on this kind of asymmetry (ie almost all popular public key encryption systems) can be cracked using a quantum fourier attack.
The McEliese cryptosystem is different. It too is asymmetric but its security is based not on factorisation but on a version of a conundrum that mathematicians call the hidden supgroup problem. What Dinh and buddies have shown is that this problem cannot be solved using quantum fourier analysis. In other words it is immune to attack by Shor’s algorithm. In fact, it is immune to any attack based on quantum fourier sampling.
That’s a big deal. It means that anything encoded in this way will be safe when the next generation of quantum computers start chomping away at the more conventional public key cryptosystems. One such system is Entropy, a peer-to-peer communications network designed to resist censorship based on the McEliese cryptosystem.
But Entropy is little used and there are good reasons why others have resisted the McEliese encryption system. The main problem is that both the public and private keys are somewhat unwieldy: a standard public key is a large matrix described by no fewer than 2^19 bits.
That may seem less of a problem now. It’s possible that the McEleise system will suddenly become the focus of much more attention more than 30 years after its invention.
However, it’s worth pointing out that while the new work guanratees safety against all known quantum attacks, it does nothing of the sort for future quantum attacks. It’s perfectly possible that somebody will develop a quantum algorithm that will tear it apart as easily as Shor’s can with the RSA algorithm. “Our results do not rule out other quantum (or classical) attacks,” says Dinh and co.
So s more likely scenario for future research is that crytpographers will renew their efforts in one of the several other directions that are looking fruitful, such as lattice-based algorithms and multivariate cryptography.
Either way, expect to hear a lot more about post quantum cryptography–provided the powers that be allow.
Ref: arxiv.org/abs/1008.2390 : The McEliece Cryptosystem Resists Quantum Fourier Sampling Attacks


1. Five Generations of Computers
- The number of instructions or the amount of data a computer can store in its memory is measured in bytes.
- It is a worldwide system of computer networks – a network of networks in which users at any one computer can get information from any other computer(if they have permission).
How does the Internet work?
Administration of Internet
- Internet Corporation for Assigned Names and Numbers(ICANN), a US non-profit organization administers the allocation of domain names and IP addresses.
- Internet Society(ISOC) is responsible for developing internet technical standards.
- A computer or an array of computers that act as one collective machine capable of processing enormous amounts of data.
- They work at very high speeds and perform complex jobs such as nuclear research or forecasting weather patterns.
- It channels all its power into executing a few programs as fast as possible rather than executing many programs concurrently.
- It uses parallel processing instead of the serial processing in the case of an ordinary computer
Supercomputers in India
|1||SahasraT||Indian Institute of Science, Bengaluru|
|2||Aaditya||Indian Institute of Tropical Meteorology, Pune|
|3||TIFR-Cray XC30||Tata Institute of Fundamental Research, Mumbai|
|4||HP Apollo 6000||Indian Institute of Technology, Delhi|
|5||PARAM Yuva-2||Centre for Development of Advanced Computing(C-DAC), Pune|
|6||PARAM ISHAN||Indian Institute of Technology, Guwahati|
Supercomputers of the World
5. Quantum Computing
- Quantum computing studies computation systems that make direct use of quantum-mechanical phenomena to perform operations on data.
- Classical computers encode information in bits. Each bit can take the value of 1 or 0. These 1s and 0s act as on/off switches that ultimately drive computer functions. Quantum computers, on the other hand, are based on qubits, which operate according to two key principles of quantum physics: superposition and entanglement.
- Superposition means that each qubit can represent both a 1 and a 0 at the same time.
- Entanglement means that qubits in a superposition can be correlated with each other i.e. the state of one (whether it is a 1 or a 0) can depend on the state of another.
6. Types of Cybercrimes
7. Cloud Computing
- It is an Internet-based computing solution where shared resources are provided like electricity distributed on the electrical grid
- Computers in the cloud are configured to work together and the various applications use the collective computing power as if they are running on a single system.
