The D-Wave Quantum Computer

Every so often there is a chance to make a difference. To undertake a project, which against all odds, makes a technology of the future an achievement of today.

Quantum Computation

Rather than store information using bits represented by 0s or 1s as conventional digital computers do, quantum computers use quantum bits, or qubits, to encode information as 0s, 1s, or both at the same time. This superposition of states—along with the other quantum mechanical phenomena of entanglement and tunneling—enables quantum computers to manipulate enormous combinations of states at once.

How D-Wave Systems Work

In nature, physical systems tend to evolve toward their lowest energy state: objects slide down hills, hot things cool down, and so on. This behavior also applies to quantum systems. To imagine this, think of a traveler looking for the best solution by finding the lowest valley in the energy landscape that represents the problem. 

Classical algorithms seek the lowest valley by placing the traveler at some point in the landscape and allowing that traveler to move based on local variations.  While it is generally most efficient to move downhill and avoid climbing hills that are too high, such classical algorithms are prone to leading the traveler into nearby valleys that may not be the global minimum. Numerous trials are typically required, with many travelers beginning their journeys from different points.  

In contrast, quantum annealing begins with the traveler simultaneously occupying many coordinates thanks to the quantum phenomenon of superposition. The probability of being at any given coordinate smoothly evolves as annealing progresses, with the probability increasing around the coordinates of deep valleys. Quantum tunneling allows the traveller to pass through hills—rather than be forced to climb them—reducing the chance of becoming trapped in valleys that are not the global minimum. Quantum entanglement further improves the outcome by allowing the traveler to discover correlations between the coordinates that lead to deep valleys.

Programming a D-Wave system

The D-Wave system has a web API with client libraries available for C/C++, Python, and MATLAB. This allows users to access the computer easily as a cloud resource over a network.

To program the system, a user maps a problem into a search for the “lowest point in a vast landscape,” corresponding to the best possible outcome. The quantum processing unit considers all the possibilities simultaneously to determine the lowest energy required to form those relationships. The solutions are values that correspond to the optimal configurations of qubits found, or the lowest points in the energy landscape. These values are returned to the user program over the network.

Because a quantum computer is probabilistic rather than deterministic, the computer returns many very good answers in a short amount of time—thousands of samples in one second. This provides not only the best solution found but also other very good alternatives from which to choose. 

D-Wave systems are intended to be used to complement classical computers. There are many examples of problems where a quantum computer can complement an HPC (high-performance computing) system. While the quantum computer is well suited to discrete optimization, for example, the HPC system is better at large-scale numerical simulations.

Download this whitepaper to learn more about programming a D-Wave quantum computer.

Capabilities

D-Wave’s flagship product, the 2000 qubit D-Wave 2000Q quantum computer, is the most advanced quantum computer in the world. It is based on a novel type of superconducting processor that uses quantum mechanics to massively accelerate computation. It is best suited to tackling complex optimization problems that exist across many domains such as:

• Optimization 
• Machine learning 
• Sampling / Monte Carlo 
• Pattern recognition and anomaly detection 
• Cyber security 
• Image analysis 
• Financial analysis 
• Software / hardware verification and validation 
• Bioinformatics / cancer research

Download the Technology Overview

Despite the incredible power of today’s supercomputers, many complex computing problems cannot be addressed by conventional systems. The huge growth of data and our need to better understand everything from the universe to our own DNA leads us to seek new tools that can help provide answers. Quantum computing is the next frontier in computing, providing an entirely new approach to solving the world’s most difficult challenges. D-Wave Systems is the leader in the development and delivery of quantum computing systems and software, and the world’s only commercial supplier of quantum computers. Our mission is to unlock the power of quantum computing for the world. We believe that quantum computing will enable solutions to the most challenging national defense, scientific, technical, and commercial problems. D-Wave’s systems are being used by some of the world’s most advanced organizations, including Lockheed Martin, Google, NASA Ames, the University of Southern California, and Los Alamos National Laboratory. D-Wave currently has more than 140 granted US patents and has published over 90 scientific papers, many of which have appeared in leading science journals.

In nature, physical systems tend to evolve toward their lowest energy state: objects slide down hills, hot things cool down, and so on. This behavior also applies to quantum systems. To imagine this, think of a traveler looking for the best solution by finding the lowest valley in the energy landscape that represents the problem. Classical algorithms seek the lowest valley by placing the traveler at some point in the landscape and allowing that traveler to move based on local variations. While it is generally most efficient to move downhill and avoid climbing hills that are too high, such classical algorithms are prone to leading the traveler into nearby valleys that may not be the global minimum. Numerous trials are typically required, with many travelers beginning their journeys from different points. In contrast, quantum annealing begins with the traveler simultaneously occupying many coordinates thanks to the quantum phenomenon of superposition. The probability of being at any given coordinate smoothly evolves as annealing progresses, with the probability increasing around the coordinates of deep valleys. Quantum tunneling allows the traveller to pass through hills—rather than be forced to climb them—reducing the chance of becoming trapped in valleys that are not the global minimum. Quantum entanglement further improves the outcome by allowing the traveler to discover correlations between the coordinates that lead to deep valleys.

