Category Archives: Quantum Computer

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

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

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

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

Picking up the quantum technology baton – The Hindu

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

Honeywell Achieves Breakthrough That Will Enable The Worlds Most Powerful Quantum Computer #47655 – New Kerala

The company also announced it has made strategic investments in two leading quantum computing software providers and will work together to develop quantum computing algorithms with JPMorgan Chase. Together, these announcements demonstrate significant technological and commercial progress for quantum computing and change the dynamics in the quantum computing industry.

Within the next three months, Honeywell will bring to market the world's most powerful quantum computer in terms of quantum volume, a measure of quantum capability that goes beyond the number of qubits. Quantum volume measures computational ability, indicating the relative complexity of a problem that can be solved by a quantum computer. When released, Honeywell's quantum computer will have a quantum volume of at least 64, twice that of the next alternative in the industry.

In a scientific paper that will be posted to the online repository arXiv later today and is available now on Honeywell's website, Honeywell has demonstrated its quantum charge coupled device (QCCD) architecture, a major technical breakthrough in accelerating quantum capability. The company also announced it is on a trajectory to increase its computer's quantum volume by an order of magnitude each year for the next five years.

This breakthrough in quantum volume results from Honeywell's solution having the highest-quality, fully-connected qubits with the lowest error rates.

Building quantum computers capable of solving deeper, more complex problems is not just a simple matter of increasing the number of qubits, said Paul Smith-Goodson, analyst-in-residence for quantum computing, Moor Insights & Strategy. Quantum volume is a powerful tool that should be adopted as an interim benchmarking tool by other gate-based quantum computer companies.

Honeywell Chairman and Chief Executive Officer Darius Adamczyk said companies should start now to determine their strategy to leverage or mitigate the many business changes that are likely to result from new quantum computing technology.

Quantum computing will enable us to tackle complex scientific and business challenges, driving step-change improvements in computational power, operating costs and speed, Adamczyk said. Materials companies will explore new molecular structures. Transportation companies will optimize logistics. Financial institutions will need faster and more precise software applications. Pharmaceutical companies will accelerate the discovery of new drugs. Honeywell is striving to influence how quantum computing evolves and to create opportunities for our customers to benefit from this powerful new technology.

To accelerate the development of quantum computing and explore practical applications for its customers, Honeywell Ventures, the strategic venture capital arm of Honeywell, has made investments in two leading quantum software and algorithm providers Cambridge Quantum Computing (CQC) and Zapata Computing. Both Zapata and CQC complement Honeywell's own quantum computing capabilities by bringing a wealth of cross-vertical market algorithm and software expertise. CQC has strong expertise in quantum software, specifically a quantum development platform and enterprise applications in the areas of chemistry, machine learning and augmented cybersecurity. Zapata creates enterprise-grade, quantum-enabled software for a variety of industries and use cases, allowing users to build quantum workflows and execute them freely across a range of quantum and classical devices.

Honeywell also announced that it will collaborate with JPMorgan Chase, a global financial services firm, to develop quantum algorithms using Honeywell's computer.

Honeywell's unique quantum computer, along with the ecosystem Honeywell has developed around it, will enable us to get closer to tackling major and growing business challenges in the financial services industry, said Dr. Marco Pistoia, managing director and research lead for Future Lab for Applied Research & Engineering (FLARE), JPMorgan Chase.

Honeywell first announced its quantum computing capabilities in late 2018, although the company had been working on the technical foundations for its quantum computer for a decade prior to that. In late 2019, Honeywell announced a partnership with Microsoft to provide cloud access to Honeywell's quantum computer through Microsoft Azure Quantum services.

Honeywell's quantum computer uses trapped-ion technology, which leverages numerous, individual, charged atoms (ions) to hold quantum information. Honeywell's system applies electromagnetic fields to hold (trap) each ion so it can be manipulated and encoded using laser pulses.

