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2024 International Conference on quantum computing and Engineering

作者： Kimura, Yusuke Li, Shaowen Sato, Hiroyuki Fujita, Masahiro Fujitsu Ltd Kawasaki Kanagawa Japan Univ Tokyo Bunkyo City Japan

ISBN: (纸本)9798331541378

To efficiently develop algorithms for quantum computers, a quantum simulator capable of handling many qubits at high speed is essential. However, a state vector-based simulator needs to store a vector of length 2(N) for N qubits. In today's typical desktop computing environment, a maximum of around 30 qubits can be handled. A decision diagram-based simulator is expected to solve the problem of memory requirement for some set of quantum algorithms. Decision diagram stores state vectors as graphs, which may significantly reduce memory usage in the presence of regularities in the state vector. In this study, we have implemented our decision diagram-based quantum simulator and conducted experiments using various algorithms to compare with the state vector-based simulator. Algorithms such as Grover and Shor show significant speedup and superiority of performance for larger numbers of qubits, whereas random circuits with many parameterized rotation gates show slower performance. As described above, researchers should understand the characteristics of simulators so that quantum algorithms can be developed more efficiently.

关键词： quantum Computer quantum computing simulation Decision Diagram State Vector simulation

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Fast and scalable quantum computing simulation on multi-core and many-core platforms

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quantum INFORMATION PROCESSING 2023年第5期22卷 215-215页

作者： Ahmadzadeh, Armin Sarbazi-Azad, Hamid Sharif Univ Technol Int Campus Kish Isl Iran Sharif Univ Technol Tehran Iran Inst Res Fundamental Sci IPM Tehran Iran

quantum computing is an emerging and promising computational paradigm that provides substantial speedup for a variety of tasks such as integer factorization, database search, and machine learning. One of the quantum computation features is the possibility of developing quantum algorithms, which could be faster than algorithms developed for classic computers. However, we are still unable to fully realize a physical quantum computer and depend on traditional computers to simulate their behavior and test quantum algorithms. This is a source of complexity since one of the challenges to simulate quantum algorithms is the exponential memory requirement. In this work, we propose a method to distribute the computation load of the simulation process between CPU and GPU to decrease the required memory and computation time. In this approach, we employ a hybrid platform, which simulates the quantum circuit in two phases using parallel array-based and recursive manners. The experimental results demonstrate speedups of 50X over the recursive method implemented on a GPU and 2.9X over the state vector method running on a multi-core CPU. Our approach is more than 10X energy-efficient for simulating 39 qubits compared to the GPU state-of-the-art technique. All in all, this approach is able to simulate more qubits over state-of-the-art GPU approaches and can be used to analyze and simulate large quantum circuits with a low-cost system instead of an expensive supercomputer.

关键词： GPU Many-core quantum computing simulation

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Cache Blocking Technique to Large Scale quantum computing simulation on Supercomputers

Cache Blocking Technique to Large Scale Quantum Computing Si...

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IEEE International Conference on quantum computing and Engineering (QCE)

作者： Doi, Jun Horii, Hiroshi IBM Res Tokyo IBM Quantum Tokyo Japan

ISBN: (纸本)9781728189697

Classical computers require large memory resources and computational power to simulate quantum circuits with a large number of qubits. Even supercomputers that can store huge amounts of data face a scalability issue in regard to parallel quantum computing simulations because of the latency of data movements between distributed memory spaces. Here, we apply a cache blocking technique by inserting swap gates in quantum circuits to decrease data movements. We implemented this technique in the open source simulation framework Qiskit Aer. We evaluated our simulator on GPU clusters and observed good scalability.

关键词： quantum computing simulation Cache blocking parallel computing GPGPU GPU Thrust MPI

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quantum computing simulation through reduction and decomposition optimizations with a case study of Shor's algorithm

Quantum computing simulation through reduction and decomposi...

