Also known as | Vesuvius |
---|---|
Developer | D-Wave Systems |
Manufacturer | D-Wave Systems |
Product family | D-Wave |
Type | Quantum computer |
CPU | Approximately 512-qubit (varies) |
Dimensions | 10 square metre room |
Predecessor | D-Wave One |
Successor | D-Wave 2X |
Website | www |
D-Wave Two (project code name Vesuvius) is the second commercially available quantum computer, and the successor to the first commercially available quantum computer, D-Wave One. Both computers were developed by Canadian company D-Wave Systems. [1] The computers are not general purpose, but rather are designed for quantum annealing. Specifically, the computers are designed to use quantum annealing to solve a single type of problem known as quadratic unconstrained binary optimization. [2] As of 2015, it was still debated whether large-scale entanglement takes place in D-Wave Two, and whether current or future generations of D-Wave computers will have any advantage over classical computers. [3] [4] [5] [6] [7] [8] [9]
D-Wave Two has a QPU (quantum processing unit) of 512 qubits—an improvement over the D-Wave One series' QPUs of about 128 qubits [10] The number of qubits can vary from chip to chip, due to variations in manufacturing. [11] The increase in qubit count for the D-Wave Two was accomplished by tiling qubit pattern of the D-Wave One. This pattern, named chimera by D-Wave Systems, has a limited connectivity such that a given qubit can only interact with at most six other qubits. [9] As with the D-Wave One, this restricted connectivity greatly limits the optimization problems that can be approached with the hardware. [11]
In March 2013, several groups of researchers at the Adiabatic Quantum Computing workshop at the Institute of Physics in London produced evidence of quantum entanglement in D-Wave CPUs. [12] In March 2014, researchers from University College London and the University of Southern California corroborated their findings; in their tests, the D-Wave Two exhibited the quantum physics outcome that it should while not showing three different classical physics outcomes. [13] [14]
In May 2013, Catherine McGeoch verified that D-Wave Two finds solutions to a synthetic benchmark set of Ising spin optimization problems.[ citation needed ] Boixo et al. (2014) evidenced that the D-Wave Two performs quantum annealing, [15] but that a simulated annealing on a notebook computer also performs well. [16] Jean Francois Puget of IBM compared computation on the D-Wave Two with IBM's CPLEX software. [17]
A D-Wave Two in the Quantum Artificial Intelligence Lab at the NASA Advanced Supercomputing Division of Ames Research Center is used. NASA, Google, and the Universities Space Research Association (USRA) started the lab in 2013. [18] [19] [20] [21]
In July 2016, computer music researcher Alexis Kirke used a harmony algorithm developed for the D-Wave Two [22] live in a public musical performance for mezzo-soprano and electronics in the UK. [23] [24]
In January 2021, a multi-institutional group of researches from ORNL, Purdue and D-Wave generated accurate results from materials science simulations on the DWave-2000Q processor that can be verified with neutron scattering experiments and other practical techniques. [25]
A quantum computer is a computer that takes advantage of quantum mechanical phenomena.
This is a timeline of quantum computing.
In quantum computing, a quantum algorithm is an algorithm which runs on a realistic model of quantum computation, the most commonly used model being the quantum circuit model of computation. A classical algorithm is a finite sequence of instructions, or a step-by-step procedure for solving a problem, where each step or instruction can be performed on a classical computer. Similarly, a quantum algorithm is a step-by-step procedure, where each of the steps can be performed on a quantum computer. Although all classical algorithms can also be performed on a quantum computer, the term quantum algorithm is usually used for those algorithms which seem inherently quantum, or use some essential feature of quantum computation such as quantum superposition or quantum entanglement.
Quantum information science is a field that combines the principles of quantum mechanics with information theory to study the processing, analysis, and transmission of information. It covers both theoretical and experimental aspects of quantum physics, including the limits of what can be achieved with quantum information. The term quantum information theory is sometimes used, but it does not include experimental research and can be confused with a subfield of quantum information science that deals with the processing of quantum information.
Superconducting quantum computing is a branch of solid state quantum computing that implements superconducting electronic circuits using superconducting qubits as artificial atoms, or quantum dots. For superconducting qubits, the two logic states are the ground state and the excited state, denoted respectively. Research in superconducting quantum computing is conducted by companies such as Google, IBM, IMEC, BBN Technologies, Rigetti, and Intel. Many recently developed QPUs use superconducting architecture.