Honeywell's trapped-ion qubits can be uniformly generated with errors more well understood compared with alternative qubit technologies that do not directly use atoms. These high-performance operations require deep experience across multiple disciplines, including atomic physics, optics, cryogenics, lasers, magnetics, ultra-high vacuum, and precision control systems. Honeywell has a decades-long legacy of expertise in these technologies.

Today, Honeywell has a cross-disciplinary team of more than 100 scientists, engineers, and software developers dedicated to advancing quantum volume and addressing real enterprise problems across industries.

Honeywell (www.honeywell.com) is a Fortune 100 technology company that delivers industry-specific solutions that include aerospace products and services; control technologies for buildings and industry; and performance materials globally. Our technologies help aircraft, buildings, manufacturing plants, supply chains, and workers become more connected to make our world smarter, safer, and more sustainable. For more news and information on Honeywell, please visit http://www.honeywell.com/newsroom.

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Honeywell Achieves Breakthrough That Will Enable The Worlds Most Powerful Quantum Computer #47655 - New Kerala

Is time broken? Physicists filmed a quantum measurement but the ‘moment’ was blurry – The Next Web

They captured an instant in time, but the moment was blurry. That may sound like the lyrics to a sweet but ultimately nihilistic song from the grunge era, but in fact it appears to be one possible take away from an exotic new quantum physics experiment.

The team set out to discover if the ideal quantum measurement exists in nature. One of the fundamental principals of quantum mechanics involves a wacky concept called superposition. This idea basicallysays that things in the quantum world can be in more than one place at the same time.

In this experiment, the researchers trapped an atom and attempted to measure an electron in superposition. The big idea here was that the electrons atomic orbit can take more than one trajectory (high or low) and, through superposition, it can exist in both trajectories at the same time.

Read: Our universe may be part of a giant quantum computer

Under normal circumstances, the very act of measuring an object in superposition causes it to collapse into one state or another. This, theoretically, makes it near-impossible for someone to hack a quantum network undetected. But physicists have long dreamed of the ideal quantum measurement.

Such a measurement would allow scientists to get a clear view of what occurs during the collapse from superposition to classical reality (what exists before we measure versus the end-result we actually observe). And, more importantly, it would make it possible to study quantum states without forcing the violent collapse: the goal of ideal quantum measurement is to maintain superposition after observation.

According to the European teams research paper:

We demonstrate a natural process that is considered to be an ideal measurement and monitor its dynamics by taking a sequence of snapshots while the process is occurring. These snapshots are tomographically complete and allow us to compare the experimental results with the theoretical prediction of an ideal measurement.

To accomplish this, the team trapped a modified strontium ion in an electric field and subjected it to a fluorescence test. The quantum action occurs naturally in this case, which allowed the team to film it as it happened over one-millionth of a second.

What they found was something in-between classic collapse and ideal quantum measurements. Per a press release from Stockholm University:

The film shows how during the measurement some of the superpositions are lost and how this loss is gradual while others are preserved as they should be in an ideal quantum measurement.

Credit: Stockholm University

While the film itself is a breakthrough that will almost certainly further our understanding of the quantum universe the researchers are applying their work to the development of a quantum computer based on measuring trapped ions the experiment revealed a tiny morsel of information about the nature of time itself.

According to the research, the collapse from superposition to ultimate state is not instantaneous. The press release described it as occurring gradually under the influence of the measurement. As this represents what might be our closest, most-detailed observation of a quantum function unfolding, it stands to reason that its our clearest view yet of how time works in the quantum universe.

This is important because time is a sort of bedrock thread tying the classical and quantum universes together. By-and-large the scientific community treats time as an external background parameter, meaning it should work the same way in the quantum world as it does in the one we naturally observe.

Yet the results of the European teams experiment appear to confirm what Einsteins Relativity has shown us all along: time may be a malleable, physical property of the universe.

