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

Japanese Journal of Applied Physics

Efficient Quantum Computing Emulation System with Unitary Macro-Operations

Yosuke Goto, Minoru Fujishima

Published Apr 1, 2007• 7 citations
Publisher

Abstract

Quantum computing has attracted many research studies to solve non-deterministic polynomial (NP) problems at high speed. However, large-scale quantum computing has not been realized yet. In this study, a new emulation method is proposed, where qubits are replaced with classical bits that use unitary macro-operations, which are a combination of quantum operations at the principal stage of the quantum computing process for executing several-hundred-qubit operations in a large-scale emulation. As a result, a quantum computing emulator has been successfully fabricated, and a 64-bit factorization was demonstrated with only 40 kbits of classical memory, where 320 qubits are required with Shor's algorithm in a quantum computer.

DOI
10.1143/jjap.46.2278

Related papers

High-speed quantum-computing emulator utilizing a dedicated processor

Minoru Fujishima, Koichiro Hoh

A quantum computer is highly promising and widely studied since it enables a much higher calculation speed than current computers. Due to physical limitations, however, the current quantum computer can only solve much smaller scale problems than conventional computers. In order to process a large-scale problem at high speed, we have been studying a quantum computing emulator utilizing semiconductor memories. As a result, we have realized a dedicated processor that solves search problems, such as the satisfiability problem, at much higher speed than current computers. Consequently, without using "quantum process," the possibility of a quantum computer executing a large-scale problem is shown.

Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE•May 9, 2003•2 citations

Introduction to Quantum Computing

Nadia Nedjah, Luiza de Macedo Mourelle

This introduction presents an overview of the key concepts discussed in the subsequent chapters of this book. The book introduces the motivation and presents and comment on recent related works in the literature about the quantum computing emulation by hardware and simulation by software. The conventional electronic computer is a machine that performs logical and arithmetic operations sequentially and/or in parallel on data coded according to binary logic. Quantum Computing has been the target of several researches due to its potential for increasing the speed of processing through the use of algorithms with intrinsic parallelism, pointing out to the possibility of polynomial time solutions for NP-Complete problems. The book describes the macro-architecture of the proposed quantum processor and its interaction with the conventional host wherein it is embedded. It defines quantum state measurement and propose an efficient micro-architecture for the unit that is responsible for the state observation of the quantum bits, thus allowing for quantum bit measurements.

CRC Press eBooks•Jan 5, 2023•1 citation

Experimental Implementation of Shor's Quantum Algorithm to Break RSA

Aminah Albuainain, Jana Alansari, Samiyah Alrashidi +3 more

Nowadays, quantum computing is an important topic since it allows computations to be completed in a small amount of the time. The goal of using quantum computers (QC) is to solve an increasing number of problems that were previously intractable to address with traditional computing. The classical approaches work with bits, which are made up of 0s and 1s, whereas QC uses qubits. Classical computing is limited by storage capacity and speed of calculations, even when parallel computation is conducted on it. Compared to traditional methods, quantum parallelism allows the storage to be reduced exponentially with the potential of a shorter amount of time. Besides, Peter Shor's algorithm can solve the factorization problem used in RSA in polynomial time, whereas in a classical computer, factoring any big integer is intractable. The purpose of this research is to explore and implement quantum computing schemes and how Shor's algorithm can break RSA algorithms.

International Conference on Computational Intelligence and Communication Networks (CICN)•Dec 4, 2022•12 citations

FPGA-based high-speed emulator of quantum computing

Minoru Fujishima

Quantum computers are believed to perform high-speed calculations, compared with conventional computers. However, the quantum computer has inherent issues. Firstly, it solves NP (non-deterministic polynomial) problems at a high speed only when a periodic function can be used in the process of calculation. Secondly, it is extremely difficult to increase the problem scale to be solved, which is determined by the number of quantum bits. To overcome the restrictions stemming from the quantum algorithm, we are studying the emulation by a FPGA (field programmable gate array). In this paper, first, it is explained why a periodic function is required for the algorithm of a quantum computer. Then, it is shown that the hardware emulator can solve NP problems at a high speed without using a periodic function.

International Conference on Field-Programmable Technology (FPT)•Jun 30, 2004•25 citations

Parallel Quantum Computing Emulation

Brian R. La Cour, S. Andrew Lanham, Corey I. Ostrove

Quantum computers provide a fundamentally new computing paradigm that promises to revolutionize our ability to solve broad classes of problems. Surprisingly, the basic mathematical structures of gate-based quantum computing, such as unitary operations on a finite-dimensional Hilbert space, are not unique to quantum systems but may be found in certain classical systems as well. Previously, it has been shown that one can represent an arbitrary multi-qubit quantum state in terms of classical analog signals using nested quadrature amplitude modulated signals. Furthermore, using digitally controlled analog electronics one may manipulate these signals to perform quantum gate operations and thereby execute quantum algorithms. The computational capacity of a single signal is, however, limited by the required bandwidth, which scales exponentially with the number of qubits when represented using frequency-based encoding. To overcome this limitation, we introduce a method to extend this approach to multiple parallel signals. Doing so allows a larger quantum state to be emulated with the same gate time required for processing frequency-encoded signals. In the proposed representation, each doubling of the number of signals corresponds to an additional qubit in the spatial domain. Single quit gate operations are similarly extended so as to operate on qubits represented using either frequency-based or spatial encoding schemes. Furthermore, we describe a method to perform gate operations between pairs of qubits represented using frequency or spatial encoding or between frequency-based and spatially encoded qubits. Finally, we describe how this approach may be extended to represent qubits in the time domain as well.

arXiv:1908.06445•IEEE International Conference on Rebooting Computing (ICRC)•Nov 1, 2018•5 citations

High-speed processor for quantum-computing emulation and its applications

Minoru Fujishima, Keiji Saito, Masafumi Onouchi +1 more

A high-speed and large-scale processor dedicated to quantum computing is proposed, which has the minimum operation function needed for execution of a quantum algorithm. In this processor, the probability amplitudes determined by the states of the quantum bits in the quantum computer are described using only one bit, and we named it a logic quantum processor. It is found that for this processor an execution speed 275 times higher than that of a software simulation is obtained when the processor executing the quantum algorithm for 16 qubit has been implemented in a FPGA. As an example application, it is shown that the processor can solve the satisfiability problem and that it can also simulate the decoherence in the quantum computer at high speed.