IT PROJECTS IN INDIA
1. National Supercomputer Mission(NSM)
- The Mission envisages empowering our national academic and R&D institutions spread over the country by installing a vast supercomputing grid comprising a cluster of more than 70 high-performance computing facilities
- The Mission would be implemented and steered jointly by the Department of Science and Technology (DST) and Department of Electronics and Information Technology (DeitY) at an estimated cost of Rs.4500 crore over a period of seven years.
- To make India one of the world leaders in Supercomputing and to enhance India’s capability in solving grand challenge problems of national and global relevance
- To empower our scientists and researchers with state-of-the-art supercomputing facilities and enable them to carry out cutting-edge research in their respective domains
- To minimize redundancies and duplication of efforts, and optimize investments in supercomputing
- To attain global competitiveness and ensure self-reliance in the strategic area of supercomputing technology
- Climate Modelling
- Weather Prediction
- Aerospace Engineering
- Computational Biology
- Molecular Dynamics
- Atomic Energy Simulations
- National Security/ Defence Applications
- Seismic Analysis
- Disaster Simulations and Management
- Computational Chemistry
- Computational Material Science and Nanomaterials
- Discoveries beyond Earth (Astrophysics)
- Large Complex Systems Simulations and Cyber Physical Systems
- Big Data Analytics
- Information repositories/ Government Information Systems
2. National e-Governance Plan
- An initiative of the Government of India to make all Government services available to the citizens of India via electronic media
- It was formulated by the Department of Electronics and Information Technology (DeitY) and Department of Administrative Reforms & Public Grievances (DAR&PG) to reduce government costs and allow citizen access to government services through Common Service Centres (CSC).
- It comprises of 27 Mission Mode Projects(MMP) and 10 program support components.
3. e-Kranti/National e-Governance Plan 2.0
- It is an important pillar of the Digital India programme.
- The vision of e-Kranti is “Transforming e-Governance for Transforming Governance”.
- The Mission of e-Kranti is to ensure a Government wide transformation by delivering all Government services electronically to citizens through integrated and interoperable systems via multiple modes, while ensuring efficiency, transparency and reliability of such services at affordable costs.
4. National Knowledge Network(NKN)
- It aims to bridge the gap between rural education, urban education, and International education by interconnecting all universities, government as well as private institutions of higher learning and research with a high-speed data communication network in the country.


Special Relativity. It’s been the bane of space explorers, futurists and science fiction authors since Albert Einstein first proposed it in 1905. For those of us who dream of humans one-day becoming an interstellar species, this scientific fact is like a wet blanket.
Luckily, there are a few theoretical concepts that have been proposed that indicate that Faster-Than-Light (FTL) travel might still be possible someday.
A popular example is the idea of a wormhole: a speculative structure that links two distant points in space time that would enable interstellar space travel.
Recently, a team of Ivy League scientists conducted a study that indicated how “traversable wormholes” could actually be a reality. The bad news is that their results indicate that these wormholes aren’t exactly shortcuts, and could be the cosmic equivalent of “taking the long way”!
Originally, the theory of wormholes was proposed as a possible solution to the field equations of Einstein’s Theory of General Relativity (GR).
Shortly after Einstein published the theory in 1915, German physicists Karl Schwarzschild found a possible solution that not only predicted the existence of black holes, but of corridors connecting them.
Unfortunately, Schwarzschild found that any wormhole connecting two black holes would collapse too quickly for anything to cross from one end to the other.
The only way they could be traversable would be if they were stabilized by the existence of exotic matter with negative energy density. Daniel Jafferis, the Thomas D. Cabot Associate Professor of Physics at Harvard University, had a different take.
As he described his analysis during the 2019 April meeting of the American Physical Society in Denver, Colorado:
“The prospect of traversable wormhole configurations has long been a source of fascination. I will describe the first examples that are consistent in a UV completable theory of gravity, involving no exotic matter. The configuration involves a direct connection between the two ends of the wormhole. I will also discuss its implications for quantum information in gravity, the black hole information paradox, and its relation to quantum teleportation.”