The classical and quantum worlds should be a clear case of as above, so below. If thats true, isthe idea of an exact moment something thats not fundamentally supported in nature?

Read next: India's apex court lifts the ban on cryptocurrency trading

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Is time broken? Physicists filmed a quantum measurement but the 'moment' was blurry - The Next Web

What Is Quantum Computing? The Next Era of Computational …

When you first stumble across the term quantum computer, you might pass it off as some far-flung science fiction concept rather than a serious current news item.

But with the phrase being thrown around with increasing frequency, its understandable to wonder exactly what quantum computers are, and just as understandable to be at a loss as to where to dive in. Heres the rundown on what quantum computers are, why theres so much buzz around them, and what they might mean for you.

All computing relies on bits, the smallest unit of information that is encoded as an on state or an off state, more commonly referred to as a 1 or a 0, in some physical medium or another.

Most of the time, a bit takes the physical form of an electrical signal traveling over the circuits in the computers motherboard. By stringing multiple bits together, we can represent more complex and useful things like text, music, and more.

The two key differences between quantum bits and classical bits (from the computers we use today) are the physical form the bits take and, correspondingly, the nature of data encoded in them. The electrical bits of a classical computer can only exist in one state at a time, either 1 or 0.

Quantum bits (or qubits) are made of subatomic particles, namely individual photons or electrons. Because these subatomic particles conform more to the rules of quantum mechanics than classical mechanics, they exhibit the bizarre properties of quantum particles. The most salient of these properties for computer scientists is superposition. This is the idea that a particle can exist in multiple states simultaneously, at least until that state is measured and collapses into a single state. By harnessing this superposition property, computer scientists can make qubits encode a 1 and a 0 at the same time.

The other quantum mechanical quirk that makes quantum computers tick is entanglement, a linking of two quantum particles or, in this case, two qubits. When the two particles are entangled, the change in state of one particle will alter the state of its partner in a predictable way, which comes in handy when it comes time to get a quantum computer to calculate the answer to the problem you feed it.

A quantum computers qubits start in their 1-and-0 hybrid state as the computer initially starts crunching through a problem. When the solution is found, the qubits in superposition collapse to the correct orientation of stable 1s and 0s for returning the solution.

Aside from the fact that they are far beyond the reach of all but the most elite research teams (and will likely stay that way for a while), most of us dont have much use for quantum computers. They dont offer any real advantage over classical computers for the kinds of tasks we do most of the time.

However, even the most formidable classical supercomputers have a hard time cracking certain problems due to their inherent computational complexity. This is because some calculations can only be achieved by brute force, guessing until the answer is found. They end up with so many possible solutions that it would take thousands of years for all the worlds supercomputers combined to find the correct one.

The superposition property exhibited by qubits can allow supercomputers to cut this guessing time down precipitously. Classical computings laborious trial-and-error computations can only ever make one guess at a time, while the dual 1-and-0 state of a quantum computers qubits lets it make multiple guesses at the same time.

So, what kind of problems require all this time-consuming guesswork calculation? One example is simulating atomic structures, especially when they interact chemically with those of other atoms. With a quantum computer powering the atomic modeling, researchers in material science could create new compounds for use in engineering and manufacturing. Quantum computers are well suited to simulating similarly intricate systems like economic market forces, astrophysical dynamics, or genetic mutation patterns in organisms, to name only a few.

Amidst all these generally inoffensive applications of this emerging technology, though, there are also some uses of quantum computers that raise serious concerns. By far the most frequently cited harm is the potential for quantum computers to break some of the strongest encryption algorithms currently in use.

In the hands of an aggressive foreign government adversary, quantum computers could compromise a broad swath of otherwise secure internet traffic, leaving sensitive communications susceptible to widespread surveillance. Work is currently being undertaken to mature encryption ciphers based on calculations that are still hard for even quantum computers to do, but they are not all ready for prime-time, or widely adopted at present.

