Google wants to make programming quantum computers easier

Quantum computers are still in their infancy, but builders of the exotic machines want to encourage software developers to experiment with them. Programming the circuits on quantum machines is a real challenge . Instead of standard digital bits, which represent either 1 or 0, quantum computers use “qubits,” which can be in both states at once thanks to a phenomenon known as superposition. Qubits can also influence one another even if they’re not physically connected. Moreover, they stay in their delicate quantum state for no longer than the blink of an eye. Exploiting them requires completely different software, and only a small band of developers currently has the highly specialized knowledge to write such programs. Google wants to help change that. It has just released Cirq, a software toolkit that lets developers create algorithms without needing a background in quantum physics. Cirq is an open-source initiative, which means anyone can access and modify the software. Google likens it to its popular TensorFlow open source toolkit that has made it easier to build machine-learning software. For now, developers can use Cirq to create quantum algorithms that run on simulators. But the goal is to have it help build software that will run on a wide range of real machines in the future. The tech giant has also released OpenFermion-Cirq, a toolkit for creating algorithms that simulate molecules and properties of materials. Indeed, chemistry is among the applications in which quantum computers are likely to be of most use in the short term. One of the companies that worked with Google on Cirq’s development is Zapata Computing, whose early focus is on software for chemistry and materials (see “The world’s first quantum superstore—or so it hopes—is here”). Another Google partner is Quantum Benchmark, which helps people assess the performance of different kinds of quantum hardware for various applications. “Cirq gives us an accessible platform for providing our tools to users,” says Joseph Emerson, the firm’s CEO and founder. There are other open-source initiatives already under way that let developers build code for some existing quantum machines, but Google’s move is significant because the company has been at the forefront of developing powerful quantum processors like the Bristlecone chip in the image above, which holds the record for number of qubits (see our qubit counter here).  Researchers working in the quantum field say that sharing code openly will help foster a more vibrant developer community, just as it has in other areas of software. “We’re at such an early stage in the development of quantum computing that it’s to everyone’s advantage that things are done out in the open,” says Andrew Childs, who is co-director of the Joint Center for Quantum Information and Computer Science at the University of Maryland. The other thing that will foster interest is greater accessibility to quantum computers themselves, many of which still reside in academic labs. Companies like IBM and Rigetti Computing have already made their machines accessible to people who want to run algorithms on them, and Google looks set to follow suit. It says it plans to make the Bristlecone processor available via the computing cloud, and that developers will be able to use Cirq to write programs for it.

https://www-technologyreview-com.cdn.ampproject.org/v/s/www.technologyreview.com/s/611673/google-wants-to-make-programming-quantum-computers-easier/amp/?amp_js_v=a2&amp_gsa=1#amp_tf=From%20%251%24s&ampshare=https%3A%2F%2Fwww.technologyreview.com%2Fs%2F611673%2Fgoogle-wants-to-make-programming-quantum-computers-easier%2F

Magnetic model simulated in 3D by D-Wave quantum processor

Researchers in Canada have used a @DWave  quantum processing unit to solve a computationally challenging problem in condensed matter physics. While the speed of the calculation does not surpass that of the best conventional computers, the work could be a major step towards the use of quantum processors to enhance physicists’ understanding of systems that are currently difficult to compute. Some experts, however, say that the technique has significant limitations.  Advertisement The team focussed on the transverse field Ising model, which is a stalwart of condensed-matter theory. It is used, for example, to describe magnetic materials by assuming that spin magnetic moments are fixed on a regular lattice and interact with their nearest neighbours in the presence of an applied magnetic field. Other systems outside condensed matter physics can also be described by the same equations. Quantum computing expert Helmut Katzgraber of Texas A&M University in the US offers an example: “Suppose you have a very large museum such as the Louvre in Paris and you want to place guards in the museum. You want to find the smallest number of guards that you can distribute across the museum such that every single room is watched.” In 1D, the model’s equations can be solved analytically. In two or more dimensions, however, numerical solutions are required. On a conventional computer, a lot of computing power is needed to run the necessary algorithms: “The workhorse for studying that system is something referred to as quantum Monte Carlo,” explains condensed matter physicist Richard Harris of D-Wave Systems. “People use very large servers to study that particular system using that technique.”

https://physicsworld.com/a/magnetic-model-simulated-in-3d-by-d-wave-quantum-processor/

D-Wave Demonstrates Large-Scale Programmable Quantum Simulation

BURNABY, British Columbia, July 12, 2018 (GLOBE NEWSWIRE) -- @DWave Systems Inc., the leader in quantum computing systems and software, announced the publication of a significant scientific result in the peer-reviewed journal Science [Vol. 361, Issue 6398, July 13 2018]. The article, titled “Phase transitions in a programmable spin glass simulator,” details how a D-Wave 2000Q™ quantum computer was used to predict phase transitions within a particular quantum mechanical system known as the transverse field Ising model. This work has significantly raised the bar in regards to size and complexity of the problems addressed by fully programmable quantum computers. The D-Wave system is capable of programming the individual interactions between spins, whereas prior work with other quantum devices was limited to studying systems in which those interactions could not be individually programmed. In the work described in the Science article, researchers used a 2048-qubit D-Wave quantum computer to study the transverse field Ising model on 3-dimensional simple cubic lattices up to dimensions of 8x8x8 (512 quantum spins). The magnetic phases, and more importantly the phase transitions, were correctly identified within the 3-dimensional space as a function of quantum mechanical energy scale, the strength of interactions between spins, and disorder among the programmable interactions. E.H. “Ned” Allen, Ph.D., Chief Scientist and Corporate Senior Fellow at Lockheed Martin, commented on the work described in Science: Over the past two years, D-Wave scientists and engineers have accomplished a premier goal of scientific computing: characterization of the phase behavior of a genuinely new material not found in nature by a precisely controlled quantum computer used as a simulator (see R. Harris et al, ‘citation to paper’). While it’s not a demonstration of the “quantum supremacy” sought by pundits of quantum computing, it is a more important accomplishment because the problem they’ve attacked is one of immediate significance to today’s advanced technology sectors and it is the first truly useful application of a quantum computer. A crucial contribution of the Harris group’s work, then, is that it shows us how to explore the behavior of novel system designs without having to completely understand them first, as we must to write a useful digital simulation code. D-Wave’s tools presented in the paper are useful in initial conceptualization and invention – not just analysis. According to scientists at D-Wave, this work is important in the following regards: The demonstration of phase transitions as a function of quantum mechanical energy scale is strong evidence the D-Wave quantum system is able to perform quantum simulations. The results demonstrate that the embedded 3-dimensional system, whose connectivity is vastly different from that of the physical layout of qubits within the QPU, behaves as expected. The experimental techniques used in this study have motivated new work to search for signatures of long-range correlations between quantum mechanical degrees of freedom in the vicinity of the observed phase transitions. Such correlations are not only of scientific interest, but are expected to be critical to realizing a computational advantage when using D-Wave’s quantum computers on a broad range of computation problems of commercial utility. “This work represents an important milestone for quantum computing, because it is the first time physics of this kind has been simulated in a scalable architecture at such a large scale,” said Vern Brownell, CEO of D-Wave. “It also provides unprecedented validation for annealing quantum computing, which is the basis of D-Wave’s quantum technology.” In 1982, the theoretical physicist Richard Feynman proposed the use of an engineered quantum system, a so-called quantum simulator, as a quantum computer to study computationally challenging quantum mechanical problems. The key insight brought forth by Feynman was that, at its core, nature is quantum mechanical and that simulating nature would be much more efficient if the computer used to perform that simulation were likewise quantum mechanical. While many quantum mechanics calculations for even modest-sized systems become intractable using classical digital computing technologies, a quantum computer can successfully perform those computational tasks with relative ease. Thus, a practical large-scale quantum computer will be a key enabling technology for advancing many branches of sciences and engineering.