Simple on the Outside, Extraordinary on the Inside The D-Wave 2000Q system has a footprint of approximately 10' x 7' x 10' (L x W x H). Its physical enclosure houses sophisticated cryogenic refrigeration, shielding, and I/O systems to support a single thumbnail-sized QPU. Most of the physical volume of the system is required to accommodate the refrigeration system and to provide easy service access. For quantum effects to play a role in computation, the QPU requires an extreme, isolated environment. The refrigerator and layers of shielding create an internal high vacuum environment with a temperature close to absolute zero that is isolated from external magnetic fields, vibration, and RF signals of any form. Adjoining cabinets contain the control subsystems and the front-end servers that provide connectivity to the system. The D-Wave 2000Q system can be integrated into standard data centers, high-performance computing environments, as well as private and public clouds. Systems are also accessible online through D-Wave’s hosted cloud environment.

 Colder than Interstellar Space 50 K QPU 4 K 1 K 100 mK 15 mK The D-Wave 2000Q system operates near absolute zero. This extremely low temperature, along with the shielded environment that isolates the QPU from its surroundings, enables the QPU to behave quantum mechanically. D-Wave systems operate at less than 15 millikelvin, approximately 180 times colder than interstellar space. D-Wave’s “dry” dilution refrigerator uses liquid helium refrigerant in a closed-loop system, avoiding the need for on-site replenishment. While dilution refrigerators are not uncommon in research environments, D-Wave has advanced the technology to ensure long run-life and reliability in a commercial product setting. Despite the extreme environment inside the system, a standard data center can normally accommodate the D-Wave 2000Q quantum computer. I/O, Shielding, and Materials The extreme isolated environment required for the QPU places unusual demands on the design, materials, and manufacturing processes required for the various subsystems. The I/O subsystem that passes information to the QPU and back while filtering out all unwanted noise requires a variety of normal and superconducting materials to provide the required performance. The magnetic shielding subsystem provides the lowfield environment required for the QPU, using highpermeability and superconducting materials to achieve fields below 1 nanotesla. This is 50,000 times less than the Earth’s magnetic field.

The D-Wave QPU is built from a lattice of tiny loops of the metal niobium, each of which is one qubit (shown on the next page, in red). Below temperatures of 9.2 kelvin, niobium becomes a superconductor and exhibits quantum mechanical effects. When in a quantum state, current flows in both directions simultaneously, which means that the qubit is in superposition—that is, in both a 0 and a 1 state at the same time. At the end of the problem-solving process, this superposition collapses into one of the two classical states, 0 or 1.

Going from a single qubit to a multi-qubit QPU requires that the qubits be interconnected to exchange information. Qubits are connected via couplers, which are also superconducting loops. The interconnection of qubits and couplers, together with control circuitry to manage the magnetic fields, creates an integrated fabric of programmable quantum devices. When the QPU arrives at a solution to a problem, all qubits settle into their final states and the values they hold are returned to the user as a bit string. The D-Wave 2000Q system has up to 2048 qubits and 5600 couplers. To reach this scale, it uses 128,000 Josephson junctions, which makes the D-Wave 2000Q QPU by far the most complex superconducting integrated circuit ever built.

 Unlike the CPUs of classical computers, D-Wave’s superconducting QPU dissipates negligible amounts of heat during computation. While traditional supercomputers generate massive amounts of heat and consume massive amounts of power, the D-Wave system consumes less than 25 kW of power, most of which goes towards operating the cooling and front-end servers. This low power consumption has remained constant since the introduction of the first D-Wave system despite the dramatic increase in system performance with each successive product generation. The required water cooling is on par with what a kitchen tap can provide. The required air conditioning is one-tenth of what would be expected in a data center for a system with a similar footprint. As more powerful D-Wave systems are released in the future, power consumption will remain constant, resulting in huge increases in performance per watt and per dollar. Tens of kilowatts means tens of thousands of dollars in operating costs per year in contrast to millions of dollars per year for even a modest high performance computer system that consumes megawatts of power. If realized today, exascale supercomputers would consume power on the order of that produced by the Hoover dam.

Improved Annealing Path Control Certain problems benefit when some qubits anneal slightly before or after others. The anneal offsets feature, introduced with the D-Wave 2000Q system, lets users advance or delay anneal paths to enhance application performance. Algorithms using this feature have shown performance improvements of up to 1000 times for some problem types. Quantum computers will change the world, leading to better and faster solutions to the most challenging problems, and to unprecedented applications. D-Wave quantum computers are ideally suited to solving many hard problems in optimization, machine learning, sampling and cyber security. With 2000 qubits and new control features, the D-Wave 2000Q quantum computer can solve larger problems than was previously possible, and with better performance. A growing community of developers are using the unique capabilities of D-Wave systems to solve challenging problems in a diverse set of application areas including: Machine Learning & Computer Science • Detecting statistical anomalies • Finding compressed models • Recognizing images and patterns • Training neural networks • Verifying and validating software • Classifying unstructured data • Diagnosing circuit faults Security & Mission Planning • Detecting computer viruses & network intrusion • Scheduling resources and optimal paths • Determining set membership • Analyzing graph properties • Factoring integers Healthcare & Medicine • Detecting fraud • Generating targeted cancer drug therapies • Optimizing radiotherapy treatments • Creating protein models Financial Modeling • Detecting market instabilities • Developing trading strategies • Optimizing trading trajectories • Optimizing asset pricing and hedging • Optimizing portfolios

