Category Archives: Quantum Computing

The pace of improvement in quantum computing mirrors the fast advances made in AI and machine learning. It is normal to ask whether quantum technologies could boost learning algorithms: this field of inquiry is called quantum-improved machine learning.

Quantum computers are gadgets that work dependent on principles from quantum physics. The computers that we at present use are constructed utilizing transistors and the information is stored as double 0 and 1. Quantum computers are manufactured utilizing subatomic particles called quantum bits, qubits for short, which can be in numerous states simultaneously. The principal advantage of quantum computers is that they can perform exceptionally complex tasks at supersonic velocities. In this way, they take care of issues that are not presently feasible.

The most significant advantage of quantum computers is the speed at which it can take care of complex issues. While theyre lightning speedy at what they do, they dont give abilities to take care of issues from undecidable or NP-Hard problem classes. There is a problem set that quantum computing will have the option to explain, anyway, its not applicable for all computing problems.

Ordinarily, the issue set that quantum computers are acceptable at solving includes number or data crunching with an immense amount of inputs, for example, complex optimisation problems and communication systems analysis problemscalculations that would normally take supercomputers days, years, even billions of years to brute force.

The application that is routinely mentioned as an instance that quantum computers will have the option to immediately solve is solid RSA encryption. A recent report by the Microsoft Quantum Team recommends this could well be the situation, figuring that itd be feasible with around a 2330 qubit quantum computer.

Streamlining applications leading the pack makes sense well since theyre at present to a great extent illuminated utilizing brute force and raw computing power. If quantum computers can rapidly observe all the potential solutions, an ideal solution can become obvious all the more rapidly. Streamlining stands apart on the grounds that its significantly more natural and simpler to get a hold on.

The community of people who can fuse optimization and robust optimization is a whole lot bigger. The machine learning community, the coinciding between the innovation and the requirements are technical; theyre just pertinent to analysts. Whats more, theres a much smaller network of statisticians on the planet than there are of developers.

Specifically, the unpredictability of fusing quantum computing into the machine learning workflow presents an impediment. For machine learning professionals and analysts, its very easy to make sense of how to program the system. Fitting that into a machine learning workflow is all the more challenging since machine learning programs are getting very complex. However, teams in the past have published a lot of research on the most proficient method to consolidate it in a training workflow that makes sense.

Undoubtedly, ML experts at present need another person to deal with the quantum computing part: Machine learning experts are searching for another person to do the legwork of building the systems up to the expansions and demonstrating that it can fit.

In any case, the intersection of these two fields goes much further than that, and its not simply AI applications that can benefit. There is a meeting area where quantum computers perform machine learning algorithms and customary machine learning strategies are utilized to survey the quantum computers. This region of research is creating at such bursting speeds that it has produced a whole new field called Quantum Machine Learning.

This interdisciplinary field is incredibly new, however. Recent work has created quantum algorithms that could go about as the building blocks of machine learning programs, yet the hardware and programming difficulties are as yet significant and the development of fully functional quantum computers is still far off.

The future of AI sped along by quantum computing looks splendid, with real-time human-imitable practices right around an inescapable result. Quantum computing will be capable of taking care of complex AI issues and acquiring multiple solutions for complex issues all the while. This will bring about artificial intelligence all the more effectively performing complex tasks in human-like ways. Likewise, robots that can settle on optimised decisions in real-time in practical circumstances will be conceivable once we can utilize quantum computers dependent on Artificial Intelligence.

How away will this future be? Indeed, considering just a bunch of the worlds top organizations and colleges as of now are growing (genuinely immense) quantum computers that right now do not have the processing power required, having a multitude of robots mirroring humans running about is presumably a reasonable way off, which may comfort a few people, and disappoint others. Building only one, however? Perhaps not so far away.

Quantum computing and machine learning are incredibly well matched. The features the innovation has and the requirements of the field are extremely close. For machine learning, its important for what you have to do. Its difficult to reproduce that with a traditional computer and you get it locally from the quantum computer. So those features cant be unintentional. Its simply that it will require some time for the people to locate the correct techniques for integrating it and afterwards for the innovation to embed into that space productively.