https://globenewswire.com/news-release/2018/07/12/1536928/0/en/D-Wave-Demonstrates-Large-Scale-Programmable-Quantum-Simulation.html

The Quantum Race the United States Can’t Afford To Lose

The #quantum race is on, and the stakes are high. The winner will gain a military and intelligence edge, as well as a first mover advantage in what is guaranteed to be a massive industry for decades to come. Europe and China have both been pumping government funds into the industry, and after some wrangling on Capitol Hill, the United States is throwing its hat into the ring. Thanks to quantum computing, computers are about to become unfathomably powerful. Instead of relying on transistors and binary signals as is the case with current computers, quantum computers use microwaves and quantum particles to explore multiple calculations simultaneously. This allows quantum computers to be blazingly fast. One prototype quantum computer proved 100 million times faster than its normal counterparts, and these speeds have numerous applications. Likewise, quantum technologies will also be applied more broadly than in just computers, reinventing many devices and technical standards. Quantum computers will be able to simulate previously impossibly large chemical reactions, leading to new materials and medicines. Intensely precise sensors and clocks will enable disruption-proof navigational technologies, radars, and more. Previously challenging optimization problems, such as analyzing complex sets of variables to find the best asset allocation for an investment portfolio, will be within the realm of feasibility. The first country to successfully commercialize quantum technologies will gain a huge first mover advantage, both in quantum devices and in all of the discoveries the technology will unlock. Quantum computers will also have a large impact on cybersecurity. Current cryptographic methods focus on using complex math to scramble data into unintelligible content. With their incredibly fast processing speeds, quantum computers will be able to rapidly decrypt content into readable data, making current cryptographic methods trivial to break. #Quantumphysics will also be able to provide better encryption than what is currently possible, creating systems that alert users if anyone tries to eavesdrop. U.S. tech giants, including @IBM, @Intel, @Microsoft, and @Google, were among the first to pick up on quantum’s value. Last year IBM built one of the largest quantum computers to date, and their user-friendly quantum computing service is already available for free via the cloud. Google announced its plan to reach quantum supremacy, and Microsoft announced it is very close to releasing its own quantum computer and possibly has an improved design from other tech giants. U.S. companies face fierce competitors from abroad. Alibaba also offers quantum computing services via the cloud and Baidu aims to be a global leader in quantum computing software within the next five years. A healthy amount of private sector competition is good for the industry, but Chinese and European companies have been receiving heavy government assistance. The European Commission has issued a Quantum Manifesto and is pursuing its $1.13 billion quantum technologies strategic plan. Europe has defined their focus on ‘near-to-market’ quantum technologies that offer commercial benefits, such as communications networks, ultra-sensitive cameras, and software to interact with quantum devices. A step ahead of Europe is China, which is investing $10 billion into its National Laboratory for Quantum Information Sciences in Hefei, set to open in 2020. China has successfully facilitated a two-way quantum secured video call from Beijing to Vienna using its Micius satellite and inaugurated the first long distance quantum landline.

https://www.cfr.org/blog/quantum-race-united-states-cant-afford-lose

Quantum Computing: What It Is, And Who The Major Players Are

When you change the way you look at things, the things you look at change" -- Max Planck, Father of Quantum Physics We are in a computer age where computing devices are an integral and inseparable part of our lives. However, these machines consume a certain amount of energy per bit to perform any operation. Going by current energy consumption trends, it is predicted that by 2040 computing will not be sustainable, as the energy required will exceed the world’s estimated energy production. This calls for a fundamental reduction in consumption and this is where quantum computing enters the fray. Here’s an overview of the market and the players working on this revolutionary technology. Understanding quantum computing Quantum computing harnesses the unique ability of subatomic participles, which allows them to exist in more than one state at the same time. By leveraging this feature, quantum computers can handle operations at speeds exponentially higher than conventional computers while consuming much less energy. “While the classical computer is very good at calculus, the quantum computer is even better at sorting, finding prime numbers, simulating molecules, and optimization, and thus could open the door to a new computing era,” a Morgan Stanley report notes. It is believed that quantum computing will have a huge impact on areas where “computing power is becoming a limitation for R&D such as commerce, finance, military affairs, intelligence, pharmaceuticals (drug design and discovery), aerospace (designing), utilities (nuclear fusion), chemicals (polymer design), Artificial Intelligence (AI), and Big Data search, and capital goods, especially digital manufacturing. The market for quantum computing is projected to be around $5 billion to $10 billion a year by Morgan Stanley in the next 10 years, while a report by Homeland Security Research estimates that the global market for quantum computing and technologies will grow at a CAGR of 24.6% throughout 2018-2024. By 2024, products and services market would be $8.45 billion while government-funded research and development would be $2.25 billion. According to CIR, revenue from quantum computing could reach $8 billion by 2027. Major Players IBM (IBM) recently predicted that quantum computing will be mainstream in five years. Last year, IBM announced its “industry-first initiative to build commercially available universal quantum computing systems,” dubbed “IBM Q” to be delivered via the IBM Cloud. In November 2017, IBM announced significant upgrades for its quantum systems, including the development of the first working 50 qubit processor (a "qubit" is a unit of quantum information). In December 2017, 12 of its initial clients (including names like JPMorgan Chase, Samsung, Barclays, Honda, Oxford University, among others) joined the IBM Q Network to explore practical applications of quantum computing to solve previously “unsolvable” problems across industries. For example, @IBM ’s association with @JPMorgan Chase is to apply quantum computing to different aspects of financial industry such as trading strategies, portfolio optimization, asset pricing and risk analysis. Or take @Samsung, which is working with IBM to study use cases on the semiconductor and electronics industry. @Google (GOOG, GOOGL), @NASA and the Universities Space Research Association (USRA) collaborated to set up the Quantum Artificial Intelligence Lab ( #QuAIL) project in 2013. The project primarily aims to use quantum computing to improve the NASA’s ability to “solve difficult optimization problems for missions in aeronautics, Earth and space sciences, and space exploration.” In 2013, the facility installed the @DWave Two quantum computer by D-Waves Systems, the world's first #quantumcomputing company. In 2017, the D-Wave 2000Q system, by far the most advanced quantum computer available, was installed at QuAIL. In March 2018, Google unveiled Bristlecone, its new quantum processor. Google believes, “Bristlecone would then be a compelling proof-of-principle for building larger scale quantum computers.” @Microsoft (MSFT) established #StationQ, a research lab in 2005 to focus on studies of topological quantum computing to perform computations. In recent years, Microsoft has intensified its efforts towards quantum computing. The company’s approach to building a quantum computer is “based on a type of qubit – or unit of quantum information – called a topological qubit.” In December 2017, Microsoft released a free preview version of its Quantum Development Kit and updates to it were announced in February 2018.

https://m.nasdaq.com/article/quantum-computing-what-it-is-and-who-the-major-players-are-cm939998

Quantum Computing, Is Simulation Before Teleportation Safe?