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12th International Workshop on Java Technologies for Real-Time and Embedded Systems (JTRES)

作者： de Avila, Anderson B. Reiser, Renata H. S. Pilla, Mauricio L. Univ Fed Pelotas Grad Program Comp Sci R Gomes Carneiro 1 BR-19601061 Pelotas RS Brazil

Because of the expansion of transformations and read/write memory states by tensor products in multidimensional quantum applications, the exponential increase in temporal and spatial complexities constitutes one of the main challenges for quantum computing simulations. simulation of these systems is very relevant to develop and test new quantum algorithms. In order to overcome the increase in simulation complexity, this work presents reduction and decomposition optimizations for the Distributed Geometric Machine environment. By exploring properties as the sparsity of the Identity operator and partiality of dense unitary transformations, better storage and distribution of quantum information are achieved. The main improvements are reached by decreasing replication and void elements inherited from quantum operators. In the evaluation of this proposal, Hadamard transformations from 21 to 28 qubits and quantum Fourier Transforms from 26 to 28 qubits were simulated over CPU, sequentially and in parallel, and in graphics processing unit, showing reduced temporal complexity and, consequently, shorter simulation time. Moreover, evaluations of the Shor's algorithm considering 2n+3 qubits in the order-finding quantum algorithm were simulated up to 25 qubits. When comparing our implementations running on the same hardware with language-integrated quantum operation, academic release version, our new simulator was faster and allowed for the simulation of more qubits. Copyright (c) 2016 John Wiley & Sons, Ltd.

关键词： quantum computing simulation parallel processing GPU Shor's algorithm

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quantum computing simulation through reduction and decomposition optimizations with a case study of Shor's algorithm

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CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE 2017年第22期29卷 e3961.1-e3961.14页

作者： de Avila, Anderson B. Reiser, Renata H. S. Pilla, Mauricio L. Univ Fed Pelotas Grad Program Comp Sci R Gomes Carneiro 1 BR-19601061 Pelotas RS Brazil

关键词： quantum computing simulation parallel processing GPU Shor's algorithm

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Improving in situ GPU simulation of quantum computing in the D-GM environment

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INTERNATIONAL JOURNAL OF HIGH PERFORMANCE computing APPLICATIONS 2019年第3期33卷 462-472页

作者： Avila, Anderson Sander Reiser, Renata Hax Pilla, Mauricio Lima Yamin, Adenauer Correa Univ Fed Pelotas UFPEL PPGC CDTEC R Gomes Carneiro 1 BR-96010610 Pelotas RS Brazil

Exponential increase and global access to read/write memory states in quantum computing (QC) simulation limit both the number of qubits and quantum transformations which can be currently simulated. Although QC simulation is parallel by nature, spatial and temporal complexity are major performance hazards, making this a nontrivial application for high performance computing. A new methodology employing reduction and decomposition optimizations has shown relevant results, but its GPU implementation could be further improved. In this work, we develop a new kernel for in situ GPU simulation that better explores its resources without requiring further hardware. Shor's and Grover's algorithms are simulated up to 25 and 21 qubits respectively and compared to our previous version, to LIQUi|'s simulator and to ProjectQ framework, showing better results with relative speedups up to 4.38x, 3357.76x and 333x respectively.

关键词： In situ computing high performance computing quantum computing simulation applications of HPC GPU computing

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Unitary mechanical metamaterials with embedded one-qubit logic

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EXTREME MECHANICS LETTERS 2025年 77卷

作者： Karpov, Eduard G. Rahman, Kazi A. Univ Illinois Dept Civil Mat &Environm Engn Chicago IL 60607 USA

A class of lattice metamaterials characterized by a transfer matrix that updates polarization of a static sinusoidal displacement wave along a material coordinate in accordance with a unitary transformation is conceptualized. Specific material designs are discussed where the unitary transfer matrix takes the forms of the commonly used one-qubit quantum gates, such as the Pauli-X, Hadamard and others, depending on the unit cell geometry. Also, polarization parameters of the displacement wave are shown to form a Pauli spinor, a two-component complex vector representing the qubit state. Unitary metamaterials can be realized in practice as certain planar structures, or 3D lattices in a state of deformation similar to the continuum plain strain. Their potential application in human-scale mechanical platforms for simulating the quantum computation logic is discussed.