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The Well-matched Combo of Quantum Computing and Machine Learning - Analytics Insight

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Why would you be thinking about quantum computing? Yes, it may be two years or more before quantum computing will be widely available, but there are already quite a few organizations that are pressing ahead. I'll get into those use cases, but first - Lets start with the basics:

Classical computers require built-in fans and other ways to dissipate heat, and quantum computers are no different. Instead of working with bits of information that can be either 0 or 1, as in a classical machine, a quantum computer relies on "qubits," which can be in both states simultaneously called a superposition thanks to the quirks of quantum mechanics. Those qubits must be shielded from all external noise, since the slightest interference will destroy the superposition, resulting in calculation errors. Well-isolated qubits heat up quickly, so keeping them cool is a challenge.

The current operating temperature of quantum computers is 0.015 Kelvin or -273C or -460F. That is the only way to slow down the movement of atoms, so a "qubit" can hold a value.

There have been some creative solutions proposed for this problem, such as the nanofridge," which builds a circuit with an energy gap dividing two channels: a superconducting fast lane, where electrons can zip along with zero resistance, and a slow resistive (non-superconducting) lane. Only electrons with sufficient energy to jump across that gap can get to the superconductor highway; the rest are stuck in the slow lane. This has a cooling effect.

Just one problem though: The inventor, MikkoMttnen, is confident enough in the eventual success that he has applied for a patent for the device. However, "Maybe in 10 to 15 years, this might be commercially useful, he said. Its going to take some time, but Im pretty sure well get there."

Ten to fifteen years? It may be two years or more before quantum computing will be widely available, but there are already quite a few organizations that are pressing ahead in the following sectors:

An excellent, detailed report on the quantum computing ecosystem is: The Next Decade in Quantum Computingand How to Play.

But the cooling problem must get sorted. It may be diamonds that finally solve some of the commercial and operational/cost issues in quantum computing: synthetic, also known as lab-grown diamonds.

The first synthetic diamond was grown by GE in 1954. It was an ugly little brown thing. By the '70s, GE and others were growing up to 1-carat off-color diamonds for industrial use. By the '90s, a company called Gemesis (renamed Pure Grown Diamonds) successfully created one-carat flawless diamonds graded ILA, meaning perfect. Today designer diamonds come in all sizes and colors: adding Boron to make them pink or nitrogen to make them yellow.

Diamonds have unique properties. They have high thermal conductivity (meaning they don't melt like silicon). The thermal conductivity of a pure diamond is the highest of any known solid. They are also an excellent electrical insulator. In its center, it has an impurity called an N-V center, where a carbon atom is replaced by a nitrogen atom leaving a gap where an unpaired electron circles the nitrogen gap and can be excited or polarized by a laser. When excited, the electron gives off a single photon leaving it in a reduced energy state. Somehow, and I admit I dont completely understand this, the particle is placed into a quantum superposition. In quantum-speak, that means it can be two things, two values, two places at once, where it has both spin up and spin down. That is the essence of quantum computing, the creation of a "qubit," something that can be both 0 and 1 at the same time.

If that isnt weird enough, there is the issue of entanglement. A microwave pulse can be directed at a pair of qubits, placing them both in the same state. But you can "entangle" them so that they are always in the same state. In other words, if you change the state of one of them, the other also changes, even if great distances separate them, a phenomenon Einstein dubbed, spooky action at a distance. Entangled photons don't need bulky equipment to keep them in their quantum state, and they can transmit quantum information across long distances.

At least in the theory of the predictive nature of entanglement, adding qubits explodes a quantum computer's computing power. In telecommunications, for example, entangled photons that span the traditional telecommunications spectrum have enormous potential for multi-channel quantum communication.

News Flash: Physicists have just demonstrated a 3-particle entanglement. This increases the capacity of quantum computing geometrically.