For the purposes of this study, Jafferis examined the work performed by Einstein and Nathan Rosen in 1935. Looking to expand upon the work of Schwarszchild and other scientists seeking solutions to GR, they proposed the possible existence of “bridges” between two distant points in space time (known as “Einstein–Rosen bridges” or “wormholes”) that could theoretically allow for matter and objects to pass between them.
By 2013, this theory was used by theoretical physicists Leonard Susskind and Juan Maldacena as a possible resolution for GR and “quantum entanglement“.
Known as the ER=EPR conjecture, this theory suggests that wormholes are why an elementary particles state can become entangled with that of a partner, even if they are separated by billions of light years.
It was from here that Jafferis developed his theory, postulating that wormholes could actually be traversed by light particles (aka. photons). To test this, Jafferis conducted an analysis with the assistance with Ping Gao and Aron Wall (a Harvard graduate student and Stanford University research scientist, respectively).
What they found was that while it is theoretically possible fir light to traverse a wormhole, they are not exactly the cosmic shortcut we were all hoping for them to be.
As Jafferis explained in an AIP press statement, “It takes longer to get through these wormholes than to go directly, so they are not very useful for space travel.”
Basically, the results of their analysis showed that a direct connection between black holes is shorter than that of a wormhole connection.
While this certainly sounds like bad news to people who are excited by the prospect of interstellar (and intergalactic) travel someday, the good news is that this theory provides some new insight into the realm of quantum mechanics.
“The real import of this work is in its relation to the black hole information problem and the connections between gravity and quantum mechanics,” said Jafferis.
The “problem” he refers to is known as the Black Hole Information Paradox, something that astrophysicists have been struggling with since 1975, when Stephen Hawking discovered that black holes have a temperature and slowly leak radiation (aka. Hawking radiation).
This paradox relates to how black holes are able to preserve any information that passes into them. Even though any matter accreted onto their surface would compressed to the point of singularity, the matter’s quantum state at the time of its compression would be preserved thanks to time dilation (it becomes frozen in time).
But if black holes lose mass in the form of radiation and eventually evaporate, this information will eventually be lost. By developing a theory through which light can travel through a black hole, this study could represent a means of resolving this paradox.
Rather than radiation from black holes representing a loss of mass-energy, it could be that Hawking Radiation is actually coming from another region of space time.
It may also help scientists who are attempting to develop a theory that unifies gravity with quantum mechanics (aka. quantum gravity, or a “Theory of Everything”).
This is due to the fact that Jafferis used quantum field theory tools to postulate the existence of traversable black holes, thus doing away with the need for exotic particles and negative mass (which appear inconsistent with quantum gravity).
As Jafferis explained:
“It gives a causal probe of regions that would otherwise have been behind a horizon, a window to the experience of an observer inside a spacetime, that is accessible from the outside. I think it will teach us deep things about the gauge/gravity correspondence, quantum gravity, and even perhaps a new way to formulate quantum mechanics.”
As always, breakthroughs in theoretical physics can be a two-edged sword, giving with one hand and taking away with the other.
So while this study may have thrown more cold water on the dream of FTL travel, it could very well help us unlock some of the Universe’s deeper mysteries.
Who knows? Maybe some of that knowledge will allow us to find a way around this stumbling block known as Special Relativity!


Blockchain cryptography is at the very heart of what keeps cryptocurrencies and other digital assets safe from hackers and other cyber-attacks. Public key encryption provides each user with a public and private key, which are extremely difficult to guess through brute-force attacks, at least using today’s computing resources. However, developments in quantum computing will make brute-force attacks far easier in the future.
Here, we will take an in-depth look at how a quantum computer could successfully attack existing blockchain cryptography. Considering some projects are already making headway, we’ll also look at how blockchains can be secured against quantum machines.
How Can a Quantum Computer Break Blockchain Cryptography?
Blockchain uses public key encryption, where each user is given a public and private key to secure their digital assets. These keys are generated using a cryptographic method called prime number factorization, which is the backbone of all modern cryptography.
The mathematical principle behind prime number factorization is that any number, no matter how large, can be produced by multiplying prime numbers. It’s relatively easy to produce any number using prime numbers. However, it’s vastly more difficult to reverse the process and work out which prime numbers were multiplied to produce a particular value once the numbers become large. This reversal is called prime number factorization.