A little over a decade ago, actual fabrication of quantum computers was barely in its incipient stages. Starting in the 2010s, though, development of functioning prototype quantum computers took off. A number of companies have assembled working quantum computers as of a few years ago, with IBM going so far as to allow researchers and hobbyists to run their own programs on it via the cloud.

Despite the strides that companies like IBM have undoubtedly made to build functioning prototypes, quantum computers are still in their infancy. Currently, the quantum computers that research teams have constructed so far require a lot of overhead for executing error correction. For every qubit that actually performs a calculation, there are several dozen whose job it is to compensate for the ones mistake. The aggregate of all these qubits make what is called a logical qubit.

Long story short, industry and academic titans have gotten quantum computers to work, but they do so very inefficiently.

Fierce competition between quantum computer researchers is still raging, between big and small players alike. Among those who have working quantum computers are the traditionally dominant tech companies one would expect: IBM, Intel, Microsoft, and Google.

As exacting and costly of a venture as creating a quantum computer is, there are a surprising number of smaller companies and even startups that are rising to the challenge.

The comparatively lean D-Wave Systems has spurred many advances in the fieldand proved it was not out of contention by answering Googles momentous announcement with news of a huge deal with Los Alamos National Labs. Still, smaller competitors like Rigetti Computing are also in the running for establishing themselves as quantum computing innovators.

Depending on who you ask, youll get a different frontrunner for the most powerful quantum computer. Google certainly made its case recently with its achievement of quantum supremacy, a metric that itself Google more or less devised. Quantum supremacy is the point at which a quantum computer is first able to outperform a classical computer at some computation. Googles Sycamore prototype equipped with 54 qubits was able to break that barrier by zipping through a problem in just under three-and-a-half minutes that would take the mightiest classical supercomputer 10,000 years to churn through.

Not to be outdone, D-Wave boasts that the devices it will soon be supplying to Los Alamos weigh in at 5000 qubits apiece, although it should be noted that the quality of D-Waves qubits has been called into question before. IBM hasnt made the same kind of splash as Google and D-Wave in the last couple of years, but they shouldnt be counted out yet, either, especially considering their track record of slow and steady accomplishments.

Put simply, the race for the worlds most powerful quantum computer is as wide open as it ever was.

The short answer to this is not really, at least for the near-term future. Quantum computers require an immense volume of equipment, and finely tuned environments to operate. The leading architecture requires cooling to mere degrees above absolute zero, meaning they are nowhere near practical for ordinary consumers to ever own.

But as the explosion of cloud computing has proven, you dont need to own a specialized computer to harness its capabilities. As mentioned above, IBM is already offering daring technophiles the chance to run programs on a small subset of its Q System Ones qubits. In time, IBM and its competitors will likely sell compute time on more robust quantum computers for those interested in applying them to otherwise inscrutable problems.

But if you arent researching the kinds of exceptionally tricky problems that quantum computers aim to solve, you probably wont interact with them much. In fact, quantum computers are in some cases worse at the sort of tasks we use computers for every day, purely because quantum computers are so hyper-specialized. Unless you are an academic running the kind of modeling where quantum computing thrives, youll likely never get your hands on one, and never need to.

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What Is Quantum Computing? The Next Era of Computational ...

Honeywell says it will soon launch the worlds most powerful quantum computer – TechCrunch

The best-kept secret in quantum computing. Thats what Cambridge Quantum Computing (CQC) CEO Ilyas Khan called Honeywells efforts in building the worlds most powerful quantum computer. In a race where most of the major players are vying for attention, Honeywell has quietly worked on its efforts for the last few years (and under strict NDAs, it seems). But today, the company announced a major breakthrough that it claims will allow it to launch the worlds most powerful quantum computer within the next three months.

In addition, Honeywell also today announced that it has made strategic investments in CQC and Zapata Computing, both of which focus on the software side of quantum computing. The company has also partnered with JPMorgan Chase to develop quantum algorithms using Honeywells quantum computer. The company also recently announced a partnership with Microsoft.