The cooling of qubits is the stumbling block. Diamonds seem to offer a solution, one that could quantum computing into the mainstream. The impurities in synthetic diamonds can be manipulated, and the state of od qubit can held at room temperature, unlike other potential quantum computing systems, and NV-center qubits (described above) are long-lived. There are still many issues to unravel to make quantum computers feasible, but today, unless you have a refrigerator at home that can operate at near absolute-zero, hang on to that laptop.

But doesnt diamonds in computers sound expensive, flagrant, excessive? It begs the question, What is anything worth? Synthetic diamonds for jewelry are not as expensive as mined gems, but the price one pays at retail s burdened by the effect of monopoly, and so many intermediaries, distributors, jewelry companies, and retailers.

A recent book explored the value of fine things and explains the perceived value which only has a psychological basis.In the 1930s, De Beers, which had a monopoly on the world diamond market and too many for the weak demand, engaged the N. W. Ayers advertising agency realizing that diamonds were only sold to the very rich, while everyone else was buying cars and appliances. They created a market for diamond engagement rings and introduced the idea that a man should spend at least three months salary on a diamond for his betrothed.

And in classic selling of an idea, not a brand, they used their earworm taglines like diamonds are forever. These four iconic words have appeared in every single De Beers advertisement since 1948, and AdAge named it the #1 slogan of the century in 1999. Incidentally, diamonds arent forever. That diamond on your finger is slowly evaporating.

The worldwide outrage over the Blood Diamond scandal is increasing supply and demand for fine jewelry applications of synthetic diamonds. If quantum computers take off, and a diamond-based architecture becomes a standard, it will spawn a synthetic diamond production boom, increasing supply and drastically lowering the cost, making it feasible.

Many thanks to my daughter, Aja Raden, an author, jeweler, and behavioral economist for her insights about the diamond trade.

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Quantum computing is right around the corner, but cooling is a problem. What are the options? - Diginomica

March 23, 2020 A new approach for using a quantum computer to realize a near-term killer app for the technology received first prize in the 2019 IBM Q Best Paper Awardcompetition, the company announced. The paper, Minimizing State Preparations in Variational Quantum Eigensolver (VQE) by Partitioning into Commuting Families, was authored by UChicago CS graduate studentPranav Gokhaleand fellow researchers from theEnabling Practical-Scale Quantum Computing (EPiQC)team.

The interdisciplinary team of researchers from UChicago, University of California, Berkeley, Princeton University and Argonne National Laboratory won the $2,500 first-place award for Best Paper. Their research examined how the VQE quantum algorithm could improve the ability of current and near-term quantum computers to solve highly complex problems, such as finding the ground state energy of a molecule, an important and computationally difficult chemical calculation the authors refer to as a killer app for quantum computing.

Quantum computers are expected to perform complex calculations in chemistry, cryptography and other fields that are prohibitively slow or even impossible for classical computers. A significant gap remains, however, between the capabilities of todays quantum computers and the algorithms proposed by computational theorists.

VQE can perform some pretty complicated chemical simulations in just 1,000 or even 10,000 operations, which is good, Gokhale says. The downside is that VQE requires millions, even tens of millions, of measurements, which is what our research seeks to correct by exploring the possibility of doing multiple measurements simultaneously.

Gokhale explains the research inthis video.

With their approach, the authors reduced the computational cost of running the VQE algorithm by 7-12 times. When they validated the approach on one of IBMs cloud-service 20-qubit quantum computers, they also found lower error as compared to traditional methods of solving the problem. The authors have shared theirPython and Qiskit codefor generating circuits for simultaneous measurement, and have already received numerous citations in the months since the paper was published.

For more on the research and the IBM Q Best Paper Award, see theIBM Research Blog. Additional authors on the paper include ProfessorFred Chongand PhD studentYongshan Dingof UChicago CS, Kaiwen Gui and Martin Suchara of the Pritzker School of Molecular Engineering at UChicago, Olivia Angiuli of University of California, Berkeley, and Teague Tomesh and Margaret Martonosi of Princeton University.