The next era of computing devices could be increasingly driven by quantum computing. Nobody is quite sure exactly when that next era of accessible widely commercialized quantum compputing is scheduled to arrive and fewer still appear to be clear about what quantum computing actually is. What we can say is that quantum machines are in heavy stages development today, but how we will build software to run on them is still in question. ADVERTISING inRead invented by Teads Quantum computing made simple-ish Put simply (or as simply as possible), traditional computers run on binary systems where a ‘bit’ can only be a value of 0 or 1, thus the scale of any computing engine is built on a binary foundation. Quantum computing goes further because a ‘qubit’ can have a quantum state made up of two or more values simultaneously (called a superposition), so the scale of any computing engine is built upon a quantum foundation with greater power. Logically enough then, big firms like @Microsoft, @IBM, @Google and #quantum specialist @DWave (plus others including @Raytheon, @Airbus and @Lockheed Martin) are now working to try and provide our software programmers with tools to start creating with quantum. The ‘problem’ here is that we are trying to build in a comparatively unknown space where we don’t know how things work, how they behave and quite how fragile things are -- spoiler alert, so-called ‘quantum states’ are extremely fragile and quantum errors are complex and tough to measure. Because of these fragilities, complexities and uncertainties, Forbes contributor Fred Campbell has suggested that current quantum software offerings from firms like Microsoft are mere vaporware. It’s an arguably fair and appealing argument i.e. Microsoft doesn’t have a quantum machine yet and the firm is building in relatively unknown space as it attempts to craft relevance to new quantum tools onto its existing stack including Visual Studio and the Azure cloud offering. It’s also true that the fragility of quantum computing is leading firms developing in this space to adopt various different approaches, Microsoft is betting on what we call topological quantum computer designs where qubits are more stable. What if that turns out to be the wrong path to go down? Should we start working to provide developers with tools to code to quantum realities now if the resultant fabric of quantum computing that we end up is markedly different? The answer must surely be that we should ready ourselves (and our programmer developers), but remain more skeptical about eventual realities than any one vendor feels comfortable enough to assert.

https://www.forbes.com/sites/adrianbridgwater/2018/01/02/quantum-computing-is-simulation-before-teleportation-safe/#7e96fdd0591e

Current and near term quantum computers

 The (noisy) 50-100 qubit #quantumcomputer is coming soon. ( #NISQ = noisy intermediate-scale quantum computer). NISQ devices cannot be simulated by brute force using the most powerful currently existing #supercomputers. NISQ will be an interesting tool for exploring physics. It might also have useful applications. But we’re not sure about that. NISQ will not change the world by itself. Rather it is a step toward more powerful quantum technologies of the future. Potentially transformative scalable quantum computers may still be decades away. We’re not sure how long it will take. Qubit “quality” The number of qubits is an important metric, but it is not the only thing that matters. The quality of the qubits, and of the “quantum gates” that process the qubits, is also very important. All quantum gates today are noisy, but some are better than others. Qubit measurements are also noisy. For today’s best hardware (superconducting circuits or trapped ions), the probability of error per (two-qubit) gate is about 1 per 1000, and the probability of error per measurement is about 1 per 100 (or better for trapped ions). We don’t yet know whether systems with many qubits will perform that well. Naively, we cannot do many more than 1000 gates (and perhaps not even that many) without being overwhelmed by the noise. Actually, that may be too naïve, but anyway the noise limits the computational power of NISQ technology. Eventually we’ll do much better, either by improving (logical) gate accuracy using quantum error correction (at a hefty overhead cost) or building much more accurate physical gates, or both. But that probably won’t happen very soon. Other important features: The time needed to execute a gate (or a measurement). E.g., the two-qubit gate time is about 40 ns for superconducting qubits, 100 µs for trapped ions, a significant difference. Also qubit connectivity, fabrication yield, …  Quantum Speedups? When will quantum computers solve important problems that are beyond the reach of the post powerful classical supercomputers? We should compare with post-exascale classical hardware, e.g. 10 years from now, or more (over 10^18 FLOPS). We should compare with the best classical algorithms for the same tasks. Note that, for problems outside NP (e.g typical quantum simulation tasks), validating the performance of the quantum computer may be difficult. Even if classical supercomputers can compete, the quantum computer might have advantages, e.g. lower cost and/or lower power consumption. Quantum optimizers Eddie Farhi: “Try it and see if it works!” We don’t expect a quantum computer to solve worst case instances of NP-hard problems, but it might find better approximate solutions, or find them faster. Hybrid quantum/classical algorithms. Combine quantum evaluation of an expectation value with a classical feedback loop for seeking a quantum state with a lower value. Quantum approximate optimization algorithm (QAOA). In effect, seek low-energy states of a classical spin glass. Variational quantum eigensolvers (VQE). Seek low energy states of a quantum many-body system with a local Hamiltonian H. (Much easier than algorithms which require simulation of time evolution governed by H.) Classical optimization algorithms (for both classical and quantum problems) are sophisticated and well-honed after decades of hard work. Will NISQ be able to do better? How quantum testbeds might help Peter Shor: “You don’t need them [testbeds] to be big enough to solve useful problems, just big enough to tell whether you can solve useful problems.” Classical examples: Simplex method for linear programming: experiments showed it’s fast long before theorists could prove that it’s fast. Metropolis algorithm: experiments showed it’s useful for solving statistical physics problems before theory established criteria for rapid convergence. Deep learning. Mostly tinkering so far, without much theory input. Possible quantum examples: Quantum annealers, approximate optimizers, variational eigensolvers, … playing around may give us new ideas. But in the NISQ era, imperfect gates will place severe limits on circuit size. In the long run, quantum error correction will be needed for scalability. In the near term, better gates might help a lot! What can we do with, say, less than 100 qubits, depth less than 100? We need a dialog between quantum algorithm experts and application users. Quantum annealing The D-Wave machine is a (very noisy) 2000-qubit quantum annealer (QA), which solves optimization problems. It might be useful. But we have no convincing theoretical argument that QAs are useful, nor have QA speedups been demonstrated experimentally. QA is a noisy version of adiabatic quantum computing (AQC), and we believe AQC is powerful. Any problem that can be solved efficiently by noiseless quantum computers can also be solved efficiently by noiseless AQC, using a “circuit-to-Hamiltonian map.” But in contrast to the quantum circuit model, we don’t know whether noisy AQC is scalable. Furthermore, the circuit-to-Hamiltonian map has high overhead: Many more qubits are needed by the (noiseless) AQC algorithm than by the corresponding quantum circuit algorithm which solves the same problem. Theorists are more hopeful that a QA can achieve speedups if the Hamiltonian has a “sign problem” (is “non-stoquastic”). Present day QAs are stoquastic, but non-stoquastic versions are coming soon. Assessing the performance of QA may already be beyond the reach of classical simulation, and theoretical analysis has not achieved much progress. Further experimentation should clarify whether QAs actually achieve speedups relative to the best classical algorithms. QAs can also be used for solving quantum simulation problems rather than classical optimization problems (D-Wave, unpublished). Quantum speedups in the NISQ era and beyond Can noisy intermediate-scale quantum computing (NISQ) surpass exascale classical hardware running the best classical algorithms? Near-term quantum advantage for useful applications is possible, but not guaranteed. Hybrid quantum/classical algorithms (like QAOA and VQE) can be tested. Near-term algorithms should be designed with noise resilience in mind. Quantum dynamics of highly entangled systems is especially hard to simulate, and is therefore an especially promising arena for quantum advantage. Experimentation with quantum testbeds may hasten progress and inspire new algorithms. NISQ will not change the world by itself. Realistically, the goal for near-term quantum platforms should be to pave the way for bigger payoffs using future devices. Lower quantum gate error rates will lower the overhead cost of quantum error correction, and also extend the reach of quantum algorithms which do not use error correction. Truly transformative quantum computing technology may need to be fault tolerant, and so may still be far off. But we don’t know for sure how long it will take. Progress toward fault tolerant QC must continue to be a high priority for quantum technologists. Quantum hardware: state of the art IBM Quantum Experience in the cloud: now 16 qubits (superconducting circuit). 20 qubits by end of 2017, 50-qubit device “built and measured.” Google 22-qubit device (superconducting circuit), 49 qubits next year. Harvard 51-qubit quantum simulator (Rydberg atoms in optical tweezers). Dynamical phase transition in Ising-like systems; puzzles in defect (domain wall) density. UMd 53-qubit quantum simulator (trapped ions). Dynamical phase transition in Ising-like systems; high-efficiency single-shot readout of many-body correlators. ionQ: 32-qubit processor planned (trapped ions), with all-to-all connectivity. Microsoft: is 2018 the year of the Majorana qubit? And many other interesting platforms … spin qubits, defects in diamond (and other materials), photonic systems, … There are other important metrics besides the number of qubits; in particular, the two-qubit gate error rate (currently over 1 per 1000) determines how large a quantum circuit can be executed with reasonable signal-to-noise

https://www.google.com/amp/s/www.nextbigfuture.com/2017/12/current-and-near-term-quantum-computers.html/amp#ampshare=https://www.nextbigfuture.com/2017/12/current-and-near-term-quantum-computers.html

U.S. Leads World in Quantum Computing Patent Filings with IBM Leading the Charge

The ever-decreasing size of transistors and circuitry utilized in computing devices today are necessitating a push towards quantum computing, or computing architectures for performing operations with components utilizing quantum-mechanical phenomena. As transistor gates are made smaller and smaller, becoming close to the size of the electrons they’re meant to control for the proper transmission of data, the physics of classical computing will no longer be adequate to perform operations. The transition to quantum computing will require a greater scientific understanding of quantum phenomena, such as entanglement and superposition, as well as major technological advances such as the first-ever demonstration of a Fredkin gate last year in Australia. Research and development into quantum computing have been making some headlines recently. In early November, Armonk, NY-based information tech giant #IBM (NYSE: @IBM) announced two upgrades to its #quantumcomputing technologies, branded as #IBMQ, including an operational prototype of a processor which can perform #quantumoperations using 50 #quantumbits, or #qubits, for an average coherence time of 90 milliseconds; that may provide an incredibly short window of time to perform #quantumoperations, but IBM still leads the field in that regard. Academia is also becoming more invested in quantum computing R&D as is reflected in a recent New York Times article on quantum research being performed at Yale, MIT and elsewhere. Business startups in the field are also finding themselves to be valuable investments. Yale spin-off Quantum Circuits Inc. recently announced a round of funding which netted the firm $18 million which it will reportedly use to build and sell a practical quantum computing platform. Patenting activities in the quantum computing sector have also rapidly increased in recent years according to a quantum computing patent landscape report recently released by patent analytics advisory firm Patinformatics. Among the highlights of this report include a major increase in quantum computing patent family publications which are forecast to rise by 430 percent from less than 100 publications in 2014 up to more than 400 publications projected through 2017. That three-year period represents a significant statistical breakout compared to the 50 to 100 publications range which was generally experienced between 2003 and 2014. (NOTE: A single patent family includes all patent filings across various countries which cover the same inventive concept.) The recent Patinformatics quantum computing report, which primarily deals with inventions relating to the computing aspect itself and not necessarily specific applications, analyzes three areas of quantum computing patents: qubits, the computational units involved in quantum operations which are capable of existing in a variety of states; hardware, including the circuitry and gates for quantum devices, some of which are specific to certain types of qubits; and applications for quantum computing generally. 2017 projections indicate that qubit technologies will see the most patent family publications, followed closely by quantum hardware patents with quantum application patents placing at a not-too-distant third. Within the qubit sector itself, super-conducting loop technology are seeing the greatest amount of interest from research and development firms. Projections for 2017 show that about 80 patent families related to super-conducting loop inventions will publish this year, a total which is nearly four times the number of patent families covering second-place quantum dot tech which are projected to publish this year. According to Anthony Trippe, Patinformatics’ managing director, this is a strong sign that super-conducting loop quantum computer technologies will be the first type of qubit technology to be commercially released. “It’s probably about five to ten years closer to market than what is seen in other literature,” Trippe said. He noted that some have discussed the potential of topological qubits, which is projected to be covered by a projected five patent families publishing this year, but that Microsoft (NASDAQ:MSFT) was the only tech firm investing heavily in that field. Quantum hardware patent filings are being driven by circuit-related technologies, while cryptography and annealing applications were major drivers among quantum application patent publications. In terms of countries of priority for quantum computer patent application filings, the United States is by far the preferred jurisdiction for applicants. The U.S. has been the priority country listed on around 800 quantum computer patent publications, nearly 3.5 times the number of priority country publications from second-place Japan. China, in third-place, has nearly 200 priority country publications in the quantum computer space. However, since 2014, China has swapped places with Japan and China’s projected publication growth rate is expected to increase faster than Japan’s in the coming years. “People have been patenting in this space since the 1990s,” Trippe notes, “but it really hasn’t taken off until the 2014 timeframe. It’s one of those really unique technologies that people have known about for a long time and it hasn’t reached critical mass, but now things are accelerating rapidly.” Among individual companies, it’s actually a Canadian firm which has the largest portfolio of patent families directed at quantum computing. British Columbia-based D-Wave Systems was an early developer in quantum computing, seeing 34 patent families published between 2003 and 2005. D-Wave has had a total of 170 patent families covering quantum computing published since 2002 and is projected to have 34 patent families publish this year. The highest projection for 2017 patent family publications, however, belongs to Armonk, NY-based tech giant IBM (NYSE:IBM), which is likely to have 60 patent families publish this year. Rounding out the top five companies by total number of patent families are Microsoft, Japan-based Nippon Telegraph and Telephone (NTT) (TYO:9432) and defense firm Northrop Grumman (NYSE:NOC). “The most fascinating thing for us is that when the media talks about the subject of quantum computing, all you’ll see is IBM, Microsoft, Google or D-Wave,” Trippe said. “You don’t see anything about NTT or Northrop Grumman.” Among companies who are increasing their patent filing activities in the quantum computing space, Trippe notes that it’s interesting to see Nokia/Alcatel (NYSE:NOK) having a large increase in publications since 2016. Nokia has shown a recent interest in monetizing its patent portfolio by selling assets, including its August announcement that it would be unloading 4,260 patent families to anyone paying in cash. These patents were acquired in 2015 when Nokia bought Alcatel-Lucent. “They have a significant portfolio in the space and they’re a known seller,” Trippe said, noting that Nokia is likely near the top of the list in terms of companies looking to make patent deals in the quantum computing space. The Patinformatics quantum computing report also provides feedback on the sectors of quantum computing upon which patenting companies are focused. For instance, D-Wave systems has a particular interest in qubit patents with about 100 such patent families while IBM shows a stronger interest in hardware, where it outpaces D-Wave in publications. In terms of quantum hardware, IBM has taken a particular interest in circuit technologies whereas Microsoft looks to be the sole leader in logic gates. Most quantum application patent families are directed at general quantum processing methods but D-Wave has broken out in quantum annealing applications; the Patinformatics report finds that 33 percent of D-Wave’s entire portfolio is directed at quantum annealing. Trippe noted that among Chinese firms included in the patent landscape report, there appears to be a heavy interest in locking down the quantum cryptography sector of application inventions. “They’re clearly trying to corner the market on being able to use cryptographic methods to protect data from being cracked by quantum computers,” he said. One interesting finding from the Patinformatics report is that, although Northrop Grumman doesn’t have the largest portfolio in the field, it is well-situated to compete with the biggest players. “One of our main assertions is that, if there’s an organization interested in being competitive with IBM, they may want to contemplate a partnership or acquisition of Northrop Grumman,” Trippe said. Both Northrop and IBM have made significant investments into super-conducting loop qubit technologies and Northrop actually edges IBM in logic gate hardware. “In order to compete with IBM, we think that there will be some consolidation,” Trippe said. “Companies that no one is talking about today will be key players in that universe.” Patinformatics’ patent report also includes spatial concept map analysis of emerging companies in the quantum computing space and the sectors being covered by their patenting activities. Some startups have a wider scope of patent family publications, such as Somerville, MA-based MagiQ which has invested in encryption applications, photon generation and processor hardware, as well as some qubit technologies. By contrast, Australian firm Qucor and Irish firm Element Six are more narrowly focused on qubit tech, especially within super-conducting loops and diamond vacancies. The contributions of the academic world to the quantum computing patent landscape cannot be overlooked either according to the Patinformatics report. The top three universities in the field include two American institutions, MIT and Harvard, and a Chinese school in third place, Zhejiang University. “It’s pretty clear that eventually, that IP is going to end up with somebody,” Trippe said. “There are going to be collaborations that take place coming from these primarily Western universities.” Data on what these academic patents cover suggest that Chinese institutions, much like many Chinese companies, aren’t interested so much in hardware inventions as locking down applications, especially cryptography. Chinese universities are projected to have more patent families published in 2017 than U.S. universities
http://www.ipwatchdog.com/2017/12/04/u-s-leads-world-quantum-computing-patent-ibm/id=90304/