Key Encryption and Prime Number Factorization
Blockchain cryptography relies on prime number factorization for linking the public and private key. The prime number factors of the public key are what form the private key. Because today’s computers, even using the advantages of networks, cannot factor the private key, our digital assets can remain secure against attackers.
For example, in 2009, researchers used a network of computers to try and factor a number 232 digits long. It took the equivalent of 2,000 years for a single computer launching such an attack. Computer security specialists nevertheless thought this was an unacceptable risk. Thus, current encryption standards use prime numbers that are 309 digits long.
Quantum computers are capable of performing many more thousands of calculations per second than today’s computers, even accounting for the network effect. Quantum machines are still in a relatively early stage of development. However, its thought that over the next decade, quantum computers will become sufficiently powerful to break existing blockchain cryptography.
Therefore, one of the challenges for the blockchain developer community is ensuring that existing blockchains are resilient enough to withstand attacks from tomorrows quantum computers.
The Specific Threat of Quantum Computing to Blockchain
Because all current cybersecurity relies on encryption using prime number factorization, the advent of quantum computing isn’t just a threat to blockchain encryption. It has implications across the whole of the internet and all connected computers. However, centralized entities control pretty much all websites and networks outside of blockchain. Therefore, it isn’t a significant problem to implement an upgrade across the network or website.
On the other hand, decentralized networks control blockchains. Decentralization means that every computer on the network has to agree to upgrade at the same time for the upgrade to become active. Not only that but because the quantum threat to blockchain cryptography is specific to the public and private keys, then all wallets will need to upgrade to the new software to ensure quantum resistance.
The Worst Bear Market in Future History?
Satoshi Nakamoto is thought to own around a million Bitcoins, not to mention his fortunes from the many Bitcoin hard forks over the years. If the Bitcoin network pushes through an upgrade to ensure quantum resistance, and Satoshi doesn’t upgrade his BTC wallets to the new protocol, his wallets become vulnerable to the quantum threat. So, even if all other holders of BTC upgrade their wallets, a quantum attack could still see Satoshi’s one million BTC stolen and sold off onto the market in one fell swoop.
Even worse though, it’s not just whales that are at risk. After all, anyone consciously sitting on crypto-wealth will be eager to upgrade as soon as possible. However, it’s thought that around four million BTC are lost due to their users losing their private keys. Someone stealing and then selling this volume of crypto in a short space of time could have a devastating effect on the markets.
Therefore, developing quantum resistant blockchain cryptography is not necessarily the problem. The implementation across thousands or even millions of wallets becomes the real challenge.
Securing Blockchain Cryptography against the Quantum Threat
Most people still think the quantum threat is several years away, perhaps even more than a decade. However, the above scenario illustrates why it’s vital that developments in blockchain cryptography already start to consider quantum resistance as a precautionary measure.
One-time Signatures with Cryptographic Hashing
Quantum Resistant Ledger (QRL) is not one of the biggest blockchain projects out there. However, its sole use case is in ensuring quantum resistant blockchain cryptography. The project works from a principle that prediction timelines about advancements in quantum technology may be fallible. For this reason, we should already start preparing for the eventuality that quantum developments may arrive sooner than we think.
The QRL blockchain completely does away with prime number factorization for blockchain cryptography. Instead, it makes use of Extended Merkle Signature Schemes (XMSS), which is a complex model. However, in principle, it involves generating key pairs using cryptographic hashing. This is the same concept as hashing a block in a blockchain to protect the contents.
These key pairs are for one-time use only and are aggregated together using a Merkle tree. By using hash-based blockchain cryptography rather than prime number factorization, the signatures become far more complicated to brute-force. This hashing makes them more resistant to quantum attacks.
The Nexus blockchain uses a similar mechanism when handling transactions, called signature chains. Nexus hashes the public key so although it’s visible on the blockchain, it isn’t readable.
