Challenges
Datasets
Workspaces
Papers
Discussions
Leaderboard
Log inSign up
Challenges
Datasets
Workspaces
Papers
Discussions
Leaderboard
Blog
Job Board
Q3AS

© 2026 Aqora Quantum S.A.S.

TermsPrivacyLegal Notice

WIT transactions on information and communication technologies

A hardware accelerator approach for quantum computer modeling

Vyacheslav F. Guzik, Sergey M. Gushanskiy, Кубраков Евгений Сергеевич

Published Apr 1, 2014• 0 citations
Publisher
DOI
10.2495/icte130471

Related papers

Моделирование квантовых вычислений с использованием аппаратного вычислительного ядра

Гушанский Сергей Михайлович, Переверзев Владимир Андреевич

This article discusses the principles of quantum computing simulation using hardware approach. We describe a general mathematical model of a quantum computer; we show the method of mathematical modeling of quantum computation with optimization and a scheme of a hardware processing core in a quantum computing accelerator. The article gives a method of assessment of increasing productivity in the simulation of quantum computations using computing hardware core. The problems associated with the parallelization of computations on a hardware accelerator, simulating quantum computing were analyzed. The work lists the results of comparison of software and hardware simulation, as well as the dependence of the temporal evaluation of the number of qubits and parallel ALU in the computer-hardware accelerator

Политематический сетевой электронный научный журнал Кубанского государственного аграрного университета•Jan 1, 2016•0 citations

Hardware for Quantum Computing

Chuck Easttom

Springer eBooks•Jan 1, 2024•5 citations

Quantum Computing for Computer Architects

Tzvetan S. Metodi, Frederic T. Chong

Synthesis lectures on computer architecture•Jan 1, 2006•9 citations

Аппаратный подход к моделированию квантовых вычислений с использованием алгоритма оптимизации

Гузик Вячеслав Филиппович, Гушанский Сергей Михайлович, Кубраков Евгений Сергеевич

A hardware approach for the quantum computing modeling was considered. A common mathematical model of the quantum computer was described; a methodic of mathematical modeling of the quantum computing was shown. During the mathematical methodic description the most resource-intensive parts of the model are allocated. Considered questions connected with data parallelizing with a hardware accelerator, which is used for quantum computer modeling. A common scheme of the accelerator’s work algorithm was shown. Suggested more compact data format for accelerator implementation, that will reduce time costs spent by elementary arithmetic operations. Proposed the use of the optimization algorithm for data minimization during the calculations in the phase of transforming model of quantum register with quantum gates in quantum computer simulators. Shown results of optimization algorithm execution and compared results with classic mathematical approach.

Известия Южного федерального университета. Технические науки•Jan 1, 2014•0 citations

Developing a Hardware Approach to Simulating Quantum Computing Using an Optimization Algorithm

Пуховский Валерий Николаевич, Sergey M. Gushanskiy, Viktor Potapov

In the past few decades, there has been an acute problem of creating a quantum computer that uses quantum mechanical effects such as quantum parallelism and quantum entanglement for computations. Using these mechanisms, the quantum computer is able to solve some of the NP-class problems in polynomial time. A hardware approach to modeling quantum computing is considered, and a general mathematical model of the operation of a quantum computer is described, and a technique for mathematical modeling of quantum computing is presented. At the stage of consideration of the method of mathematical modeling, the most resource-intensive parts of the model are indicated. Also, issues related to data parallelization on a hardware accelerator, which are planned to be used to simulate quantum computing, were considered, and algorithms for the operation of this type of accelerator were given. A more compact data format is proposed, which is recommended to be used when implementing the accelerator. Using the proposed format, it is possible to reduce the resources spent on elementary arithmetic operations. The possibility of introducing an optimization algorithm to minimize the time spent in computations, as well as to speed up the execution of quantum algorithms in simulators of a quantum computer at the stage of the effect of quantum gates on the quantum register model, is proposed. The results of the optimization algorithm and its comparison with the classical mathematical approach using a software model are presented.

Panhellenic Conference on Informatics•Nov 26, 2021•1 citation

Quantum Computing for Computer Architects

Tzvetan S. Metodi, Frederic T. Chong

Synthesis lectures on computer architecture•Jan 1, 2006•60 citations
This article discusses the principles of quantum computing simulation using hardware approach. We describe a general mathematical model of a quantum computer; we show the method of mathematical modeling of quantum computation with optimization and a scheme of a hardware processing core in a quantum computing accelerator. The article gives a method of assessment of increasing productivity in the simulation of quantum computations using computing hardware core. The problems associated with the parallelization of computations on a hardware accelerator, simulating quantum computing were analyzed. The work lists the results of comparison of software and hardware simulation, as well as the dependence of the temporal evaluation of the number of qubits and parallel ALU in the computer-hardware accelerator
A hardware approach for the quantum computing modeling was considered. A common mathematical model of the quantum computer was described; a methodic of mathematical modeling of the quantum computing was shown. During the mathematical methodic description the most resource-intensive parts of the model are allocated. Considered questions connected with data parallelizing with a hardware accelerator, which is used for quantum computer modeling. A common scheme of the accelerator’s work algorithm was shown. Suggested more compact data format for accelerator implementation, that will reduce time costs spent by elementary arithmetic operations. Proposed the use of the optimization algorithm for data minimization during the calculations in the phase of transforming model of quantum register with quantum gates in quantum computer simulators. Shown results of optimization algorithm execution and compared results with classic mathematical approach.
In the past few decades, there has been an acute problem of creating a quantum computer that uses quantum mechanical effects such as quantum parallelism and quantum entanglement for computations. Using these mechanisms, the quantum computer is able to solve some of the NP-class problems in polynomial time. A hardware approach to modeling quantum computing is considered, and a general mathematical model of the operation of a quantum computer is described, and a technique for mathematical modeling of quantum computing is presented. At the stage of consideration of the method of mathematical modeling, the most resource-intensive parts of the model are indicated. Also, issues related to data parallelization on a hardware accelerator, which are planned to be used to simulate quantum computing, were considered, and algorithms for the operation of this type of accelerator were given. A more compact data format is proposed, which is recommended to be used when implementing the accelerator. Using the proposed format, it is possible to reduce the resources spent on elementary arithmetic operations. The possibility of introducing an optimization algorithm to minimize the time spent in computations, as well as to speed up the execution of quantum algorithms in simulators of a quantum computer at the stage of the effect of quantum gates on the quantum register model, is proposed. The results of the optimization algorithm and its comparison with the classical mathematical approach using a software model are presented.