Honeywell has long built the kind of complex control systems that power many of the worlds largest industrial sites. Its that kind of experience that has now allowed it to build an advanced ion trap that is at the core of its efforts.

This ion trap, the company claims in a paper that accompanies todays announcement, has allowed the team to achieve decoherence times that are significantly longer than those of its competitors.

It starts really with the heritage that Honeywell had to work from, Tony Uttley, the president of Honeywell Quantum Solutions, told me. And we, because of our businesses within aerospace and defense and our business in oil and gas with solutions that have to do with the integration of complex control systems because of our chemicals and materials businesses we had all of the underlying pieces for quantum computing, which are just fabulously different from classical computing. You need to have ultra-high vacuum system capabilities. You need to have cryogenic capabilities. You need to have precision control. You need to have lasers and photonic capabilities. You have to have magnetic and vibrational stability capabilities. And for us, we had our own foundry and so we are able to literally design our architecture from the trap up.

The result of this is a quantum computer that promises to achieve a quantum Volume of 64. Quantum Volume (QV), its worth mentioning, is a metric that takes into account both the number of qubits in a system as well as decoherence times. IBM and others have championed this metric as a way to, at least for now, compare the power of various quantum computers.

So far, IBMs own machines have achieved QV 32, which would make Honeywells machine significantly more powerful.

Khan, whose company provides software tools for quantum computing and was one of the first to work with Honeywell on this project, also noted that the focus on the ion trap is giving Honeywell a bit of an advantage. I think that the choice of the ion trap approach by Honeywell is a reflection of a very deliberate focus on the quality of qubit rather than the number of qubits, which I think is fairly sophisticated, he said. Until recently, the headline was always growth, the number of qubits running.

The Honeywell team noted that many of its current customers are also likely users of its quantum solutions. These customers, after all, are working on exactly the kind of problems in chemistry or material science that quantum computing, at least in its earliest forms, is uniquely suited for.

Currently, Honeywell has about 100 scientists, engineers and developers dedicated to its quantum project.

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Majority of Promising AI Startups Are Still Based in the US – Transport Topics Online

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The most promising startups using artificial intelligence are U.S.-based companies working in the fields of health care, retail and transportation, according to a study that looked at budding AI companies around the world.

Of the top 100 startups in AI, 65% were based in the U.S., though some of those had dual headquarters in China or elsewhere, according to the analysis by CB Insights, a tech research group that analyzed data on close to 5,000 startups around the world.

These would be companies to watch that are doing really interesting research in AI, said Deepashri Varadharajan, the lead analyst on the report. Some of them might get acquired. Some might have successful product launches.

The research group considered venture capital investment, patent activity and market potential to develop its list of the companies most likely to succeed. The high percentage of U.S.-based companies reflect the countrys historical dominance in AI research, Varadharajan said.

Host Seth Clevenger went to CES 2020 in Las Vegas and met with Rich Mohr of Ryder Fleet Management Solutions and Stephan Olsen of the Paccar Innovation Center to discuss how high-tech the industry has become. Listen to a snippet above, and to hear the full episode, go to RoadSigns.TTNews.com.

More than 4,300 startups in 80 countries have raised $83 billion since 2014, including $26.6 billion just last year, according to CB Insights. While the dollar figures for investment have grown rapidly, the share of U.S.-based investments dropped in that period to 39% from 71%.

The U.S. still has the most number of deals, but that deal share has started to drop as other countries are starting to fund technologies, she said. The vast majority are automating specific tasks in white-collar settings.

That echoes a Brookings Institution study last year that found white-collar jobs are most likely to see an impact from AI, particularly in the life sciences and computer industries.

Top-ranked firms in the CB Insights ranking included several unicorns, or startups whose private valuations reached $1 billion or more. These include the following: Butterfly Network, which is building an ultrasound device that uses AI-assisted diagnostics; Faire Wholesale Inc., which helps local retailers determine what goods are predicted to sell best in specific locations, and DataRobot, whose tools help companies develop their own AI applications.

Some of the startups already have begun work with larger companies, including Caspar.AI, a U.S. and Japan-based firm thats working with Panasonic Corp. on smart home products and ClimaCell Inc., a climate-monitoring firm thats partnered with Alphabet Inc.s Google, JetBlue Airways Corp. and Delta Air Lines Inc. Google also is working with U.K.-based InstaDeep Ltd., which builds AI systems for other companies in the fields of logistics, energy and electronic design.

What the companies have in common is that they are addressing a need within specific industries and, in many cases, breaking through bottlenecks, Varadharajan said.

You can be using AI, thats great, but is there a problem that youre trying to solve? she said. It can be an industry-specific need or pushing the boundaries of core research itself.

The health care startups were looking at diagnostics, health monitoring and enhancing imaging. AI companies are working to develop commuter modeling, waste recycling and mapping for city planning. Improving the energy grid, anti-fraud features in the finance industry, and indoor farming are some of the other areas where AI is being used.

Some future trends she pointed to include energy efficiency, improving quantum computing and doctored videos called deepfakes.

With assistance from Alex Tanzi.

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Majority of Promising AI Startups Are Still Based in the US - Transport Topics Online

10 Revolutionary Technologies To Lookout For In 2020 – Fossbytes

Technology is booming day by day from anti-solar panels to Quantum computing; revolutionary inventions and modifications are everywhere.

2020 is going to be another year of new technologies as a number of technological advances have been lined up, as per the MIT Technology Review. These inventions are surely going to change the way we live.

Scientists have begun human trials of the Anti-aging drugs (Senolytics). The drugs are not supposed to make you live longer but they will reverse the process of aging.

The drug removes senescent cells; cells that lose function as we start aging, however, are resistant to cell death and infect neighboring cells.

Senolytic drugs will help save the human body from diseases that occur mainly due to aging such as Dementia, Arthritis, Cancer and Heart diseases.

Previously, scientists were dogmatic to link the natural disaster with climate change. Thanks to the new rising technologies, weather attribution studies have been able to accurately draw a link, thus convincing the world that climate change is real.

This came into existence by the increased computing power which allowed the scientists to develop high-resolution simulations. Now, scientists are able to perform more virtual experiments which increase the chances of tackling unwanted weather disturbances.

The studies also provide brief information about what natural risks can occur in the future. As per the latest studies, scientists came to the conclusion that global warming is boosting dangerous weather disturbances.

The Internet is easily hackable, however, researchers are trying to create a quantum-based Internet which will be unhackable.

A team of developers at the Delft University of Technology is creating a network that will connect four cities in the Netherlands with the use of quantum technology.

The technology will be based on a quantum behavior of atomic particles known as entanglement. Previously, there have been attempts to send photons through fiber-optic cables, however, the process broke the quantum link and made the information prone to hacking.

However, entangled photons cant be read without disrupting their content.

In the wrong hands, Census data can lead back to individuals when combined with other public statistics. To safeguard the privacy of users, the US government Census Bureau injects inaccuracies aka noise to protect the data.

However, the Census Bureau has often mixed up data with other statistics that resulted in the wrong identification of the residents.

Differential privacy is a mathematical technique that measures how much privacy increases when noise is added. The technique will help the bureau in keeping the identities of the residents private.

Hyper-personalized medicines are genetic medicines that can be tailored to any persons genes, therefore curing any specific medical issue they are suffering from. This will help in curing the diseases which are termed as too rare to cure.

Several cases are registered every year in which the patient is suffering from a rare disease caused by a genetic flaw. The concept of hyper-personalized medicines will help in curing extremely rare diseases caused due to flaws in the DNA.