Quantum programming is the process of designing or assembling sequences of instructions, called quantum circuits, using gates, switches, and operators to manipulate a quantum system for a desired outcome or results of a given experiment. Quantum circuit algorithms can be implemented on integrated circuits, conducted with instrumentation, or written in a programming language for use with a quantum computer or a quantum processor.
Quantum annealing (QA) is an optimization process for finding the global minimum of a given objective function over a given set of candidate solutions, by a process using quantum fluctuations. Quantum annealing is used mainly for problems where the search space is discrete with many local minima; such as finding the ground state of a spin glass or the traveling salesman problem. The term "quantum annealing" was first proposed in 1988 by B. Apolloni, N. Cesa Bianchi and D. De Falco as a quantum-inspired classical algorithm. It was formulated in its present form by T. Kadowaki and H. Nishimori in 1998 though an imaginary-time variant without quantum coherence had been discussed by A. B. Finnila, M. A. Gomez, C. Sebenik and J. D. Doll in 1994.
D-Wave Quantum Systems Inc. is a Canadian quantum computing company, based in Burnaby, British Columbia. D-Wave claims to be the world's first company to sell computers that exploit quantum effects in their operation. D-Wave's early customers include Lockheed Martin, University of Southern California, Google/NASA and Los Alamos National Lab.
Adiabatic quantum computation (AQC) is a form of quantum computing which relies on the adiabatic theorem to perform calculations and is closely related to quantum annealing.
Hartmut Neven is a scientist working in quantum computing, computer vision, robotics and computational neuroscience. He is best known for his work in face and object recognition and his contributions to quantum machine learning. He is currently Vice President of Engineering at Google where he is leading the Quantum Artificial Intelligence Lab which he founded in 2012.
Scott Joel Aaronson is an American theoretical computer scientist and David J. Bruton Jr. Centennial Professor of Computer Science at the University of Texas at Austin. His primary areas of research are quantum computing and computational complexity theory.
Quantum machine learning is the integration of quantum algorithms within machine learning programs.
The USC-Lockheed Martin Quantum Computing Center (QCC) is a joint scientific research effort between Lockheed Martin Corporation and the University of Southern California (USC). The QCC is housed at the Information Sciences Institute (ISI), a computer science and engineering research unit of the USC Viterbi School of Engineering, and is jointly operated by ISI and Lockheed Martin.
IBM Quantum Platform is an online platform allowing public and premium access to cloud-based quantum computing services provided by IBM. This includes access to a set of IBM's prototype quantum processors, a set of tutorials on quantum computation, and access to an interactive textbook. As of February 2021, there are over 20 devices on the service, six of which are freely available for the public. This service can be used to run algorithms and experiments, and explore tutorials and simulations around what might be possible with quantum computing.
Cloud-based quantum computing is the invocation of quantum emulators, simulators or processors through the cloud. Increasingly, cloud services are being looked on as the method for providing access to quantum processing. Quantum computers achieve their massive computing power by initiating quantum physics into processing power and when users are allowed access to these quantum-powered computers through the internet it is known as quantum computing within the cloud.
In quantum computing, quantum supremacy or quantum advantage is the goal of demonstrating that a programmable quantum computer can solve a problem that no classical computer can solve in any feasible amount of time, irrespective of the usefulness of the problem. The term was coined by John Preskill in 2012, but the concept dates back to Yuri Manin's 1980 and Richard Feynman's 1981 proposals of quantum computing.
Sycamore is a transmon superconducting quantum processor created by Google's Artificial Intelligence division. It has 53 qubits.
John M. Martinis is an American physicist and a professor of physics at the University of California, Santa Barbara. In 2014, the Google Quantum A.I. Lab announced that it had hired Martinis and his team in a multimillion dollar deal to build a quantum computer using superconducting qubits.
Sergio Boixo has degrees in computer engineering, philosophy, mathematics, and master and PhD in physics, and is best known for his work on quantum computing. He is currently working as Chief Scientist Quantum Computer Theory for Google's Quantum Artificial Intelligence Lab, a team he joined in 2013, shortly after its foundation.
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