About The University of Chicago

The University of Chicago is an urban research university that has driven new ways of thinking since 1890. Our commitment tofree and open inquirydraws inspired scholars to ourglobal campuses, where ideas are born that challenge and change the world. We empower individuals to challenge conventional thinking in pursuit of original ideas. Students in theCollegedevelop critical, analytic, and writing skills in ourrigorous, interdisciplinary core curriculum. Throughgraduate programs, students test their ideas with UChicago scholars, and become the next generation of leaders in academia, industry, nonprofits, and government.

Source: The University of Chicago

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Research by University of Chicago PhD Student and EPiQC Wins IBM Q Best Paper - HPCwire

In the Budget 2020 speech, Finance Minister Nirmala Sitharaman made a welcome announcement for Indian science over the next five years she proposed spending 8,000 crore (~ $1.2 billion) on a National Mission on Quantum Technologies and Applications. This promises to catapult India into the midst of the second quantum revolution, a major scientific effort that is being pursued by the United States, Europe, China and others. In this article we describe the scientific seeds of this mission, the promise of quantum technology and some critical constraints on its success that can be lifted with some imagination on the part of Indian scientific institutions and, crucially, some strategic support from Indian industry and philanthropy.

Quantum mechanics was developed in the early 20th century to describe nature in the small at the scale of atoms and elementary particles. For over a century it has provided the foundations of our understanding of the physical world, including the interaction of light and matter, and led to ubiquitous inventions such as lasers and semiconductor transistors. Despite a century of research, the quantum world still remains mysterious and far removed from our experiences based on everyday life. A second revolution is currently under way with the goal of putting our growing understanding of these mysteries to use by actually controlling nature and harnessing the benefits of the weird and wondrous properties of quantum mechanics. One of the most striking of these is the tremendous computing power of quantum computers, whose actual experimental realisation is one of the great challenges of our times. The announcement by Google, in October 2019, where they claimed to have demonstrated the so-called quantum supremacy, is one of the first steps towards this goal.

Besides computing, exploring the quantum world promises other dramatic applications including the creation of novel materials, enhanced metrology, secure communication, to name just a few. Some of these are already around the corner. For example, China recently demonstrated secure quantum communication links between terrestrial stations and satellites. And computer scientists are working towards deploying schemes for post-quantum cryptography clever schemes by which existing computers can keep communication secure even against quantum computers of the future. Beyond these applications, some of the deepest foundational questions in physics and computer science are being driven by quantum information science. This includes subjects such as quantum gravity and black holes.

Pursuing these challenges will require an unprecedented collaboration between physicists (both experimentalists and theorists), computer scientists, material scientists and engineers. On the experimental front, the challenge lies in harnessing the weird and wonderful properties of quantum superposition and entanglement in a highly controlled manner by building a system composed of carefully designed building blocks called quantum bits or qubits. These qubits tend to be very fragile and lose their quantumness if not controlled properly, and a careful choice of materials, design and engineering is required to get them to work. On the theoretical front lies the challenge of creating the algorithms and applications for quantum computers. These projects will also place new demands on classical control hardware as well as software platforms.

Globally, research in this area is about two decades old, but in India, serious experimental work has been under way for only about five years, and in a handful of locations. What are the constraints on Indian progress in this field? So far we have been plagued by a lack of sufficient resources, high quality manpower, timeliness and flexibility. The new announcement in the Budget would greatly help fix the resource problem but high quality manpower is in global demand. In a fast moving field like this, timeliness is everything delayed funding by even one year is an enormous hit.

A previous programme called Quantum Enabled Science and Technology has just been fully rolled out, more than two years after the call for proposals. Nevertheless, one has to laud the governments announcement of this new mission on a massive scale and on a par with similar programmes announced recently by the United States and Europe. This is indeed unprecedented, and for the most part it is now up to the government, its partner institutions and the scientific community to work out details of the mission and roll it out quickly.