Quantum Computing Market: Regional Market Segment by Production, Consumption, Revenue and Growth Rate

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. Firstly, the Quantum Computing market research report provides a basic overview of the industry including definitions, market status and industry chain structure. The Quantum Computing market analysis is provided for the international market including development history, competitive landscape analysis, and major regions’ development status. What’s more, the Quantum Computing industry development trends and growth patterns are analyzed. Request a sample of Quantum Computing market research report @ http://www.360marketupdates.com/enquiry/request-sample/10828964 Quantum Computing market potential is analysed for each geographical region based on the growth rate, macroeconomic parameters, consumer buying patterns, demand and present scenarios in Quantum Computing industry. To determine the Quantum Computing market size the report considers the revenue generated from sales of quantum computers only. Further the Quantum Computing market report focuses on global major leading industry players with information. Report contains vendor landscape in addition to a SWOT analysis of the key vendors operating in #QuantumComputing market space like #DWave Systems, #Google, #IBM, #Intel, and #Microsoft. Other Prominent Vendors in the market are: 1QB Information Technologies and many more. Quantum Computing Market Drivers, Challenges and Trends: – Quantum Computing Market Driver: –  one of the major drivers for this market is increasing expenditure by stakeholders. There are different stakeholders in the market, namely governments and private enterprises, that have shown an increasing interest in quantum computing. Quantum computing will have potential applications in a variety of sectors such as aerospace and defense, civil aviation, cybersecurity, finance, healthcare, and logistics. The potential applications have compelled governments and companies to focus on developing quantum computers and related technologies. The investments by these stakeholders drive the global quantum computing market. Quantum Computing Market Challenge: – one of the major factors hindering the growth of this market is quantum decoherence. Quantum decoherence is one of the major challenges that is faced by quantum computing firms. This is a process wherein a quantum state tends to become a classical computing bit. Any outside interference can lead to the destruction of the quantum state, which will make the bit transition into either a 0 or a 1 state. Outside interferences include heat, internal defects, and vibrations. This results in the loss of information that the qubits hold to the surroundings. Researchers are focusing on preserving superposition, which is the basis of quantum computing by delaying decoherence. Quantum Computing Market trend: – The latest trend gaining momentum in the market is growth of AI and machine learning. AI is a branch of science that deals with computers, machines, software, and computer-operated robots to think intelligently to find solutions for complex problems in a manner that is like how a human brain thinks. AI is applied to the projects that require a human’s intellectual processes such as the ability to reason, derive conclusions from the past, and generalize certain learnings. Machine learning is a type of AI that allows computers to self-learn. When a computer is exposed to new data, it can analyze it, make decisions, grow, and learn from this data

http://www.satprnews.com/2017/11/27/quantum-computing-market-regional-market-segment-by-production-consumption-revenue-and-growth-rate/

