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A quantum computer is a computer that exploits quantum mechanical phenomena. At small scales, physical matter exhibits properties of both particles and waves, and quantum computing leverages this behavior using specialized hardware. Classical physics cannot explain the operation of these quantum devices, and a scalable quantum computer could perform some calculations exponentially faster than any modern "classical" computer. In particular, a large-scale quantum computer could break widely-used encryption schemes and aid physicists in performing physical simulations; however, the current state of the art is still largely experimental and impractical.
Simulated annealing (SA) is a probabilistic technique for approximating the global optimum of a given function. Specifically, it is a metaheuristic to approximate global optimization in a large search space for an optimization problem. It is often used when the search space is discrete. For problems where finding an approximate global optimum is more important than finding a precise local optimum in a fixed amount of time, simulated annealing may be preferable to exact algorithms such as gradient descent or branch and bound.
This is a timeline of quantum computing.
In computer science and mathematical optimization, a metaheuristic is a higher-level procedure or heuristic designed to find, generate, tune, or select a heuristic that may provide a sufficiently good solution to an optimization problem or a machine learning problem, especially with incomplete or imperfect information or limited computation capacity. Metaheuristics sample a subset of solutions which is otherwise too large to be completely enumerated or otherwise explored. Metaheuristics may make relatively few assumptions about the optimization problem being solved and so may be usable for a variety of problems.
The Fannie and John Hertz Foundation is an American non-profit organization that awards fellowships to Ph.D. students in the applied physical, biological and engineering sciences. The fellowship provides $250,000 of support over five years. The goal is for Fellows to be financially independent and free from traditional restrictions of their academic departments in order to promote innovation in collaboration with leading professors in the field. Through a rigorous application and interview process, the Hertz Foundation seeks to identify young scientists and engineers with the potential to change the world for the better and supports their research endeavors from an early stage. Fellowship recipients pledge to make their skills available to the United States in times of national emergency.
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 "Quantum annealing in the transverse Ising model" 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 "Quantum annealing is a new method for minimizing multidimensional functions".
Stochastic optimization (SO) methods are optimization methods that generate and use random variables. For stochastic problems, the random variables appear in the formulation of the optimization problem itself, which involves random objective functions or random constraints. Stochastic optimization methods also include methods with random iterates. Some stochastic optimization methods use random iterates to solve stochastic problems, combining both meanings of stochastic optimization. Stochastic optimization methods generalize deterministic methods for deterministic problems.
D-Wave Systems Inc. is a Canadian quantum computing company, based in Burnaby, British Columbia, Canada. D-Wave was the world's first company to sell computers to 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 do calculations and is closely related to quantum annealing.
Daniel Amihud Lidar is the holder of the Viterbi Professorship of Engineering at the University of Southern California, where he is a Professor of Electrical Engineering, Chemistry, Physics & Astronomy. He is the Director and co-founder of the USC Center for Quantum Information Science & Technology (CQIST) as well as Scientific Director of the USC-Lockheed Martin Quantum Computing Center, notable for his research on control of quantum systems and quantum information processing.
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.
Lateral computing is a lateral thinking approach to solving computing problems. Lateral thinking has been made popular by Edward de Bono. This thinking technique is applied to generate creative ideas and solve problems. Similarly, by applying lateral-computing techniques to a problem, it can become much easier to arrive at a computationally inexpensive, easy to implement, efficient, innovative or unconventional solution.
Bikas Kanta Chakrabarti (born 14 December 1952 in Kolkata is an Indian physicist. Since January 2018, he is emeritus professor of physics at the Saha Institute of Nuclear Physics, Kolkata, India.
D-Wave Two 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. 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. 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.
Quantum machine learning is the integration of quantum algorithms within machine learning programs. The most common use of the term refers to machine learning algorithms for the analysis of classical data executed on a quantum computer, i.e. quantum-enhanced machine learning. While machine learning algorithms are used to compute immense quantities of data, quantum machine learning utilizes qubits and quantum operations or specialized quantum systems to improve computational speed and data storage done by algorithms in a program. This includes hybrid methods that involve both classical and quantum processing, where computationally difficult subroutines are outsourced to a quantum device. These routines can be more complex in nature and executed faster on a quantum computer. Furthermore, quantum algorithms can be used to analyze quantum states instead of classical data. Beyond quantum computing, the term "quantum machine learning" is also associated with classical machine learning methods applied to data generated from quantum experiments, such as learning the phase transitions of a quantum system or creating new quantum experiments. Quantum machine learning also extends to a branch of research that explores methodological and structural similarities between certain physical systems and learning systems, in particular neural networks. For example, some mathematical and numerical techniques from quantum physics are applicable to classical deep learning and vice versa. Furthermore, researchers investigate more abstract notions of learning theory with respect to quantum information, sometimes referred to as "quantum learning theory".
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.
Robert J. Schoelkopf III is an American physicist, most noted for his work on quantum computing as one of the inventors of superconducting qubits. Schoelkopf's main research areas are quantum transport, single-electron devices, and charge dynamics in nanostructures. His research utilizes quantum-effect and single-electron devices, both for fundamental physical studies and for applications. Techniques often include high-speed, high-sensitivity measurements performed on nanostructures at low temperatures. Schoelkopf serves as director of the Yale Center for Microelectronic Materials and Structures and as associate director of the Yale Institute for Nanoscience and Quantum Engineering. Since 2014, Schoelkopf is also the Director of the Yale Quantum Institute.
Florian Neukart is an Austrian business executive, computer scientist, physicist, and scientific author known for his work in quantum computing and artificial intelligence. He has primarily been working on utilizing quantum computers, artificial intelligence, and related technologies for solving industry problems. In his work on artificial intelligence, he describes methods for interpreting signals in the human brain in combination with paradigms from artificial intelligence to create artificial conscious entities.
Wolfgang Lechner is a theoretical physicist from Austria. He is the co-founder and co-CEO of the company ParityQC and professor at the Institute for Theoretical Physics of the University of Innsbruck.
References
- ↑ "Scott Kirkpatrick - Google Scholar". Google Scholar. Retrieved 11 November 2019.
- ↑ Reed Business Information (9 June 1983). New Scientist. Reed Business Information. pp. 697–. ISSN 0262-4079.
{{cite book}}:|author=has generic name (help) - ↑ Ray, Tiernan. "Is the world ready for cross-platform quantum programming?". ZDNet. Retrieved 8 March 2020.