The public key hash then generates a one-time private key as an authorization signature for the transaction. Afterwards, the wallet automatically creates a new public/private key pair for the next transaction, along with a sending or receiving address for the current transaction. In this way, the transaction keys are separate from the address, making it more secure against quantum attacks.
Despite that the threat may still be some way off, blockchain cryptography faces some unique challenges from quantum computing. The developer community is very much aware of the threat. Hence, the introduction of innovative solutions such as the ones listed here by QRL and Nexus. Implementing these kinds of solutions will prove to the most challenging part of quantum-proofing the major blockchains such as Bitcoin and Ethereum.
However, the blockchain developer community is nothing if not creative. It will be fascinating to see some of the ideas coming out of the quantum challenge. Furthermore, find out which of those ideas will ultimately evolve into the most resilient solutions.
Featured image courtesy of Pixabay
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What is Artificial Leaf?
- The artificial leaf is a silicon-based technology which produces hydrogen energy (a clean fuel) by utilizing sunlight to split water molecules into hydrogen and oxygen.
- It is designed to mimic photosynthesis, the natural mechanism by which plants utilize sunlight to produce carbohydrates and store energy. But Artificial Leaf is designed to be far more efficient in photosynthesis than plants. Hence it is like a photosynthesis machine.
- The invention of Artificial Leaf is credited to an American Chemist named Daniel G. Nocera and his colleagues in 2011.
- It is an amalgamation of physics, engineering, and biology.
- It is a clean way of producing energy that will someday become the main weapon in the fight against climate change and also as an important power source, particularly in developing nations like India.
How is it different from the natural leaf?
A plant utilizes just 1% of the energy it gets from the sun for converting CO2 and water into carbohydrates or glucose, whereas the artificial leaf can utilize 20% of the energy it receives from the sun to produce Hydrogen.
What is the need for Artificial Leaf?
- The primary application of artificial leaf is the production of clean energy that is Hydrogen. Hydrogen is being used in a variety of different sustainable technologies. But conventional techniques of capturing Hydrogen such as steam reforming and hydraulic fracturing (or fracking) tend to release potentially harmful chemicals into the environment which is not desirable for sustainable development.
- This could solve the major challenge of solar and wind power plants in producing and storing energy when the sun is not shining and the air is still and also the associated costs.
- Around 3 billion people are living in regions that do not have any access to electricity. Hence, there is a need for a simple device like Artificial Leaf that is compatible with local conditions.
- The artificial leaf is highly relevant for countries like India as it is blessed with immense sunlight throughout the year but not adequately translated into energy.
How does it work?
- Artificial Leaf system consists of semiconductors piled up in a way to simulate the natural leaf system. When sunlight strikes the semiconductors, electrons transfer in one direction, generating electric current. The current instantaneously splits water into hydrogen and oxygen.
- The resultant hydrogen gas can then be used for the immediate production of electricity or can be stored for later usage.
- Semiconductors are coated in chemical catalysts such as platinum to speed up the water-splitting reaction.
- The main by-product of this process is water, which is why researchers believe that artificial leaf is the cleanest source of energy generation.
What are the applications of Artificial Leaf?
- It has the potential to transform the transportation sector in a big way by making even the long-distance air travel affordable and environmentally sustainable. It makes the way for the eco-friendly cars to become a common mode of transport in the future since artificial leafs can produce liquid hydrocarbon fuels that could be burned in modern car engines without any major alterations in design or technology.
- Artificial leaf makes hydrogen a renewable source of energy as sunlight and water are abundant on Earth.
- With artificial leaf, people can produce their own electricity and can live far away from the electricity grid, as hydrogen energy can be produced anywhere at any time. It has to be noted that, an estimated one to three bottles of water is enough to power a single household in less-developed regions of the world.
- Researchers also claim that, by using the resultant hydrogen from artificial leaf we can also produce various products such as fertilizers, plastics and drugs by means of using microbes or bacterium.
- It helps mitigate global warming and climate change by reducing carbon footprint, since it absorbs CO2 from the air to generate hydrogen and releasing more oxygen in the process. It is also 100% more efficient in absorbing CO2 from air than natural plant leaf.
