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Информационно-управляющие системы

Логическое проектирование и квантовый вызов

V. I. Varshavskii

Published Jan 1, 2005• 0 citations
OpenAlex

Abstract

Is the design methodology of logical and computing structures ready to efficiently use new functional possibilities of quantum devices? Does the range of existing and suggested quantum devices provide effective design of logical and computing structures? With some examples, we discuss the possibility of obtaining positive answers to these questions uniting the efforts of physicists, technologists and experts in computer engineering. The paper indicates some directions where such collaboration may prove to be productive.

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Is the design methodology of logical and computing structures ready to efficiently use new functional possibilities of quantum devices? Does the range of existing and suggested quantum devices provide effective design of logical and computing structures? With some examples, we discuss the possibility of obtaining positive answers to these questions uniting the efforts of physicists, technologists and experts in computer engineering. A number of hot points is outlined where this collaboration may be fruitful.

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Arising from a special session held at the 2010 North American Annual Meeting of the Association for Symbolic Logic, this volume is an international cross-disciplinary collaboration with contributions from leading experts exploring connections across their respective fields. Themes range from philosophical examination of the foundations of physics and quantum logic, to exploitations of the methods and structures of operator theory, category theory, and knot theory in an effort to gain insight into the fundamental questions in quantum theory and logic. The book will appeal to researchers and students working in related fields, including logicians, mathematicians, computer scientists, and physicists. A brief introduction provides essential background on quantum mechanics and category theory, which, together with a thematic selection of articles, may also serve as the basic material for a graduate course or seminar.

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ПЕРСПЕКТИВЫ РАЗВИТИЯ КВАНТОВЫХ КОМПЬЮТЕРОВ И ИХ ВЛИЯНИЕ НА СОВРЕМЕННУЮ НАУКУ И ТЕХНИКУ

E.V. Kharin, M.N.A. Azman

Quantum computers are one of the most interesting and promising areas of modern information technology. With their help, solving complex problems is performed several times faster than on traditional computers. The development of this technology allows not only to expand the boundaries of computing, but also to revise all areas of scientific research in a new way. This article analyzes the theoretical foundations of quantum computers, the level of their development, prospects, and influence on modern science and technology.

ВЕСТНИК КАРАГАНДИНСКОГО ГОСУДАРСТВЕННОГО ИНДУСТРИАЛЬНОГО УНИВЕРСИТЕТА•Mar 12, 2026•0 citations

The Square Root of NOT

Brian Hayes

Digital computers are built out of circuits that have definite, discrete states: on or off, zero or one, high voltage or low voltage. Engineers go to great lengths to make sure these circuits never settle into some intermediate condition. Quantum-mechanical systems, as it happens, offer a guarantee of discreteness without any engineering effort at all. When you measure the spin orientation of an electron, for example, it is always either "up " or "down, " never in between. Likewise an atom gains or loses energy by making a "quantum jump" between specific energy states, without passing through intermediate energy levels. So why not build a digital computer out of quantum-mechanical devices, letting particle spins or the energy levels of atoms stand for binary units of information? One answer to this "Why not? " question is that you can't avoid building a quantum-mechanical computer even if you try. Since quantum mechanics appears to be a true theory of nature, it governs all physical systems, including the transistors and other components of the computer on your desk. All the same, quantum effects are seldom evident in electronic devices; components and circuits are designed so that the quantum states of many millions of electrons are averaged together, blurring their discreteness. In a quantum computer, the basic working parts would probably have to be individual electrons or atoms, and so another answer to the "Why not?" question is that building such a machine is simply beyond our skills. And

American Scientist•Jul 1, 1995•6 citations

Физические основы и проблемы технической реализации квантового компьютера

Вахний Татьяна Владимировна, Гуц Александр Константинович

The review of different approaches to creation of the quantum computer is given. The main problems of technical realization and prospect of each of approaches are discussed. It is paid attention to researches of behavior of quantum computers by means of the simulators which are based on classical computers.