But there are some limits that come from how the government must do business with public funds. Here, private funding, both via industry and philanthropy, can play an outsized role even with much smaller amounts. For example, unrestricted funds that can be used to attract and retain high quality manpower and to build international networks all at short notice can and will make an enormous difference to the success of this enterprise. This is the most effective way (as China and Singapore discovered) to catch up scientifically with the international community, while quickly creating a vibrant intellectual environment to help attract top researchers.

Further, connections with Indian industry from the start would also help quantum technologies become commercialised successfully, allowing Indian industry to benefit from the quantum revolution. We must encourage industrial houses and strategic philanthropists to take an interest and reach out to Indian institutions with an existing presence in this emerging field. As two of us can personally attest, the Tata Institute of Fundamental Research (TIFR), home to Indias first superconducting quantum computing lab, would be delighted to engage.

R. Vijayaraghavan is Associate Professor of Physics at the Tata Institute of Fundamental Research and leads its experimental quantum computing effort; Shivaji Sondhi is Professor of Physics at Princeton University and has briefed the PM-STIAC on the challenges of quantum science and technology development; Sandip Trivedi, a Theoretical Physicist, is Distinguished Professor and Director of the Tata Institute of Fundamental Research; Umesh Vazirani is Professor of Computer Science and Director, Berkeley Quantum Information and Computation Center and has briefed the PM-STIAC on the challenges of quantum science and technology development

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Picking up the quantum technology baton - The Hindu

When an egg cell of almost any sexually reproducing species is fertilized, it sets off a series of waves that ripple across the eggs surface. These waves are produced by billions of activated proteins that surge through the eggs membrane like streams of tiny burrowing sentinels, signaling the egg to start dividing, folding, and dividing again, to form the first cellular seeds of an organism.

Now MIT scientists have taken a detailed look at the pattern of these waves, produced on the surface of starfish eggs. These eggs are large and therefore easy to observe, and scientists consider starfish eggs to be representative of the eggs of many other animal species.

In each egg, the team introduced a protein to mimic the onset of fertilization, and recorded the pattern of waves that rippled across their surfaces in response. They observed that each wave emerged in a spiral pattern, and that multiple spirals whirled across an eggs surface at a time. Some spirals spontaneously appeared and swirled away in opposite directions, while others collided head-on and immediately disappeared.

The behavior of these swirling waves, the researchers realized, is similar to the waves generated in other, seemingly unrelated systems, such as the vortices in quantum fluids, the circulations in the atmosphere and oceans, and the electrical signals that propagate through the heart and brain.

Not much was known about the dynamics of these surface waves in eggs, and after we started analyzing and modeling these waves, we found these same patterns show up in all these other systems, says physicist Nikta Fakhri, the Thomas D. and Virginia W. Cabot Assistant Professor at MIT. Its a manifestation of this very universal wave pattern.

It opens a completely new perspective, adds Jrn Dunkel, associate professor of mathematics at MIT. You can borrow a lot of techniques people have developed to study similar patterns in other systems, to learn something about biology.

Fakhri and Dunkel have published their results today in the journal Nature Physics. Their co-authors are Tzer Han Tan, Jinghui Liu, Pearson Miller, and Melis Tekant of MIT.

Finding ones center

Previous studies have shown that the fertilization of an egg immediately activates Rho-GTP, a protein within the egg which normally floats around in the cells cytoplasm in an inactive state. Once activated, billions of the protein rise up out of the cytoplasms morass to attach to the eggs membrane, snaking along the wall in waves.

Imagine if you have a very dirty aquarium, and once a fish swims close to the glass, you can see it, Dunkel explains. In a similar way, the proteins are somewhere inside the cell, and when they become activated, they attach to the membrane, and you start to see them move.

Fakhri says the waves of proteins moving across the eggs membrane serve, in part, to organize cell division around the cells core.

The egg is a huge cell, and these proteins have to work together to find its center, so that the cell knows where to divide and fold, many times over, to form an organism, Fakhri says. Without these proteins making waves, there would be no cell division.