- Artifical leaves also help in making the thermal power plants more efficient, because thermal plants produce more CO2 which can be turned into energy to further fuel the power plant. In short, it removes CO2 and at the same time the leaf energy power up the thermal power stations.
- It provides environmental friendly and affordable storage of energy when compared to other renewables such as solar and wind power plants.
What are the challenges in the commercialization of Artificial Leaf?
- Efficiency and cost-effectiveness are the two important factors that affect the commercialization process. In initial research, artificial leaf captured only 4.7% of solar energy for producing hydrogen. Artificial leaf technology remains potentially expensive due to lack of cheap and abundant materials in the production process.
- Concerns about the safety of hydrogen fuel storage also restrict the practical implementation.
What are the opportunities for the successful commercialization?
- Devices developed since the initial research achieved efficiencies as higher as 10%.
- Researchers are also working on the cheaper version of catalysts and processes to make the technology cheaper for the large-scale production.
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What is the recent Indian research on the Artificial leaf about?
- In 2017, Council of Scientific and Industrial Research (CSIR) scientists of India developed an artificial leaf device with improved efficiency. They used gold nanoparticles, titanium dioxide, and quantum dots to make the process efficient.
- Quantum dots are semiconductor nanocrystals with distinct properties that depend on the size of the dots. It does not need any external voltage and performs better than existing solar cells. Apart from solar cells quantum dots also have applications in transistors, LEDs, medical imaging and quantum computing.
We are already experiencing the harmful effects of global warming such as changing climate and rising water levels to such a degree that would only become severe if we keep on adding more CO2 into the atmosphere.The artificial leaf is a big leap forward in producing environmentally sustainable energy thereby mitigating the harmful effects of climate change as it absorbs the CO2 from the air directly to produce energy. Hence policymakers should actively donate researchers with funds and make relevant policies in order to achieve the desired scale in the artificial leaf production.
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(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.
Learn more about the UTSA Department of Electrical and Computer Engineering.
Celebrate UTSA’s 50th Anniversary and share social media posts about the 50th using the hashtag #UTSA50.
UTSA will offer science, engineering, architecture, sports, music, writing and language and culture camps for kids, teens and adults. Register now.Various locations, Main and Downtown Campuses
The weeklong academy will provide educators with resources, literature, information, and best practices on bringing Mexican American Studies into their classrooms. The materials provided are aligned to the social studies Texas Essential Knowledge and Skills objectives for middle and high school.UTSA Institute of Texan Cultures, Hemisfair Campus
Lecture presented by Dr. Nelson Flores, associate professor at the University of Pennsylvania. Free and open to the public.Durango Building, La Villita Room (DBB 1.116), Downtown Campus
Are you transferring to UTSA? Take this opportunity to drop off any documents and complete your application for admission to UTSA! During this time you will have the opportunity to drive up, meet a staff member and submit your transcripts.Frio Street Building Breezeway, Downtown Campus
Are you transferring to UTSA? Take this opportunity to drop off any documents and complete your application for admission to UTSA! During this time you will have the opportunity to drive up, meet a staff member and submit your transcripts.Welcome Center Breezeway, Bauerle Rd. Garage, Main Campus
Future Roadrunners and families prepare for everything they need to know before the fall semester.Various locations, Main and Downtown Campuses
Willie Hale, UTSA assistant professor of psychology, will discuss how advances in statistical modeling can help us understand the ways in which a variety of risk and protective factors influence the onset, maintenance, and treatment of PTSD.Blue Star Contemporary, 116 Blue Star, San Antonio
Presented by Dr. Marcia Farr, Professor Emerita, The Ohio State University. Free and open to the public.Durango Building, El Mercado Room (DBB 1.208), Downtown Campue
The University of Texas at San Antonio is dedicated to the advancement of knowledge through research and discovery, teaching and learning, community engagement and public service. As an institution of access and excellence, UTSA embraces multicultural traditions and serves as a center for intellectual and creative resources as well as a catalyst for socioeconomic development and the commercialization of intellectual property - for Texas, the nation and the world.
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