Matematičeskie struktury i modelirovanie•Jan 1, 2011•0 citations

Quantum Learning Speed-up with Classical Training Data

Joong-Sung Lee, Jeongho Bang, Sunghyuk Hong +4 more

The primary question in the emerging field of machine learning (QML) is: can we achieve speed-up of machine learning? and/or what and how the effects contribute to the speed-up? The positive answers to such questions have recently been provided, for example, by the support vector machine (QSVM) which classifies many data vectors exponentially fast. However, to realize such an exponential learning speed-up, it is demanded to develop full-scale computer with a specific device, so-called quantum random access memory (QRAM)---which stores the classical big data, extremely fast, in the novel form of being quantum-mechanically superposed. Therefore, another question now arises: is it possible to attain learning speed-up even with the classical training data, and hence, requiring no full-scale computer and QRAM? To seek a satisfactory answer to this question, we consider a binary classification learning where the classicality of the training data are preserved. We then focus on a small unit structure for whole classification task, in which the minimum achievable learning speed-up would be exhibited. We provide the analysis and proof-of-principle experimental validation of a certain degree of learning speed-up in such a small unit, advocating an affirmative answer to the aforementioned main question. Through further investigation, it is also shown that our QML scheme is quite robust against the decoherence.

•Jun 5, 2017•0 citations
Is the design methodology of logical and computing structures ready to efficiently use new functional possibilities of quantum devices? Does the range of existing and suggested quantum devices provide effective design of logical and computing structures? With some examples, we discuss the possibility of obtaining positive answers to these questions uniting the efforts of physicists, technologists and experts in computer engineering. The paper indicates some directions where such collaboration may prove to be productive.
Is the design methodology of logical and computing structures ready to efficiently use new functional possibilities of quantum devices? Does the range of existing and suggested quantum devices provide effective design of logical and computing structures? With some examples, we discuss the possibility of obtaining positive answers to these questions uniting the efforts of physicists, technologists and experts in computer engineering. A number of hot points is outlined where this collaboration may be fruitful.
Arising from a special session held at the 2010 North American Annual Meeting of the Association for Symbolic Logic, this volume is an international cross-disciplinary collaboration with contributions from leading experts exploring connections across their respective fields. Themes range from philosophical examination of the foundations of physics and quantum logic, to exploitations of the methods and structures of operator theory, category theory, and knot theory in an effort to gain insight into the fundamental questions in quantum theory and logic. The book will appeal to researchers and students working in related fields, including logicians, mathematicians, computer scientists, and physicists. A brief introduction provides essential background on quantum mechanics and category theory, which, together with a thematic selection of articles, may also serve as the basic material for a graduate course or seminar.
Quantum computers are one of the most interesting and promising areas of modern information technology. With their help, solving complex problems is performed several times faster than on traditional computers. The development of this technology allows not only to expand the boundaries of computing, but also to revise all areas of scientific research in a new way. This article analyzes the theoretical foundations of quantum computers, the level of their development, prospects, and influence on modern science and technology.
Digital computers are built out of circuits that have definite, discrete states: on or off, zero or one, high voltage or low voltage. Engineers go to great lengths to make sure these circuits never settle into some intermediate condition. Quantum-mechanical systems, as it happens, offer a guarantee of discreteness without any engineering effort at all. When you measure the spin orientation of an electron, for example, it is always either "up " or "down, " never in between. Likewise an atom gains or loses energy by making a "quantum jump" between specific energy states, without passing through intermediate energy levels. So why not build a digital computer out of quantum-mechanical devices, letting particle spins or the energy levels of atoms stand for binary units of information? One answer to this "Why not? " question is that you can't avoid building a quantum-mechanical computer even if you try. Since quantum mechanics appears to be a true theory of nature, it governs all physical systems, including the transistors and other components of the computer on your desk. All the same, quantum effects are seldom evident in electronic devices; components and circuits are designed so that the quantum states of many millions of electrons are averaged together, blurring their discreteness. In a quantum computer, the basic working parts would probably have to be individual electrons or atoms, and so another answer to the "Why not?" question is that building such a machine is simply beyond our skills. And
The primary question in the emerging field of machine learning (QML) is: can we achieve speed-up of machine learning? and/or what and how the effects contribute to the speed-up? The positive answers to such questions have recently been provided, for example, by the support vector machine (QSVM) which classifies many data vectors exponentially fast. However, to realize such an exponential learning speed-up, it is demanded to develop full-scale computer with a specific device, so-called quantum random access memory (QRAM)---which stores the classical big data, extremely fast, in the novel form of being quantum-mechanically superposed. Therefore, another question now arises: is it possible to attain learning speed-up even with the classical training data, and hence, requiring no full-scale computer and QRAM? To seek a satisfactory answer to this question, we consider a binary classification learning where the classicality of the training data are preserved. We then focus on a small unit structure for whole classification task, in which the minimum achievable learning speed-up would be exhibited. We provide the analysis and proof-of-principle experimental validation of a certain degree of learning speed-up in such a small unit, advocating an affirmative answer to the aforementioned main question. Through further investigation, it is also shown that our QML scheme is quite robust against the decoherence.