IEEE International Symposium on Circuits and Systems proceedings•Nov 4, 2003•10 citations
Quantum computing has attracted many research studies to solve non-deterministic polynomial (NP) problems at high speed. However, large-scale quantum computing has not been realized yet. In this study, a new emulation method is proposed, where qubits are replaced with classical bits that use unitary macro-operations, which are a combination of quantum operations at the principal stage of the quantum computing process for executing several-hundred-qubit operations in a large-scale emulation. As a result, a quantum computing emulator has been successfully fabricated, and a 64-bit factorization was demonstrated with only 40 kbits of classical memory, where 320 qubits are required with Shor's algorithm in a quantum computer.
A quantum computer is highly promising and widely studied since it enables a much higher calculation speed than current computers. Due to physical limitations, however, the current quantum computer can only solve much smaller scale problems than conventional computers. In order to process a large-scale problem at high speed, we have been studying a quantum computing emulator utilizing semiconductor memories. As a result, we have realized a dedicated processor that solves search problems, such as the satisfiability problem, at much higher speed than current computers. Consequently, without using "quantum process," the possibility of a quantum computer executing a large-scale problem is shown.
This introduction presents an overview of the key concepts discussed in the subsequent chapters of this book. The book introduces the motivation and presents and comment on recent related works in the literature about the quantum computing emulation by hardware and simulation by software. The conventional electronic computer is a machine that performs logical and arithmetic operations sequentially and/or in parallel on data coded according to binary logic. Quantum Computing has been the target of several researches due to its potential for increasing the speed of processing through the use of algorithms with intrinsic parallelism, pointing out to the possibility of polynomial time solutions for NP-Complete problems. The book describes the macro-architecture of the proposed quantum processor and its interaction with the conventional host wherein it is embedded. It defines quantum state measurement and propose an efficient micro-architecture for the unit that is responsible for the state observation of the quantum bits, thus allowing for quantum bit measurements.
Nowadays, quantum computing is an important topic since it allows computations to be completed in a small amount of the time. The goal of using quantum computers (QC) is to solve an increasing number of problems that were previously intractable to address with traditional computing. The classical approaches work with bits, which are made up of 0s and 1s, whereas QC uses qubits. Classical computing is limited by storage capacity and speed of calculations, even when parallel computation is conducted on it. Compared to traditional methods, quantum parallelism allows the storage to be reduced exponentially with the potential of a shorter amount of time. Besides, Peter Shor's algorithm can solve the factorization problem used in RSA in polynomial time, whereas in a classical computer, factoring any big integer is intractable. The purpose of this research is to explore and implement quantum computing schemes and how Shor's algorithm can break RSA algorithms.
Quantum computers are believed to perform high-speed calculations, compared with conventional computers. However, the quantum computer has inherent issues. Firstly, it solves NP (non-deterministic polynomial) problems at a high speed only when a periodic function can be used in the process of calculation. Secondly, it is extremely difficult to increase the problem scale to be solved, which is determined by the number of quantum bits. To overcome the restrictions stemming from the quantum algorithm, we are studying the emulation by a FPGA (field programmable gate array). In this paper, first, it is explained why a periodic function is required for the algorithm of a quantum computer. Then, it is shown that the hardware emulator can solve NP problems at a high speed without using a periodic function.
Quantum computers provide a fundamentally new computing paradigm that promises to revolutionize our ability to solve broad classes of problems. Surprisingly, the basic mathematical structures of gate-based quantum computing, such as unitary operations on a finite-dimensional Hilbert space, are not unique to quantum systems but may be found in certain classical systems as well. Previously, it has been shown that one can represent an arbitrary multi-qubit quantum state in terms of classical analog signals using nested quadrature amplitude modulated signals. Furthermore, using digitally controlled analog electronics one may manipulate these signals to perform quantum gate operations and thereby execute quantum algorithms. The computational capacity of a single signal is, however, limited by the required bandwidth, which scales exponentially with the number of qubits when represented using frequency-based encoding. To overcome this limitation, we introduce a method to extend this approach to multiple parallel signals. Doing so allows a larger quantum state to be emulated with the same gate time required for processing frequency-encoded signals. In the proposed representation, each doubling of the number of signals corresponds to an additional qubit in the spatial domain. Single quit gate operations are similarly extended so as to operate on qubits represented using either frequency-based or spatial encoding schemes. Furthermore, we describe a method to perform gate operations between pairs of qubits represented using frequency or spatial encoding or between frequency-based and spatially encoded qubits. Finally, we describe how this approach may be extended to represent qubits in the time domain as well.
A high-speed and large-scale processor dedicated to quantum computing is proposed, which has the minimum operation function needed for execution of a quantum algorithm. In this processor, the probability amplitudes determined by the states of the quantum bits in the quantum computer are described using only one bit, and we named it a logic quantum processor. It is found that for this processor an execution speed 275 times higher than that of a software simulation is obtained when the processor executing the quantum algorithm for 16 qubit has been implemented in a FPGA. As an example application, it is shown that the processor can solve the satisfiability problem and that it can also simulate the decoherence in the quantum computer at high speed.