Software and Programming Just as the classical computing world needed a software ecosystem to build a broad community of application developers and users, the quantum computing world does as well. D-Wave, new quantum software companies, D-Wave customers, and users are starting to develop system software, higher level tools, and applications that leverage the power of the D-Wave system. The D-Wave 2000Q system provides a standard Internet API (based on RESTful services), with client libraries available for C/C++, Python, and MATLAB. This interface allows users to access the system either as a cloud resource over a network, or integrated into their high-performance computing environments and data centers. Access is also available through D-Wave’s hosted cloud service. Using D-Wave’s development tools and client libraries, developers can create algorithms and applications within their existing environments using industry-standard tools. While users can submit problems to the system in a number of different ways, ultimately a problem represents a set of values that correspond to the weights of the qubits and the strength of the couplers. The system takes these values along with other user-specified parameters and sends a single quantum machine instruction (QMI) to the QPU. Problem solutions correspond to the optimal configuration of qubits found; that is, the lowest points in the energy landscape. These values are returned to the user program over the network. Because quantum computers are probabilistic rather than deterministic, multiple values can be returned, providing not only the best solution found, but also other very good alternatives from which to choose. Users can specify the number of solutions they want the system to return. Users can submit problems to the D-Wave quantum computer in several ways: • Using a program in C, C++, Python, or MATLAB to create and execute quantum machine instructions • Using a D-Wave tool such as: • QSage, a translator designed for optimization problems • ToQ, a high level language translator used for constraint satisfaction problems and designed to let users “speak” in the language of their problem domain • qbsolv, an open-source, hybrid partitioning optimization solver for problems that are larger than will fit natively on the QPU • dw, which executes QMIs created via a text editor • By directly programming the system via QMIs

What’s Next While the D-Wave quantum computer is the most advanced in the world, the quantum computing revolution has only begun. Our vision is of a future where quantum computers will be accessible and of value to all, solving the world’s most complex computing problems. This will require advances in many dimensions and contributions from experts in diverse domains. It is exciting to see increasing investment worldwide, advances in research and technology, and a growing ecosystem of developers, users, and applications needed to deliver on that vision. To learn more, contact us or check out our videos, white papers, scientific papers, and other content at www.dwavesys.com/resources.  Whitepaper 

https://www.dwavesys.com/sites/default/files/Map%20Coloring%20WP2.pdf
Overview
https://www.dwavesys.com/sites/default/files/D-Wave%202000Q%20Tech%20Collateral_0117F.pdf

And Now from Wikipedia  https://en.wikipedia.org/wiki/D-Wave_Systems

D-Wave Systems

From Wikipedia, the free encyclopedia

D-Wave Systems Inc.

Type	Privately held company
Industry	Computer hardware
Founded	1999
Headquarters	Burnaby, British Columbia, Canada
Key people	Vern Brownell, CEO Geordie Rose, CTO Eric Ladizinsky, CS V. Paul Lee, Chair
Products	D-Wave One, D-Wave Two, D-Wave 2X, D-Wave 2000Q
Revenue	N/A
Net income	N/A
Number of employees	Approx. 100+
Subsidiaries	None
Website	dwavesys.com

D-Wave Systems, Inc. is a quantum computing company, based in Burnaby, British Columbia, Canada. D-Wave is the first company in the world to sell quantum computers.

The D-Wave One was built on early prototypes such as D-Wave's Orion Quantum Computer. The prototype was a 16-qubit quantum annealing processor, demonstrated on February 13, 2007 at the Computer History Museum in Mountain View, California.^[1] D-Wave demonstrated what they claimed to be a 28-qubit quantum annealing processor on November 12, 2007.^[2] The chip was fabricated at the NASA Jet Propulsion Laboratory Microdevices Lab in Pasadena, California.^[3] These early prototypes were built upon the research papers by Umesh Vazirani, a leading researcher on quantum complexity theory, who dismissed D-Wave’s claims of speedup as a misunderstanding of his work, and suggested that "even if it turns out to be a true quantum computer, and even if it could be scaled to thousands of qubits, [it] would likely not be more powerful than a cellphone".

On May 11, 2011, D-Wave Systems announced D-Wave One, described as "the world's first commercially available quantum computer", operating on a 128-qubit chipset^[4] using quantum annealing (a general method for finding the global minimum of a function by a process using quantum fluctuations)^[5][6][7][8] to solve optimization problems. In May 2013, a collaboration between NASA, Google and the Universities Space Research Association (USRA) launched a Quantum Artificial Intelligence Lab based on the D-Wave Two 512-qubit quantum computer that would be used for research into machine learning, among other fields of study.^[9]

On August 20, 2015, D-Wave Systems announced^[10] the general availability of the D-Wave 2X^[11] system, a 1000+ qubit quantum computer. This was followed by an announcement^[12] on September 28, 2015 that it had been installed at the Quantum Artificial Intelligence Lab at NASA Ames Research Center.