关键词： Lattice mechanics Mechanical metamaterials quantum computing simulation

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Towards quantum Circuit Emulation on Low -Tier FPGAs 5

Towards Quantum Circuit Emulation on Low -Tier FPGAs

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2024 International Conference on quantum computing and Engineering

作者： Conti, Christian Volpe, Deborah Cirillo, Giovanni Amedeo GrazianoT, Mariagrazia Zamboni, Maurizio Turvani, Giovanna Politecnico Torino Italy Dept Elctron & Telecommun Turin Italy Politecnico Torino Italy Dept Appl Sci & Technol Turin Italy

ISBN: (纸本)9798331541378

Researchers and industries are increasingly drawn to quantum computing for its computational potential. However, validating new quantum algorithms is challenging due to current quantum device limitations. Software simulators are time and memory -intensive, making hardware emulators an attractive alternative. This article introduces a digital architecture, designed to emulate quantum computing on low -tier Field -Programmable Gate Arrays (FPGAs), supporting Clifford+T and rotational gate sets. It simplifies and accelerates quantum algorithm verification using a RISC -like structure and efficiently handling sparse quantum gates. A dedicated compiler translates OpenQASM 2.0 into RISC -like instructions. The architecture is validated against the Qiskit state vector simulator, successfully emulating sixteen qubits on a Xilinx Kria KV260 SoM.

关键词： quantum computing Emulation Field Programmable Gate Array quantum Algorithm Verification quantum computing simulation

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AMARETTO: Enabling Efficient quantum Algorithm Emulation on Low-Tier FPGAs 31

AMARETTO: Enabling Efficient Quantum Algorithm Emulation on ...

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31st Conference on Electronics Circuits and Systems

作者： Conti, Christian Volpe, Deborah Graziano, Mariagrazia Zamboni, Maurizio Turvani, Giovanna Politecn Torino Turin Italy

ISBN: (纸本)9798350377217;9798350377200

Researchers and industries are increasingly drawn to quantum computing for its computational potential. However, validating new quantum algorithms is challenging due to the limitations of current quantum devices. Software simulators are time and memory-consuming, making hardware emulators an attractive alternative. This article introduces AMARETTO (quantum ARchitecture EmulaTion TechnOlogy), designed for quantum computing emulation on low-tier Field-Programmable gate arrays (FPGAs), supporting Clifford+T and rotational gate sets. It simplifies and accelerates the verification of quantum algorithms using a Reduced-Instruction-Set-Computer (RISC)-like structure and efficient handling of sparse quantum gates. A dedicated compiler translates OpenQASM 2.0 into RISC-like instructions. AMARETTO is validated against the Qiskit simulators. Our results show successful emulation of sixteen qubits on a AMD Kria KV260 SoM. This approach rivals other works in emulated qubit capacity on a smaller, more affordable FPGA.

关键词： quantum computing Emulation Field Programmable Gate Array quantum Algorithm Verification quantum computing simulation

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State-of-the-art quantum computing simulators: Features, optimizations, and improvements for D-GM

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NEUROcomputing 2020年 393卷 223-233页

作者： de Avila, A. B. Reiser, R. H. S. Pilla, M. L. Yamin, A. C. Univ Fed Pelotas CDTec PPGC Teresina Brazil

quantum computing is strongly limited by physical implementations of quantum computers. Currently, development of quantum computing algorithms is carried out by analytic or simulation procedures while quantum computers are not widely available. Although quantum computing simulation is parallel by nature, spatial and temporal complexity are major performance hazards. The exponential increase in memory and global access to quantum states in simulations limit not only the number of qubits but also quantum transformations. Considering these scenarios, six quantum simulators are studied, in order to find out their main features and simulation results considering implementations classified in single/multiple processor and accelerator architectures. The main strategies used to improve performance in these architectures provide relevant parameters for the development of the new extension of the Distributed Geometric Machine environment proposed in this paper. Shor's and Grover's algorithms are simulated and compared to previous D-GM results and to LIQUi vertical bar >'s simulator, showing improvements as relative speedups up to 22.2 x in relation to the previous version and up to 910.46 x when compared to LIQUi vertical bar >. (C) 2019 Elsevier B.V. All rights reserved.

关键词： quantum computing quantum computing simulation Parallel processing

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