As of now, Artificial intelligence relies a lot on centralized cloud services, that generate high carbon emissions and limit the privacy of AI applications.

However, researchers are working on reducing the size of deep-learning models without hampering their efficiency. Nowadays, AI chips claim to possess more computational power in compact physical space.

In May 2019, Google announced that it can run Google Assitant on smartphones without establishing connections with the remote servers. Slowly and steadily, the world is moving towards Tiny AI

Digital money is going to be the digital version of a particular countrys currency which will work as a replacement for the physical money.

In 2019, Facebook revealed its global digital currency known as Libra, however, the idea met a lot of criticism form countries and politicians. Soon after Facebooks announcement, the Peoples Bank of China also announced that it is going to launch its digital currency.

Chinese leaders see Libra as a threat because it will be backed by US dollars. Mark Zuckerberg claimed that Libra will play a major role in providing financial leadership to America on a global level.

A quantum computer can perform calculations that are almost impossible for the worlds best supercomputers. In October, Google described the first incident of quantum supremacy when a quantum computer with 53 qubits the basic unit of quantum computation solved a calculation in a time span of three minutes.

Google claimed the same calculation would have been solved by a supercomputer in a time span of 10,000 years i.e 1.5 billion times to the time taken by a quantum computer. It clearly states that is the number of qubits will be increased, quantum supremacy can be achieved soon.

Satellite mega-constellations are being created to provide high-speed internet all around the globe. SpaceX has started creating its own mega-constellation.

SpaceX CEO Elon Musk has said that as soon as they create 400 satellite constellation, the internet service will be launched for selected areas. SpaceX has the ultimate goal of creating a constellation of 800 satellites to provide internet coverage all around the globe.

Earth is home to billions of molecules and each molecule offers unlimited chemical possibilities if only researchers knew the right ones.

But now, scientists are using machine learning to explore the existing database of molecules and using the information to come up with breakthrough drugs.

Back in September, researchers at Hong Kong-based Insilico Medicine discovered 30,000 molecules with desirable properties by using deep learning techniques. Out of the total number, six molecules were selected to synthesize and test. One of them was found active and showed promising results when tested on animals.

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10 Revolutionary Technologies To Lookout For In 2020 - Fossbytes

Quantum researchers able to split one photon into three – Space Daily

Researchers from the Institute for Quantum Computing (IQC) at the University of Waterloo report the first occurrence of directly splitting one photon into three.

The occurrence, the first of its kind, used the spontaneous parametric down-conversion method (SPDC) in quantum optics and created what quantum optics researchers call a non-Gaussian state of light. A non-Gaussian state of light is considered a critical ingredient to gain a quantum advantage.

"It was understood that there were limits to the type of entanglement generated with the two-photon version, but these results form the basis of an exciting new paradigm of three-photon quantum optics," said Chris Wilson, a principle investigator at IQC faculty member and a professor of Electrical and Computer Engineering at Waterloo.

"Given that this research brings us past the known ability to split one photon into two entangled daughter photons, we're optimistic that we've opened up a new area of exploration."

"The two-photon version has been a workhorse for quantum research for over 30 years," said Wilson. "We think three photons will overcome the limits and will encourage further theoretical research and experimental applications and hopefully the development of optical quantum computing using superconducting units."

Wilson used microwave photons to stretch the known limits of SPDC. The experimental implementation used a superconducting parametric resonator. The result clearly showed the strong correlation among three photons generated at different frequencies. Ongoing work aims to show that the photons are entangled.

"Non-Gaussian states and operations are a critical ingredient for obtaining the quantum advantage," said Wilson. "They are very difficult to simulate and model classically, which has resulted in a dearth of theoretical work for this application."

Research Report: "Observation of Three-Photon Spontaneous Parametric Down-Conversion in a Superconducting Parametric Cavity"

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Quantum researchers able to split one photon into three - Space Daily