In January 2017, D-Wave has released Qbsolv^[13][14][15] - a piece of open-source software for solving QUBO problems on both company's quantum processors and classic hardware architectures.

Contents

  [hide] 

• 1History
• 2Computer systems
  • 2.1Orion prototype
    • 2.1.12009 Google demonstration
  • 2.2D-Wave One
    • 2.2.1Lockheed Martin and D-Wave collaboration
    • 2.2.2Optimization problem-solving in protein structure determination
  • 2.3D-Wave Two
  • 2.4D-Wave 2X
• 3Comparison of D-Wave systems
• 4Reception
• 5Notable alumni and collaborators
• 6See also
• 7References
• 8External links

History[edit]

D-Wave was founded by Haig Farris (former chair of board), Geordie Rose (CTO and former CEO), Bob Wiens (former CFO), and Alexandre Zagoskin^[16] (former VP Research and Chief Scientist). Farris taught a business course at the University of British Columbia (UBC), where Rose obtained his Ph.D., and Zagoskin was a postdoctoral fellow. The company name refers to their first qubit designs, which used d-wave superconductors.

D-Wave operated as an offshoot from UBC, while maintaining ties with the Department of Physics and Astronomy.^[17] It funded academic research in quantum computing, thus building a collaborative network of research scientists. The company collaborated with several universities and institutions, including UBC, IPHT Jena, Université de Sherbrooke, University of Toronto, University of Twente, Chalmers University of Technology, University of Erlangen, and Jet Propulsion Laboratory. These partnerships were listed on D-Wave's website until 2005.^[18][19] In June 2014 D-Wave announced a new quantum applications ecosystem with computational finance firm 1QB Information Technologies (1QBit) and cancer research group DNA-SEQ to focus on solving real-world problems with quantum hardware.^[20]

D-Wave operated from various locations in Vancouver, British Columbia, and laboratory spaces at UBC before moving to its current location in the neighboring suburb of Burnaby. D-Wave also has offices in Palo Alto and Vienna, USA.

Computer systems[edit]

Photograph of a chip constructed by D-Wave Systems Inc., designed to operate as a 128-qubitsuperconducting adiabatic quantum optimization processor, mounted in a sample holder.

The first commercially produced D-Wave processor was a programmable,^[21] superconductingintegrated circuit with up to 128 pair-wise coupled^[22] superconducting flux qubits.^[23][24][25] The 128-qubit processor was superseded by a 512-qubit processor in 2013.^[26] The processor is designed to implement a special-purpose quantum annealing^[5][6][7][8] as opposed to being operated as a universal gate-model quantum computer.

D-Wave maintains a list of peer-reviewed technical publications by their own scientists and others on their website.^[27]

Orion prototype[edit]

On February 13, 2007, D-Wave demonstrated the Orion system, running three different applications at the Computer History Museum in Mountain View, California. This marked the first public demonstration of, supposedly, a quantum computer and associated service.

The first application, an example of pattern matching, performed a search for a similar compound to a known drug within a database of molecules. The next application computed a seating arrangement for an event subject to compatibilities and incompatibilities between guests. The last involved solving a Sudoku puzzle.

The processors at the heart of D-Wave's "Orion quantum computing system" are designed for use as hardware accelerator processors rather than general-purpose computer microprocessors. The system is designed to solve a particular NP-complete problem related to the two dimensional Ising model in a magnetic field.^[1] D-Wave terms the device a 16-qubit superconducting adiabatic quantum computer processor.^[28][29]

According to the company, a conventional front end running an application that requires the solution of an NP-complete problem, such as pattern matching, passes the problem to the Orion system.

According to Geordie Rose, founder and Chief Technology Officer of D-Wave, NP-complete problems "are probably not exactly solvable, no matter how big, fast or advanced computers get"; the adiabatic quantum computer used by the Orion system is intended to quickly compute an approximate solution.^[30]

2009 Google demonstration[edit]

On December 8, 2009, at the Neural Information Processing Systems (NIPS) conference, a Google research team led by Hartmut Neven used D-Wave's processor to train a binary image classifier.

D-Wave One[edit]

On May 11, 2011, D-Wave Systems announced the D-Wave One, an integrated quantum computer system running on a 128-qubit processor. The processor used in the D-Wave One code-named "Rainier", performs a single mathematical operation, discrete optimization. Rainier uses quantum annealing to solve optimization problems. The D-Wave One is claimed to be the world's first commercially available quantum computer system.^[31] The price will be approximately US$10,000,000.^[32]

A research team led by Matthias Troyer and Daniel Lidar found that, while there is evidence of quantum annealing in D-Wave One, they saw no speed increase compared to classical computers. They implemented an optimized classical algorithm to solve the same particular problem as the D-Wave One.^[33][34]

Lockheed Martin and D-Wave collaboration[edit]

On May 25, 2011, Lockheed Martin signed a multi-year contract with D-Wave Systems to realize the benefits based upon a quantum annealing processor applied to some of Lockheed's most challenging computation problems. The contract included purchase of the D-Wave One Quantum Computer System, maintenance, and associated professional services.^[35]

Optimization problem-solving in protein structure determination[edit]

In August 2012, a team of Harvard University researchers presented results of the largest protein-folding problem solved to date using a quantum computer. The researchers solved instances of a lattice protein folding model, known as the Miyazawa–Jernigan model, on a D-Wave One quantum computer.^[36][37]

D-Wave Two[edit]

Main article: D-Wave Two

In early 2012, D-Wave Systems revealed a 512-qubit quantum computer, code-named Vesuvius,^[38] which was launched as a production processor in 2013.^[39]

In May 2013, Catherine McGeoch, a consultant for D-Wave, published the first comparison of the technology against regular top-end desktop computers running an optimization algorithm. Using a configuration with 439 qubits, the system performed 3,600 times as fast as CPLEX, the best algorithm on the conventional machine, solving problems with 100 or more variables in half a second compared with half an hour. The results are presented at the Computing Frontiers 2013 conference.^[40]

In March 2013 several groups of researchers at the Adiabatic Quantum Computing workshop at the Institute of Physics in London produced evidence, though only indirect, of quantum entanglement in the D-Wave chips.^[41]

In May 2013 it was announced that a collaboration between NASA, Google and the USRA launched a Quantum Artificial Intelligence Lab at the NASA Advanced Supercomputing Division at Ames Research Center in California, using a 512-qubit D-Wave Two that would be used for research into machine learning, among other fields of study.^[9][42]

D-Wave 2X[edit]

On August 20, 2015, D-Wave released general availability of their D-Wave 2X computer, with 1,152 qubits in a Chimera graph architecture (although, due to magnetic offsets and manufacturing variability inherent in the superconductor circuit fabrication fewer than 1,152 qubits are functional and available for use. The exact number of qubits yielded will vary with each specific processor manufactured.) This was accompanied by a report comparing speeds with high-end single threaded CPUs. Unlike previous reports, this one explicitly stated that question of quantum speedup was not something they were trying to address, and focused on constant-factor performance gains over classical hardware. For general-purpose problems, a speedup of 15x was reported, but it is worth noting that these classical algorithms benefit efficiently from parallelization—so that the computer would be performing on par with, perhaps, 30 high-end single-threaded cores.

The D-Wave 2X processor is based on a 2,048-qubit chip with half of the qubits disabled, but these may be re-activated later on.^[43][44]

Comparison of D-Wave systems[edit]

	D-Wave One	D-Wave Two	D-Wave 2X	D-Wave 2000Q[45][46]
Available	May 2011	May 2013	August 2015	January 2017
Code-name	Rainier	Vesuvius
Qubits	128	512	1152	2048
Couplers	352		3000	5600
Josephson junctions	24,000		128,000
I/O / control lines		192
Operating temperature		0.02 K	0.015 K
Power consumption		15.5 kW	25 kW
Buyers	Lockheed Martin	Lockheed Martin Google/NASA/USRA	Lockheed Martin Google/NASA/USRA Los Alamos National Laboratory	Temporal Defense Systems Inc. Google/NASA/USRA[47] Volkswagen Group[48] Virginia Tech[49]

Reception[edit]

In 2007 Umesh Vazirani, a professor at University of California (UC) Berkeley and one of the founders of quantum complexity theory upon which D-Wave is based, made the following criticism:^[50]

Their claimed speedup over classical algorithms appears to be based on a misunderstanding of a paper my colleagues van Dam, Mosca and I wrote on "The power of adiabatic quantum computing." That speed up unfortunately does not hold in the setting at hand, and therefore D-Wave's "quantum computer" even if it turns out to be a true quantum computer, and even if it can be scaled to thousands of qubits, would likely not be more powerful than a cell phone.

Wim van Dam, a professor at UC Santa Barbara, summarized the scientific community consensus as of 2008 in the journal Nature Physics:^[51] ″At the moment it is impossible to say if D-Wave's quantum computer is intrinsically equivalent to a classical computer or not. So until more is known about their error rates, caveat emptor is the least one can say″.

An article in the May 12, 2011 edition of Nature gives details which critical academics say proves that the company's chips do have some of the quantum mechanical properties needed for quantum computing.^[52][53] Prior to the 2011 Nature paper, D-Wave was criticized for lacking proof that its computer was in fact a quantum computer. Nevertheless, questions were raised^[54] and later answered^[55] regarding experimental proof of quantum entanglement inside D-Wave devices.

MIT professor Scott Aaronson, who describes himself as "Chief D-Wave Skeptic", said that D-Wave's 2007 demonstration did not prove anything about the workings of the Orion computer, and that its marketing claims were deceptive.^[56] In May 2011 he said that he was "retiring as Chief D-Wave Skeptic",^[57] and reporting his "skeptical but positive" views based on a visit to D-Wave in February 2012. Aaronson said that one of the most important reasons for his new position on D-Wave was the 2011 Nature article.^[54][58][59] In May 16, 2013 he resumed his skeptic post. He criticizes D-Wave for blowing results out of proportion on press releases that claim speedups of three orders of magnitude, in light of a paper by scientists from ETH Zurich reporting a 128-qubit D-Wave computer being outperformed by a factor of 15 using regular digital computers and applying classical metaheuristics (particularly simulated annealing) to the problem that D-Wave's computer was specifically designed to solve.^[33]

On May 16, 2013 NASA and Google, together with a consortium of universities, announced a partnership with D-Wave to investigate how D-Wave's computers could be used in the creation of artificial intelligence. Prior to announcing this partnership, NASA, Google, and Universities Space Research Association put a D-Wave computer through a series of benchmark and acceptance tests, which it passed.^[9]Independent researchers found that D-Wave's computers could solve some problems as much as 3,600 times faster than particular software packages running on conventional digital computers.^[9] Other independent researchers found that different software packages running on a single core of a desktop computer can solve those same problems as fast or faster than D-Wave's computers (at least 12,000 times faster for quadratic assignment problems, and between 1 and 50 times faster for quadratic unconstrained binary optimization problems).^[60]

In January 2014 researchers at UC Berkeley and IBM published a classical model reproducing the D-Wave machine's observed behavior, suggesting that it may not be a quantum computer.^[61]

In March 2014, researchers at University College London and the University of Southern California (USC) published a paper comparing data obtained from a D-Wave Two computer with three possible explanations from classical physics and one quantum model. They found that their quantum model was a better fit to the experimental data than the Shin–Smith–Smolin–Vazirani classical model, and a much better fit than any of the other classical models. The authors conclude that "This suggests that an open system quantum dynamical description of the D-Wave device is well-justified even in the presence of relevant thermal excitations and fast single-qubit decoherence." ^[62]

In May 2014, researchers at D-Wave, Google, USC, Simon Fraser University, and National Research Tomsk Polytechnic University published a paper containing experimental results that demonstrated the presence of entanglement among D-Wave qubits. Qubit tunneling spectroscopy was used to measure the energy eigenspectrum of two and eight-qubit systems, demonstrating their coherence during a critical portion of the quantum annealing procedure.^[63]

A study published in Science in June 2014, described as "likely the most thorough and precise study that has been done on the performance of the D-Wave machine"^[64] and "the fairest comparison yet", attempted to define and measure quantum speedup. Several definitions were put forward as some may be unverifiable by empirical tests, while others, though falsified, would nonetheless allow for the existence of performance advantages. The study found that the D-Wave chip "produced no quantum speedup" and did not rule out the possibility in future tests.^[65] The researchers, led by Matthias Troyer at the Swiss Federal Institute of Technology in Zurich, found "no quantum speedup" across the entire range of their tests, and only inconclusive results when looking at subsets of the tests. Their work illustrated "the subtle nature of the quantum speedup question." Further work^[66] has advanced understanding of these test metrics and their reliance on equilibrated systems, thereby missing any signatures of advantage due to quantum dynamics.

There are many open questions regarding quantum speedup. The ETH reference in the previous section is just for one class of benchmark problems. Potentially there may be other classes of problems where quantum speedup might occur. Researchers at Google, USC, Texas A&M, and D-Wave are working to find such problem classes.^[67]

Notable alumni and collaborators[edit]

• Jacob Biamonte^[68] (University of Malta)
• Alexandre Zagoskin^[69] (Loughborough University)
• Vern Brownell ^[70]

See also[edit]

• AQUA@home
• Superconducting quantum computing
• Adiabatic quantum computation
• Quantum annealing
• Analog computer
• Flux qubit

References[edit]