MIT researchers observe ripples across a newly fertilized egg that are similar to other systems, from ocean and atmospheric circulations to quantum fluids. Courtesy of the researchers.

In their study, the team focused on the active form of Rho-GTP and the pattern of waves produced on an eggs surface when they altered the proteins concentration.

For their experiments, they obtained about 10 eggs from the ovaries of starfish through a minimally invasive surgical procedure. Theyintroduced a hormone to stimulate maturation, and alsoinjected fluorescent markers to attach to any active forms of Rho-GTP thatrose up in response. They then observed each egg through a confocal microscope and watched as billions of the proteins activated and rippled across the eggs surface in response to varying concentrations of the artificial hormonal protein.

In this way, we created a kaleidoscope of different patterns and looked at their resulting dynamics, Fakhri says.

Hurricane track

The researchers first assembled black-and-white videos of each egg, showing the bright waves that traveled over its surface. The brighter a region in a wave, the higher the concentration of Rho-GTP in that particular region. For each video, they compared the brightness, or concentration of protein from pixel to pixel, and used these comparisons to generate an animation of the same wave patterns.

From their videos, the team observed that waves seemed to oscillate outward as tiny, hurricane-like spirals. The researchers traced the origin of each wave to the core of each spiral, which they refer to as a topological defect. Out of curiosity, they tracked the movement of these defects themselves. They did some statistical analysis to determine how fast certain defects moved across an eggs surface, and how often, and in what configurations the spirals popped up, collided, and disappeared.

In a surprising twist, they found that their statistical results, and the behavior of waves in an eggs surface, were the same as the behavior of waves in other larger and seemingly unrelated systems.

When you look at the statistics of these defects, its essentially the same as vortices in a fluid, or waves in the brain, or systems on a larger scale, Dunkel says. Its the same universal phenomenon, just scaled down to the level of a cell.

The researchers are particularly interested in the waves similarity to ideas in quantum computing. Just as the pattern of waves in an egg convey specific signals, in this case of cell division, quantum computing is a field that aims to manipulate atoms in a fluid, in precise patterns, in order to translate information and perform calculations.

Perhaps now we can borrow ideas from quantum fluids, to build minicomputers from biological cells, Fakhri says. We expect some differences, but we will try to explore [biological signaling waves] further as a tool for computation.

This research was supported, in part, by the James S. McDonnell Foundation, the Alfred P. Sloan Foundation, and the National Science Foundation.

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The growth of an organism rides on a pattern of waves - MIT News

Quantum Computing Market report covers the worldwide top manufacturers like (D-Wave Systems, Google, IBM, Intel, Microsoft, 1QB Information Technologies, Anyon Systems, Cambridge Quantum Computing, ID Quantique, IonQ, QbitLogic, QC Ware, Quantum Circuits, Qubitekk, QxBranch, Rigetti Computing) which including information such as: Capacity, Production, Price, Revenue, Cost, Shipment,Gross, Gross Profit, Interview Record, Business Distribution etc., these data help the consumer know about the competitors better. This Quantum Computing Marketreport includes (6 Year Forecast 2020-2026)Overview, Classification, Industry Value, Price, Cost and Gross Profit.This Quantum Computing industry report also covers all the regions and countries of the world, which shows a regional development status, including market size, volume and value, as well as price data.

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Scope of Quantum Computing Market: Quantum computing is a technology that applies the laws of quantum mechanics to computational ability. It includes three states, namely 1, 0 as well as the superposition of 1 and 0. Superposition indicates that two states exist at the same time. These bits are known as quantum bits or qubits. The global quantum computing market consists of the hardware that is required to develop quantum computers and its peripherals.

North America accounted for the largest share of the overall quantum computing market in 2017. On the other hand, Asia Pacific (APAC) would be the fastest growing region for quantum computing during the forecast period. This growth can be attributed to the increasing demand for quantum technology to solve the most tedious and complex problems in the defense and banking & finance industry.

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Quantum Computing Market Increase In Analysis & Development Activities Is More Boosting Demands - Daily Science