Google Debuts Software to Open Up Quantum Computers for Chemists

Google unveiled software aimed at making it easier for scientists to use the quantum computers in a move designed to give a boost to the nascent industry. The software, which is open-source and free to use, could be used by chemists and material scientists to adapt algorithms and equations to run on quantum computers. It comes at a time when @Google, @IBM, @Intel Corp., @Microsoft Corp. and @DWave Systems Inc. are all pushing to create #quantumcomputers that can be used for commercial applications.  Already, Google, IBM and D-Wave allow businesses to experiment with using not-very-powerful quantum computers for free through their cloud networks. Quantum computers could, in theory, be orders of magnitude more powerful than existing conventional supercomputers. Many believe they will enable people to do things once considered impossible -- from simulating chemical catalysts and modeling highly-complex systems, like climate, to breaking almost all public key encryption. But so far, the quantum machines these companies have built are not powerful or accurate enough to outperform conventional computers at most tasks. Google, which is part of Alphabet Inc., partnered with startup Rigetti Computing -- a rival in the effort to build practical quantum computers -- to create the new software. Researchers at ETH Zurich, the U.S. Lawrence Berkeley National Laboratories, the University of Michigan, Harvard University, the University of Oxford, Dartmouth College and NASA also helped design the software, Google said in a blog post. Called OpenFermion, the new software contains a library of algorithms for simulating how electrons interact, which is important for work in both chemistry and material science, on a quantum computer. Until now, these interactions could only be simulated on powerful conventional computers. Chemists would have had to team up with specialized quantum developers and done a lot of coding to be able to run the equations on a quantum machine. But Google and the other developers are releasing two plug-ins that will allow OpenFermion to directly translate algorithms from two of the most popular conventional simulators, Psi4 and PySCF, to run on a quantum computer. The software is also designed to be compatible with several different quantum computers, including the ones being developed by Google, Rigetti and IBM. Google has said it plans before the end of the year to achieve a milestone in computer science known as "quantum supremacy" -- using a quantum computer to do something that no conventional computer can do.

https://www.bloomberg.com/news/articles/2017-10-23/google-debuts-software-to-open-up-quantum-computers-for-chemists

India to Join China and the United States With Its Own Quantum Computer

India to take on China and the United States by building its own Quantum Computer Quantum computer is touted as the next big leap in technology. China has been leading the #Quantumcomputer arena and has already sent a hack-proof quantum computer into space. They even managed to achieve the first ever Star Trek-like teleportation by sending a ‘Photon’ 500 km from space to the Space Center in China. The United States is not far behind but its Quantum computer technology is shrouded in secret under the official secrets act. Indian scientists who have made a name for themselves by sending ‘Mangalyaan’ a Mars orbiter at 1/5th the price of American Mars Orbiter and launching an extraordinary 104 satellites in the space at one go. Now the Indian scientists have embarked on their next mission – building India’s own Quantum computer. Keen to tap into the next big advance in computing technology, the Department of Science and Technology (DST) is planning to build its own quantum computer. What is a Quantum Computer? Unlike the normal computer and laptops that we have at our homes, the quantum computer employs the principles of quantum mechanics to store information in ‘qubits’ instead of the typical ‘bits’ of 1 and 0. While our computers and laptops run on the principle of bits and bytes, the Quantum computers run on ‘Qubits’ These Qubits are theoretically 100 times faster than the conventions bits and bytes and work faster because of the way such circuits are designed, and their promise is that they can do intensive number-crunching tasks much more efficiently than the fastest comparable computers.  How fast is a Quantum Computer? Quantum computers are considered to the fastest things on Earth. To give you an example, a quantum computer would require 3.5 million fewer steps than a traditional machine to sort and parse a billion numbers. A quantum computer can find the solution in only 31,623 steps compared to the millions of steps a conventional computer would take. What is the use of a Quantum Computer? One of the top uses of Quantum computer is of course military. Indian military could have the power to number crunch any problems from field military formations to in-house missile tests and hydrogen yield testing. Quantum computer can also be used to predict the weather correctly. India depends on monsoon and a correct prediction may help its millions of farmers produce a variety of crops according to the monsoon outbreak. A quantum computer can also help ISRO’s space programme besides providing the necessary infrastructure for the Aadhar card backbone. The Indian government hopes to directly credit benefits and subsidies (Universal Basic Income) directly to the account of the beneficiary.  How long will India’s Quantum Computer take to build? While India has the necessary resources like brain power and funds, quantum computing is a very resource intensive enterprise. The Physics departments at the Indian Institute of Science, Bangalore, and the Harish Chandra Research Institute, Allahabad, have forayed into the theoretical aspects of quantum computing, the first step to building India’s own quantum computer. Experts from across the country are expected to gather this month in Allahabad for a workshop to develop such a computer. Canada’s D-Wave Systems which a pioneer in developing quantum computers and has sold machines to Lockheed Martin and Google will also be a part of this august gathering. Still, India is at least two years away from actually building its own quantum computer according to experts.
https://www.techworm.net/2017/09/india-join-china-united-states-quantum-computer.html

Computing about to take a quantum leap

#Quantumcomputing can make computers work a lot faster In theory, #quantumcomputers could be vastly superior to regular or “classical” computers in performing certain kinds of tasks, but it’s been hard to build one Creating breakthrough medicines in just months instead of scores of years spent in complex research, cracking the toughest computer code in just minutes, creating fool proof financial models for capital markets that analyse trends and execute trades at lightning speeds or forecasting weather with absolute precision, with marginal possibilities of error. These are no longer in the realms of distant possibilities but could turn into reality in just a couple of years, as quantum computing research progresses rapidly with the promise of workable versions being available as early as end of this year.According to MarketWatch, the quantum computing market is projected to top $5bn by 2020, not quite the big leagues yet. It attracted $147 million in venture capital in the last three years alone, and $2.2 billion in government funding globally, according to a Deloitte analysis. Barclays and Goldman Sachs are investigating the use of quantum computing in areas such as "portfolio optimization, asset pricing, capital project budgeting and data security. From fintech, to big data, to hardware design, cybersecurity, general analysis services, information and systems modelling, biotechnology, and a host of other sectors, once quantum computing gains sufficient traction, this would unleash the next wave of disruption along with artificial intelligence.

https://www.nationalheraldindia.com/science-tech/computing-about-to-take-a-quantum-leap

This Is Why Quantum Computing Is More Dangerous Than You Realize

#Quantumcomputing may still largely reside in the realm of scientists, but assuming it’s too many years off to be relevant today would be a serious mistake. In reality, #quantumcomputers are now commercially available. The research has largely exited the pure science phase and is now focusing on resolving engineering challenges. Furthermore, progress continues at an exponentially accelerating pace, extending Moore’s Law well beyond traditional semiconductor-based microprocessors. But the real reason you should pay attention: quantum computing can – in theory – defeat all modern encryption. From secure banking transactions to confidential correspondence to, yes, Blockchain – quantum computing can crack them all quickly and simply.
https://www.forbes.com/sites/jasonbloomberg/2017/08/11/this-is-why-quantum-computing-is-more-dangerous-than-you-realize/?c=0&s=trending#1ad343e31365

Quantum Computing Market Worth 495.3 Million USD by 2023

According to the new market research report on the " #QuantumComputing Market by Revenue Source, Application (Simulation, Optimization, and Sampling), Industry (Defense, Banking & Finance, Energy & Power, Chemicals, and Healthcare & Pharmaceuticals), and Geography - Global Forecast to 2023", published by MarketsandMarkets™ this market is expected to be valued at USD 495.3 Million by 2023, at a CAGR of 29.04% between 2017 and 2023. The major factors driving the growth of the quantum computing market include increasing incidences of cybercrimes, early adoption of quantum computing in the automotive and defense industry, and increasing investment by government entities in the quantum computing market.

http://www.prnewswire.com/news-releases/quantum-computing-market-worth-4953-million-usd-by-2023-639443813.html

Quantum leap: Obstacles remain, but a revolution in computing is almost here

Salesman Tom is about to hit the road for a monthlong journey to visit customers and sales prospects, a trip that will take him to 50 destinations across the United States. Tom needs to optimize the trip by three priorities. He must first maximize the time he spends with each client. Second, he must complete the trip in the shortest possible distance. Finally, he needs to do it at the lowest possible cost. This variation on the classic “traveling salesman problem” would take one of today’s off-the-shelf computer servers decades to solve definitively, if it could solve the problem at all. A quantum computer could knock it off in seconds. Route optimization is one of the sweet spots of this technology, but so are modeling chemical compounds, spotting patterns in DNA sequences, optimizing financial portfolios and forecasting weather. Fleets of autonomous vehicles will be managed far more safely and efficiently by quantum computers than by traditional ones. The technology could revolutionize risk analysis in the insurance industry. In short, the more complex the problem and the greater the number of variables involved, the better #quantumcomputing looks. That’s one reason the field has acquired an almost mythical aura over the more than 35 years that scientists have pursued it. Now, there’s mounting evidence that quantum computing is tantalizingly close to reality. Investment capital is flowing into the market, and some quantum computer developers are talking about showing prototypes of supercomputer-grade systems as soon as next year. Quantum startup #IonQ Inc. said last month that it has raised $22 million toward its goal of producing general-purpose quantum processors within 12 months. It’s the second startup in this field to score significant funding this year. #Rigetti Computing Inc. said in March that it has raised $64 million and expects to demonstrate a machine next year that will outperform the world’s largest supercomputers in some tasks. #IBM Corp. put a #quantumprocessor on its #publiccloud in March and invited researchers to experiment with it. The move closely followed an announcement by #DWave Systems Inc. that it sold a giant quantum machine to an unspecified customer for $15 million. And in July, a report said #Google Inc. also plans to offer researchers access to its new quantum computing technology via the cloud. The pace of activity this year is all the more remarkable given that, as recently as three years ago, experts were debating whether quantum computers could ever even be built. The consensus now is that it’s just a matter of time, and not that much time either. “The major obstacles toward coherent, capable systems are pretty much worked out,” said Andrew Bestwick, director of engineering at Rigetti. “The major challenges now are how to take something that’s been demonstrated on small systems and implement it in a highly scalable form.” That could also open up a lucrative new market. Currently it’s small, but it’s growing quickly. Market Research Future expects quantum computer sales to surge 24 percent annually to nearly $2.5 billion in 2022. Market Research Media Ltd. is even more optimistic, forecasting $5 billion in annual sales in 2020. Good timing The timing couldn’t be better. Moore’s Law, the doubling of the number of transistors on a square inch of silicon every two years, has propelled the computer industry for more than 50 years, but it appears to be finally running out of steam. Quantum computers could kick off a new era of growth in computing power. It’s badly needed. The Internet of Things promises to make networks dramatically more complex, requiring entirely new approaches to network management, a task well-suited to quantum technology. Then there’s the explosion of IoT data that will require new approaches to analyzing it all. And organizations that are searching for new efficiencies and revenue in the quest for digital transformation will find that quantum opens up vast new opportunities. Does that mean it’s time to hang a “for sale” sign on those Intel servers? Not yet, if ever. People on the front lines of quantum computer development say users can expect to see tangible benefits within the next few years, but the vaunted machines that can crack 256-bit encryption codes in seconds are still a decade or more away. D-Wave is the only company that’s currently shipping a commercial quantum computer, and experts dispute whether its technology is actually “true” quantum. IBM, Google and Microsoft Corp. are among the big players that have established their own initiatives, but the market is fragmented, leaderless and still squabbling over architectural details. But it’s not too early to start thinking about the problems that quantum technology could tackle: tasks of exponential complexity such as optimizing transportation routes, mapping molecular interactions, optimizing stock market portfolios and forecasting the weather. That requires understanding how quantum computing is different. Of bits and qubits The principles of quantum mechanics are so baffling to the average person that experts tend to fall back to describing the computing technology in terms of what it isn’t, which is traditional computing. Mainstream digital computers are based on binary arithmetic, in which numbers are expressed as combinations of ones and zeros. Performing calculations using these bits, or binary digits, is painfully slow, but it has the advantage of lending itself well to transistors, which exist in either an on or an off state. When you throw enough transistors at a problem, they can do that binary arithmetic at blinding speed. That’s how binary digital computers work.
https://siliconangle.com/blog/2017/08/04/quantum-leap-obstacles-remain-revolution-computing-almost/

Oak Ridge National Laboratory to use D-Wave cloud service

Department of Energy science and energy laboratory, Oak Ridge National Laboratory (ORNL), has signed a deal with #DWave to have cloud access to its #2000Q system. #ORNL plans to use the #quantumcomputer as part of a larger research initiative into advancing #hybridcomputing applications and #exascale computing. SHOW FULLSCREEN  D-Wave quantum processing unit Source: D-Wave Wave hello “ORNL researchers are investigating the use of quantum, neuromorphic, and other new computing architectures with the potential to accelerate applications and programs important to the Department of Energy,” said Dr Jeff Nichols, associate laboratory director of computing and computational sciences at ORNL. “This agreement fits squarely within our objective of providing distinctive equipment and unique facilities to our researchers to solve some of the nation’s most compelling computing challenges. This program is also a natural extension of the lab’s leadership in high-performance computing, with the next step being to accelerate the nation’s exascale program.” D-Wave computers have been met with widespread skepticism on whether they are indeed true quantum computers. John Morton, a professor of quantum computing at University College London, told Bloomberg that, with a version of the D-Wave system he saw, its qubits only remained in a quantum state for about 10 nanoseconds, not enough time to solve a very complex equation. Entanglement - where qubits function collectively - also appeared to be limited. But its systems have found favor despite the criticism and limitations - early customers include Google, Nasa and Lockheed Martin. Earlier this year, when it launched its $15 million 2000Q system, D-Wave announced its first customer for the 2,000 qubit machine - the secretive cyber security firm Temporal Defense Systems. But while TDS has close ties to the US government, directly selling to the US government has long been an ambition of D-Wave. In an effort to enter that market, the company last year launched the subsidiary D-Wave Government Inc, filled with senior appointees from the NSA, the Navy, Air Force and the CIA. In March 2017, it then partnered with Virginia Tech to create a permanent quantum computing center housing a D-Wave system at the Hume Center for National Security and Technology. Speaking last year, company president Robert Ewald told Defense News: “The US government is the largest procurer of computers on the planet. They also are the ones who typically apply technologies before others do for programmatic needs, whether it be the Pentagon programs or Department of Energy or the intelligence community.” But selling to the Department of Energy may become more troublesome in the future, with large cuts expected should the Trump administration persist with its planned economic strategy. D-Wave already sold one older system to the Los Alamos National Laboratory, but this time sold a presumably more affordable cloud service. The two groups will also work together to map applications to the D-Wave architecture. “Advancing the problem-solving capabilities of quantum computing takes dedicated collaboration with leading scientists and industry experts,” Ewald said. “Our work with ORNL’s exceptional community of researchers and scientists will help us understand the potential of new hybrid computing architectures, and hopefully lead to faster and better solutions for critical and complex problems.” ORNL and D-Wave aim to share some of these results with the scientific user community. Funds for the project appear to come from the DOE’s Exascale Computing Project, a $350 million per year scheme that recently saw business awarded to AMD, Cray, Nvidia and more. The Google in the room While D-Wave has pushed forward, earning contracts along the way, it is far from alone in the quantum computing space - IBM offers a prototype 17 qubit quantum processor cloud service, Microsoft is working on a topological quantum computer, and Alibaba is partnering with the Chinese government, to name but a few. The one to watch, many agree, is Google. Reports surfaced last year the Google was aiming for ‘quantum supremacy’ by the end of 2017, that is, to be on par, or better than, existing high performance computers. This month, Bloomberg reportedly saw internal Google slides that reiterated this claim. They also revealed a new lab it calls an “Embryonic quantum data center,” with it thought that the quantum computer would be offered on Google’s Cloud Platform. Jonathan DuBois, a scientist at Lawrence Livermore National Laboratory, told the publication that Google staff have been clear about plans to open up quantum service on cloud, and have pledged that government and academic researchers will get free access.
http://www.datacenterdynamics.com/content-tracks/servers-storage/oak-ridge-national-laboratory-to-use-d-wave-cloud-service/98688.article

