Approximation Methods for Simulation and Equivalence Checking of Noisy Quantum Circuits
In the current NISQ (Noisy Intermediate-Scale Quantum) era, simulating and verifying noisy quantum circuits is crucial but faces challenges such as quantum state explosion and complex noise representations, constraining simulation and equivalence checking to circuits with a limited number of qubits....
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| