Not even the greatest geniuses in the world could explain quantum computing.

In the early 1930s Einstein, in fact, called quantum mechanics the basis for quantum computing spooky action at a distance.

Then theres a famous phrase from the late Nobel Laureate in physics, Richard Feynman: If you think you understand quantum mechanics, then you dont understand quantum mechanics.

That may be so, but the mystery behind quantum has not stopped D-Wave Systems Inc. from making its mark in the field. In the 1980s it was thought maybe quantum mechanics could be used to build a computer. So people starting coming up with ideas on how to build one, says Bo Ewald, president of D-Wave in Burnaby, B.C.

Two of those people were UBC PhD physics grads Eric Ladizinsky and Geordie Rose, who had happened to take an entrepreneur course before founding D-Wave in 1999. Since there werent a lot of businesses in the field, they created and collected patents around quantum, Ewald says.

What we have with D-Wave is the mother of all ships: that is the hardware capability to unlock the future of AI

While most who were exploring the concept were looking in the direction of what is called the universal gate model, D-Wave decided to work on a different architecture, called annealing. The two do not necessarily compete, but perform different functions.

In quantum annealing, algorithms quickly search over a space to find a minimum (or solution). The technology is best suited for speeding research, modelling or traffic optimization for example.

Universal gate quantum computing can put basic quantum circuit operations together to create any sequence to run increasingly complex algorithms. (Theres a third model, called topological quantum computing, but it could be decades before it can be commercialized.)

When D-Wave sold its first commercial product to Lockheed Martin about six years ago, it marked the first commercial sale of a quantum computer, Ewald says. Google was the second to partner with D-Wave for a system that is also being run by NASA Ames Research Center. Each gets half of the machine, Ewald says. They believed quantum computing had an important future in machine learning.

Most recently D-Wave has been working with Volkswagen to study traffic congestion in Beijing. They wanted to see if quantum computing would have applicability to their business, where there are lots of optimization problems. Another recent coup is a deal with the Los Alamos National Laboratory.

Theres no question that any quantum computing investment is a long-term prospect, but that has not hindered their funding efforts. To date, the company has acquired more than 10 rounds of funding from the likes of PSP, Goldman Sachs, Bezos Expeditions, DFJ, In-Q-Tel, BDC Capital, GrowthWorks, Harris & Harris Group, International Investment and Underwriting, and Kensington Partners Ltd.

What we have with D-Wave is the mother of all ships: that is the hardware capability to unlock the future of AI, says Jrme Nycz, executive vice-president, BDC Capital. We believe D-Waves quantum capabilities have put Canada on the map.

Now, Ewing says, the key for the company moving forward is getting more smart people working on apps and on software tools in the areas of AI, machine earning and deep learning.

To that end, D-Wave recently not only open-sourced its Qbsolv software tool, it launched an initiative with Creative Destruction Lab at the University of Torontos Rotman School of Management to create a new track focused on quantum machine learning. The intensive one-year program will go through an introductory boot camp led by Dr. Peter Wittek, author of Quantum Machine Learning: What Quantum Computing means to Data Mining, with instruction and technical support from D-Wave experts, and access to a D-Wave technology.

While it is still early days in terms of deployment for quantum computing, Ewald believes D-Waves early start gives them a leg up if and when quantum hits the mainstream. So far customers tend to be government and/or research related. Google is the notable exception. But once apps come along that are applicable for other industries, it will all make sense.

The early start has given D-Wave the experience to be able to adopt other architectures as they evolve. It may be a decade before a universal gate model machine becomes a marketable product. If that turns out to be true, we will have a 10-year lead in getting actual machines into the field and having customers working on and developing apps.

Ewald is the first to admit that as an early entrant, D-Wave faces criticism around its architecture. There are a lot of spears and things that we tend to get in the chest. But we see them coming and can deal with it. If we can survive all that, we will have a better view of the market, real customers and relationships with accelerators like Creative Destruction Lab. At the end of day we will have the ability to adapt when we need to.

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D-Wave partners with U of T to move quantum computing along - Financial Post

In BriefResearchers have found a way to make the creation of qubitssimpler and more precise. The team hopes that this new techniquecould, one day, allow for the mass production of quantum computers. Commercial Quantum Computing Quantum computing is, if you are not already familiar, simply put, a type of computation that uses qubits to encode data instead of the traditional bit (1s and 0s). In short, itallows for the superposition of states, which is where data can be in more than one state at a given time.

So, while traditional computing is limited to information belonging to only one or another state, quantum computing widens those limitations. As a result,more information can be encoded into a much smaller type of bit, allowing for much larger computing capacity. And, while it is still in relatively early development, many believe that quantum computing will be the basis of future technologies, advancing our computational speed beyond what we can currently imagine.

It was extremely exciting then whenresearchers from MIT, Harvard University, and Sandia National Laboratories unveileda simpler way of using atomic-scale defects in diamond materials to build quantum computers in a way that could possibly allow them to be mass produced.

For this process, defects are they key. They are precisely and perfectly placed to function as qubits and hold information. Previous processes weredifficult, complex, and not precise enough. This new methodcreates targeted defects in a much simpler manner. Experimentally, defects created were, on average, at or under 50 nanometers of the ideal locations.

The significance of this cannot be overstated. The dream scenario in quantum information processing is to make an optical circuit to shuttle photonic qubits and then position a quantum memory wherever you need it, says Dirk Englund, an associate professor of electrical engineering and computer science, in an interview with MIT. Were almost there with this. These emitters are almost perfect.

Image Credit: carmule / Pixabay

While the reality of quantum computers, let alone mass produced quantum computers, is still a bit of a ways off, this research is promising. One of the main remaining hurdles is how these computers will read the qubits. But these diamond defects aim to solve that problem because they naturally emit light, and since the light particles emitted can retain superposition, they could help to transmit information.

The research goes on to detail how the completion of these diamond materials better allowed for the amplification of the qubit information. By the end, the researchers found that the light emitted was approximately 80-90 percent as bright as possible.

If this work eventuallyleads to the full creation of a quantum computer, life as we know it would change irrevocably. From completely upendingmodern encryption methods to allowing us to solve previously unsolvable problems, our technology and infrastructure would never be the same. Moreover, the limitations that currently exist in how we store and transmit information would shatter, opening new opportunities foras yetunimaginable exploration.

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MIT Just Unveiled A Technique to Mass Produce Quantum Computers - Futurism

Topological qubits are among the more baffling, and if practical, more promising ways to approach scalable quantum computing. At least thats what Microsoft, Purdue University, and three other universities are hoping after having recently signed a five-year agreement to develop a topological qubit based quantum computer.

Qubits are strange no matter what form they take. The basic idea being that through superposition, a qubit can be in two states at once (0 and 1) and hence a quantum computers capacity scales exponentially with the number of qubits versus classical computers which scale linearly with the number of bits. Most quantum computing efforts rely on producing superposition in some material IBM uses superconducting devices and there have been many qubit schemes proposed.

Topological qubits are among the more mysterious. They rely on quasi particles called non-abelian anyons which have not definitively been proven to exist. Using these topological qubits, information is encoded by braiding the paths of these quasi-particles. The benefit, say researchers, is topological qubits resist decoherence much better than other qubit types and should require far less error correction. At least thats the theory.

Microsoft has been dabbling in topological qubit theory for several years. Last fall Microsoft quantum researcher Alex Boharov was interviewed by Nature (Inside Microsofts quest for a topological quantum computer, October 21, 2016) on why pursue such an exotic path.

Our qubits are not even material things. But then again, the elementary particles that physicists run in their colliders are not really solid material objects. Here we have non-abelian anyons, which are even fuzzier than normal particles. They are quasiparticles. The most studied kinds of anyon emerge from chains of very cold electrons that are confined at the edge of a 2D surface. These anyons act like both an electron and its antimatter counterpart at the same time, and appear as dense peaks of conductance at each end of the chain. You can measure them with high-precision devices, but not see them under any microscope said Boharov.

As explained by Boharov, Noise from the environment and other parts of the computer is inevitable, and that might cause the intensity and location of the quasiparticle to fluctuate. But thats OK, because we do not encode information into the quasiparticle itself, but in the order in which we swap positions of the anyons.We call that braiding, because if you draw out a sequence of swaps between neighbouring pairs of anyons in space and time, the lines that they trace look braided. The information is encoded in a topological property that is, a collective property of the system that only changes with macroscopic movements, not small fluctuations.

The upside is tantalizing he said, So far, weve had an amazing ride in terms of creating more-efficient algorithms reducing the number of qubit interactions, known as gates, that you need to run certain computations that are impossible on classical computers. In the early 2000s, for example, people thought it would take about 24 billion years to calculate on a quantum computer the energy levels of ferredoxin, which plants use in photosynthesis. Now, through a combination of theory, practice, engineering and simulation, the most optimistic estimates suggest that it may take around an hour. We are continuing to work on these problems, and gradually switching towards more applied work, looking towards quantum chemistry, quantum genomics and things that might be done on a small-to-medium-sized quantum computer.

Now, Microsoft is further ramping up its quantum efforts with a collaboration that includes Purdue as well as a global experimental group established by Microsoft at the Niels Bohr Institute at the University of Copenhagen in Denmark, TU Delft in the Netherlands, and the University of Sydney, Australia.For Purdue, this is an extension of joint work on quantum computing with Microsoft begun roughly one year ago. Michael Freedman of Microsofts Station Q in Santa Barbara leads the effort.

Whats exciting is that were doing the science and engineering hand-in-hand, at the same time, says Purdue researcher Michael Manfra in an article on the project posted on the Purdue web site yesterday.

Purdues role in the project will be to grow and study ultra-pure semiconductors and hybrid systems of semiconductors and superconductors that may form the physical platform upon which a quantum computer is built. Manfras group has expertise in a technique called molecular beam epitaxy, and this technique will be used to build low-dimensional electron systems that form the basis for quantum bits, or qubits, according to the article.

Purdue President Mitch Daniels noted in the article that Purdue was home to the first computer science department in the United States, and said the partnership and Manfras work places the university at the forefront of quantum computing.Someday quantum computing will move from the laboratory to actual daily use, and when it does, it will signal another explosion of computing power like that brought about by the silicon chip, Daniels said.

Link to Purdue article written by Steve Tally: http://www.purdue.edu/newsroom/releases/2017/Q2/microsoft,-purdue-collaborate-to-advance-quantum-computing-.html

Link Nature interview: https://www.nature.com/news/inside-microsoft-s-quest-for-a-topological-quantum-computer-1.20774

Caption for feature image:Michael Freedman (left), Microsoft Corp. quantum computing researcher, and Suresh Garimella, executive vice president for research and partnerships, and Purdues Goodson Distinguished Professor of Mechanical Engineering, sign a new five-year enhanced collaboration between Purdue and Microsoft to build a robust and scalable quantum computer by producing what scientists call a topological qubit. (Purdue University photo/Charles Jischke)

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Microsoft, Purdue Tackle Topological Quantum Computer - HPCwire - HPCwire (blog)

In BriefMajor companies like IBM are turning to artificialintelligence and quantum computing to protect against cyberattacks. While these technologies aren't silver bullets, they areessential tools for cyber security in the age of the Internet ofThings. Weapons of Cyber Warfare

Cyber security has become a key issue in our national and international discussions. No longer do cyber attacks concern only email companies and individuals who are unwilling to update their tech. Now, cyber crime has had a major impact on both U.S. mainstream political parties, and almost any organization even hospitals should have some concern about the possibility of an attack through a computer network.

In their struggle to fight cyber crime, major companies like IBM are turning to two of the worlds most powerful technologies artificial intelligence (AI) and quantum computing.

IBMs AI, Watson,helps human analysts sift through the200,000 or so security events the company has to deal with on a day-to-day basis. It helps determine which events dont require special attention, such as instances when an employee forgets their password, and which should receive more scrutiny.

Before artificial intelligence, wed have to assume that a lot of the data say 90 percent is fine. We only would have bandwidth to analyze this 10 percent, Daniel Driver from Chemring Technology Solutions, a provider of electric warfare, said in an interview with the Financial Times.The AI mimics what an analyst would do, how they look at dataIts doing a huge amount of legwork upfront, which means we can focus our analysts time.

Watson is about 60 times faster that its human counterparts, and speed is key for defending against cyber attacks. But even Watsons impressive rates pale in comparison to those that can be attained with quantum computers.

The analogy we like to use is that of a needle in a haystack, Driver said in the interview. A machine can be specially made to look for a needle in a haystack, but it still has to look under every piece of hay. Quantum computing means, Im going to look under every piece of hay simultaneously and find the needle immediately.

While these technologies are not silver bullets against cyber attacks, they are becoming vital tools in the cyber security industry, which is projected to grow from $74 billion last year to $100 billion in 2020. Part of this growth may be attributed to societys increasing reliance on the Internet of Things (IoT). As everything from light bulbs to our jackets become digitally accessible, every person should be more concerned about cyber security.

As we continue to see advancements in both AI and quantum computing technologies, more businesses and households will have access to these protective tools. AIs are already finding their places in different sectors of our society including healthcare. Perhaps in addition to diagnosing medical images, AIs can also protect hospitals from future cyber attacks.

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AI and Quantum Computers Are Our Best Weapons Against Cyber Criminals - Futurism

Photo: Erik Lucero Put Chip Here: Google will put its superconducting quantum computer chip in this 10-millikelvin dilution refrigerator.

Quantum computers have long held the promise of performing certain calculations that are impossibleor at least, entirely impracticalfor even the most powerful conventional computers to perform. Now, researchers at a Google laboratory in Goleta, Calif., may finally be on the cusp of proving it, using the same kinds of quantum bits, or qubits, that one day could make up large-scale quantum machines.

By the end of this year, the team aims to increase the number of superconducting qubits it builds on integrated circuits to create a 7-by-7 array. With this quantum IC, the Google researchers aim to perform operations at the edge of whats possible with even the best supercomputers, and so demonstrate quantum supremacy.

Weve been talking about, for many years now, how a quantum processor could be powerful because of the way that quantum mechanics works, but we want to specifically demonstrate it, says team member John Martinis, a professor at the University of California, Santa Barbara, who joined Google in 2014.

A system size of 49 superconducting qubits is still far away from what physicists think will be needed to perform the sorts of computations that have long motivated quantum computing research. One of those is Shors algorithm, a computational scheme that would enable a quantum computer to quickly factor very large numbers and thus crack one of the foundational components of modern cryptography. In a recent commentary in Nature, Martinis and colleagues estimated that a 100-million-qubit system would be needed to factor a 2,000-bit numbera not-uncommon public key lengthin one day. Most of those qubits would be used to create the special quantum states that would be needed to perform the computation and to correct errors, creating a mere thousand or so stable logical qubits from thousands of less stable physical components, Martinis says.

There will be no such extra infrastructure in this 49-qubit system, which means a different computation must be performed to establish supremacy. To demonstrate the chips superiority over conventional computers, the Google team will execute operations on the array that will cause it to evolve chaotically and produce what looks like a random output. Classical machines can simulate this output for smaller systems. In April, for example, Lawrence Berkeley National Laboratory reported that its 29-petaflop supercomputer, Cori, had simulated the output of 45 qubits. But 49 qubits would pushif not exceedthe limits of conventional supercomputers.

This computation does not as yet have a clear practical application. But Martinis says there are reasons beyond demonstrating quantum supremacy to pursue this approach. The qubits used to make the 49-qubit array can also be used to make larger universal quantum systems with error correction, the sort that could do things like decryption, so the chip should provide useful validation data.

Photo: Erik Lucero Steps to Supremacy: Googles quantum computing chip is a 2-by-3 array of qubits. The company hopes to make a 7-by-7 array later this year.

There may also be, the team suspects, untapped computational potential in systems with little or no error correction. It would be wonderful if this were true, because then we could have useful products right away instead of waiting for a long time, says Martinis. One potential application, the team suggests, could be in the simulation of chemical reactions and materials.

Google recently performed a dry run of the approach on a 9-by-1 array of qubits and tested out some fabrication technology on a 2-by-3 array. Scaling up the number of qubits will happen in stages. This is a challenging system engineering problem, Martinis says. We have to scale it up, but the qubits still have to work well. We cant have any loss in fidelity, any increase in error rates, and I would say error rates and scaling tend to kind of compete against each other. Still, he says, the team thinks there could be a way to scale up systems well past 50qubits even without error correction.

Google is not the only company working on building larger quantum systems without error correction. In March, IBM unveiled a plan to create such a superconducting qubit system in the next few years, also with roughly 50qubits, and to make it accessible on the cloud. Fifty is a magic number, says Bob Sutor, IBMs vice president for this area, because thats around the point where quantum computers will start to outstrip classical computers for certain tasks.

The quality of superconducting qubits has advanced a lot over the years since D-Wave Systems began offering commercial quantum computers, says Scott Aaronson, a professor of computer science at the University of Texas at Austin. D-Wave, based in Burnaby, B.C., Canada, has claimed that its systems offer a speedup over conventional machines, but Aaronson says there has been no convincing demonstration of that. Google, he says, is clearly aiming for a demonstration of quantum supremacy that is not something youll have to squint and argue about.

Its still unclear whether there are useful tasks a 50-or-so-qubit chip could perform, Aaronson says. Nor is it certain whether systems can be made bigger without error correction. But he says quantum supremacy will be an important milestone nonetheless, one that is a natural offshoot of the effort to make large-scale, universal quantum machines: I think that it is absolutely worth just establishing as clearly as we can that the world does work this way. Certainly, if we can do it as a spin-off of technology that will be useful eventually in its own right, then why the hell not?

This article appears in the June 2017 print issue as Google Aims for Quantum Computing Supremacy.

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Google Plans to Demonstrate the Supremacy of Quantum ... - IEEE Spectrum