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2. Jump up^ "D-Wave Systems News". dwavesys.com.
3. Jump up^ "A picture of the demo chip". Hack The Multiverse.
4. Jump up^ M. W. Johnson et al (2011), Quantum annealing with manufactured spins (Nature)
5. ^ Jump up to:^a b T. Kadowaki; H. Nishimori (1998). "Quantum annealing in the transverse Ising model". Phys. Rev. E. 58: 5355–5363. doi:10.1103/physreve.58.5355.
6. ^ Jump up to:^a b A. B. Finilla; M. A. Gomez; C. Sebenik; D. J. Doll (1994). "Quantum annealing: A new method for minimizing multidimensional functions". Chem. Phys. Lett. 219: 343–348. doi:10.1016/0009-2614(94)00117-0.
7. ^ Jump up to:^a b G. E. Santoro; E. Tosatti (2006). "Optimization using quantum mechanics: quantum annealing through adiabatic evolution". J. Phys. A. 39: R393. doi:10.1088/0305-4470/39/36/r01.
8. ^ Jump up to:^a b A. Das; B. K. Chakrabarti (2008). "Colloquium: Quantum annealing and analog quantum computation". Rev. Mod. Phys. 80: 1061–1081. doi:10.1103/revmodphys.80.1061.
9. ^ Jump up to:^a b c d Choi, Charles (May 16, 2013). "Google and NASA Launch Quantum Computing AI Lab". MIT Technology Review.
10. Jump up^ "D-Wave Systems Announces the General Availability of the 1000+ Qubit D-Wave 2X Quantum Computer | D-Wave Systems". www.dwavesys.com. Retrieved 2015-10-14.
11. Jump up^ http://www.dwavesys.com/d-wave-two-system
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13. Jump up^ Finley, Klint (11 January 2017). "Quantum Computing Is Real, and D-Wave Just Open-Sourced It". Wired (magazine). Condé Nast. Retrieved 14 January 2017.
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15. Jump up^ "dwavesystems/qbsolv". GitHub. Retrieved 14 January 2017.
16. Jump up^ "Department staff - Dr Alexandre Zagoskin - Physics - Loughborough University". lboro.ac.uk.
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20. Jump up^ "D-Wave Systems Building Quantum Application Ecosystem, Announces Partnerships with DNA-SEQ Alliance and 1QBit". Retrieved 2014-06-09.
21. Jump up^ M. W. Johnson et al., "A scalable control system for a superconducting adiabatic quantum optimization processor," Supercond. Sci. Technol. 23, 065004 (2010); preprint available: arXiv:0907.3757
22. Jump up^ Harris, R.; et al. (2009). "Compound Josephson-junction coupler for flux qubits with minimal crosstalk". Phys. Rev. B. 80: 052506. arXiv:0904.3784 . doi:10.1103/physrevb.80.052506.
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24. Jump up^ Next Big Future: Robust and Scalable Flux Qubit, [1], September 23, 2009
25. Jump up^ Next Big Future: Dwave Systems Adiabatic Quantum Computer [2], October 23, 2009
26. Jump up^ D-Wave Systems: D-Wave Two Quantum Computer Selected for New Quantum Artificial Intelligence Initiative, System to be Installed at NASA's Ames Research Center, and Operational in Q3, [3], May 16, 2013
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28. Jump up^ Kaminsky; William M. Kaminsky; Seth Lloyd (2002-11-23). "Scalable Architecture for Adiabatic Quantum Computing of NP-Hard Problems". Quantum Computing & Quantum Bits in Mesoscopic Systems. Kluwer Academic. arXiv:quant-ph/0211152 .
29. Jump up^ Meglicki, Zdzislaw (2008). Quantum Computing Without Magic: Devices. MIT Press. pp. 390–391. ISBN 0-262-13506-X.
30. Jump up^ "Yeah but how fast is it? Part 3. OR some thoughts about adiabatic QC". 2006-08-27. Archived from the original on 2006-11-19. Retrieved 2007-02-11.
31. Jump up^ "Learning to program the D-Wave One". Retrieved 11 May 2011.
32. Jump up^ "First Ever Commercial Quantum Computer Now Available for $10 Million". Retrieved 25 May 2011.
33. ^ Jump up to:^a b Scott Aaronson (16 May 2013). "D-Wave: Truth finally starts to emerge".
34. Jump up^ Boixo, Sergio; Rønnow, Troels F.; Isakov, Sergei V.; Wang, Zhihui; Wecker, David; Lidar, Daniel A.; Martinis, John M.; Troyer, Matthias (16 April 2013). "Quantum annealing with more than one hundred qubits". Nature Physics. 10 (3): 218–224. arXiv:1304.4595 . doi:10.1038/nphys2900.
35. Jump up^ "Lockheed Martin Signs Contract with D-Wave Systems".Retrieved 2011-05-25
36. Jump up^ "D-Wave quantum computer solves protein folding problem". nature.com.
37. Jump up^ "D-Wave uses quantum method to solve protein folding problem". phys.org.
38. Jump up^ "D-Wave Defies World of Critics With 'First Quantum Cloud' - WIRED". WIRED. 22 February 2012.
39. Jump up^ "The black box that could change the world". The Globe and Mail.
40. Jump up^ McGeoch, Catherine; Wang, Cong (May 2013). "Experimental Evaluation of an Adiabatic Quantum System for Combinatorial Optimization".