Volkswagen buys D-Wave quantum computers which sell for $15 million each

Martin Hofmann, VW’s chief information officer, told New York Times that the investment in quantum computing technology is a sign of things to come. “For us, it’s a new era of technology,” he said. #VW is claimed to have used a #DWave computer to steer the movements of 10,000 taxis in Beijing simultaneously, optimising their routes and reducing congestion, according to the report in NYT. While some expressed scepticism over the test, many computer technology experts agree that binary computing systems will not be capable of keeping up with the colossal growth in both the volume of data and the requirements for processing it. #Quantumcomputing, which some say might be the solution, is still in the experimental stage and there are many challenges to overcome, never mind the fact that no one understands anything about it.

https://roboticsandautomationnews.com/2017/07/02/volkswagen-buys-d-wave-quantum-computers-which-sell-for-15-million-each/13227/

Top 5 Vendors in the Quantum Computing Market from 2017 to 2021: Technavio

The global #quantumcomputing market is forecasted to grow at a CAGR of over 35% during the forecast period. The global quantum computing market will see significant growth from 2018 because of the extensive research that has been carried out for developing a full-fledged quantum computer and related hardware. In 2017, #IBM announced an initiative known as #IBMQ, which is focused on building the world's first universal quantum computer. Competitive vendor landscape According to the report, the global quantum computing market is dominated by #DWave Systems as it is the only company to have commercialized quantum computers. However, the ongoing investment in R&D by several market participants will lead to more competition in the market once quantum computers are commercialized. “The only firm that has developed a quantum computer as of 2017 is D-Wave Systems. The company's most recent product offering is the D-Wave 2X that has over 2,000 qubits. Organizations such as #IBM, #Google, and #Microsoft have ramped up their research work for developing a #quantumcomputer within the next few years,” says Raghu Raj Singh, a lead computing devices research analyst from #Technavio. A trend that is noticed in the global computing market is that major vendors are making strategic partnerships to develop quantum computers. For example, Google is working closely with NASA and USRA to understand quantum computing and develop universal quantum computers. This report is available at a USD 1,000 discount for a limited time only: View market snapshot before purchasing Buy 1 Technavio report and get the second for 50% off. Buy 2 Technavio reports and get the third for free. Top five quantum computing market vendors D-Wave Systems D-Wave Systems is a quantum computing firm, and it is the first company to launch a series of commercially viable quantum computers. The firm released its first quantum computer, the D-Wave One in 2010. Google Google is a multinational corporation that specializes in Internet-related services and products including online advertising technologies, search engines, cloud computing, and software. The parent company of Google is Alphabet. IBM IBM is a conglomerate that operates in over 170 countries. It manufactures computer hardware and software while offering various computing services. The hardware designed by IBM for different categories include IBM's POWER microprocessors, which has been used inside many gaming consoles such as the PlayStation 3, Nintendo's Wii U, and Xbox 360. Intel Intel designs and manufactures advanced and integrated digital technology platforms, which comprise a microprocessor and chipset that can be enhanced by additional hardware, software, and services. It sells these platforms primarily to OEMs, original device manufacturers (ODMs), as well as manufacturing and communications equipment manufacturers in the computing and communications industry. Microsoft Microsoft licenses, develops, markets, and supports software, services, as well as devices worldwide. It develops, markets, and supports software and services designed to increase individual, team, and organizational productivity and efficiency to ease user operations in both hardware and software services. Its products are categorized into two divisions, namely commercial licensing and others.
http://www.businesswire.com/news/home/20170629005889/en/Top-5-Vendors-Quantum-Computing-Market-2017

Quantum Computing Market 35.12% CAGR by 2021 Says a New Research Report at ReportsnReports.com

PUNE, India, Jun 26, 2017 (PR Newswire Europe via COMTEX) -- PUNE, India, June 26, 2017 /PRNewswire/ -- The latest trend gaining momentum in the #quantumcomputing market is growth of #AI and #machinelearning. AI is a branch of science that deals with computers, machines, software, and computer-operated robots to think intelligently to find solutions for complex problems in a manner that is like how a human brain thinks. AI is applied to the projects that require a human's intellectual processes such as the ability to reason, derive conclusions from the past, and generalize certain learnings. Machine learning is a type of AI that allows computers to self-learn. When a computer is exposed to new data, it can analyze it, make decisions, grow, and learn from this data.

According to the quantum computing market report, one of the major drivers for this industry is increasing expenditure by stakeholders. There are different stakeholders in the quantum computing industry, namely governments and private enterprises that have shown an increasing interest in quantum computing. Quantum computing will have potential applications in a variety of sectors such as aerospace and defense, civil aviation, cybersecurity, finance, healthcare, and logistics. The potential applications have compelled governments and companies to focus on developing quantum computers and related technologies. The investments by these stakeholders drive the global quantum computing market.

The following companies as the key players in the global quantum computing market: #DWave Systems, #Google, #IBM, #Intel, and #Microsoft. Other prominent vendors in the market are: #1QB Information Technologies, #Anyon Systems, #CambridgeQuantumComputing, #IDQuantique, #IonQ, #QbitLogic, #QCWare, #QuantumCircuits, #Qubitekk, #QxBranch, and #Rigetti Computing. 

http://www.marketwatch.com/story/quantum-computing-market-3512-cagr-by-2021-says-a-new-research-report-at-reportsnreportscom-2017-06-26-10203147

How Quantum computing with DNA storage will affect your health

#MooresLaw, which states that processing speeds will double every two years as we cram more and more silicon transistors onto chips, has been faltering since the early 2000s when the law started to run up against fundamental limitations presented by the laws of thermodynamics. While the chip industry, with #Intel leading the charge, has found ways to sidestep the limitations up until now, many are now saying that despite the industry's best efforts, the stunning gains in processor speeds will not be seen again by the simple application of Moore's Law.

http://hardware.itbusinessnet.com/article/How-Quantum-computing-with-DNA-storage-will-affect-your-health-4944900