41. Jump up^ Aron, Jacob (8 March 2013). "Controversial quantum computer aces entanglement tests". New Scientist. Retrieved 14 May 2013.
42. Jump up^ Hardy, Quentin (16 May 2013). "Google Buys a Quantum Computer". Bits. The New York Times. Retrieved 3 June 2013.
43. Jump up^ The Future Of Quantum Computing: Vern Brownell, D-Wave CEO @ Compute Midwest on YouTube 4 December 2014
44. Jump up^ brian wang. "Next Big Future: Dwave Systems shows off quantum chip with 2048 physical qubits". nextbigfuture.com.
45. Jump up^ "D-Wave Announces D-Wave 2000Q Quantum Computer and First System Order | D-Wave Systems". www.dwavesys.com. Retrieved 2017-01-25.
46. Jump up^ D-Wave Systems, PDF, 01-2017, http://www.dwavesys.com/sites/default/files/D-Wave%202000Q%20Tech%20Collateral_0117F.pdf
47. Jump up^ "D-Wave 2000Q System to be Installed at Quantum Artificial Intelligence Lab Run by Google, NASA, and Universities Space Research Association". 2017-03-13.
48. Jump up^ "Digital pioneering work: Volkswagen uses quantum computers". 2017-03-13.
49. Jump up^ "Dwave sells 2000 qubit quantum annealing to Volkswagen, Virginia Tech and upgrades systems for NASA and Google". 2017-03-14.
50. Jump up^ "Shtetl-Optimized: D-Wave Easter Spectacular". 2007-04-07. Retrieved 2007-05-17.
51. Jump up^ "Quantum computing: In the 'death zone'?". Nature Physics. 3: 220–221. 2007-04-07. doi:10.1038/nphys585. Retrieved 2008-12-23.
52. Jump up^ Quantum annealing with manufactured spins Nature 473, 194–198, 12 May 2011
53. Jump up^ The CIA and Jeff Bezos Bet on Quantum ComputingTechnology Review October 4, 2012 by Tom Simonite
54. ^ Jump up to:^a b "Shtetl-Optimized". scottaaronson.com.
55. Jump up^ "Entanglement in a quantum annealing processor". prx. 2014-05-29.
56. Jump up^ "Shtetl-Optimized: The Orion Quantum Computer Anti-Hype FAQ". 2007-02-09. Retrieved 2007-05-17.
57. Jump up^ "Shtetl-Optimized". scottaaronson.com.
58. Jump up^ "Shtetl-Optimized: Thanksgiving Special: D-Wave at MIT". 2007-11-22. Retrieved 2007-12-03.
59. Jump up^ "In Defence of D-Wave".
60. Jump up^ "D-Wave: comment on comparison with classical computers". 2013-06-10. Retrieved 2013-06-20.
61. Jump up^ Shin, Seung Woo; Graeme Smith; John A. Smolin; Umesh Vazirani (28 January 2014). "How 'Quantum' is the D-Wave Machine?". arXiv:1401.7087  [quant-ph].
62. Jump up^ Walter Vinci, Tameem Albash, Anurag Mishra, Paul A. Warburton, Daniel A. Lidar "Distinguishing Classical and Quantum Models for the D-Wave Device" (17 Mar 2014) http://arxiv.org/abs/1403.4228
63. Jump up^ Lanting, T.; Przybysz, A. J.; Smirnov, A. Yu.; Spedalieri, F. M.; Amin, M. H.; Berkley, A. J.; Harris, R.; Altomare, F.; Boixo, S.; Bunyk, P.; Dickson, N.; Enderud, C.; Hilton, J. P.; Hoskinson, E.; Johnson, M. W.; Ladizinsky, E.; Ladizinsky, N.; Neufeld, R.; Oh, T.; Perminov, I.; Rich, C.; Thom, M. C.; Tolkacheva, E.; Uchaikin, S.; Wilson, A. B.; Rose, G. (2014). "Verification Required". aps.org. doi:10.1103/PhysRevX.4.021041.
64. Jump up^ Helmut Katzgraber, quoted in (Cho 2014).
65. Jump up^ Cho, Adrian (20 June 2014), "Quantum or not, controversial computer yields no speedup", Science, 344 (6190): 1330–1331, doi:10.1126/science.344.6190.1330, PMID 24948715.
66. Jump up^ Mohammad H. Amin, "Searching for quantum speedup in quasistatic quantum annealers" arXiv:1503.04216
67. Jump up^ Steiger, Damian; Heim, Bettina; Rønnow, Troels; Troyer, Matthias (October 22, 2015), "Performance of quantum annealing hardware", Electro-Optical and Infrared Systems: Technology and Applications XII; and Quantum Information Science and Technology, doi:10.1117/12.2202661
68. Jump up^ "Faculty | Prof Jacob Biamonte | Physics | University of Oxford". qubit.org. Retrieved 2013-09-04.
69. Jump up^ "Department staff | Dr Alexandre Zagoskin | Physics | Loughborough University". Lboro.ac.uk. Retrieved 2013-05-16.
70. Jump up^ "CrunchBase".

External links[edit]

• Official website
• "Announcement of the 16-qubit quantum computer demonstration". Jan 19, 2007.
• Quantum Computing Day 2: Image Recognition with an Adiabatic Quantum Computer on YouTube
• Karimi, Kamran; Dickson, Neil G.; et all (Jan 27, 2011). "Investigating the Performance of an Adiabatic Quantum Optimization Processor". arXiv:1006.4147  [quant-ph]. Theoretical performance of a D-Wave processor
• Ghosh, A.; Mukherjee, S. (Dec 2, 2013). "Quantum Annealing and Computation: A Brief Documentary Note". Science and Culture. 79: 485–500. arXiv:1310.1339 . Bibcode:2013arXiv1310.1339G.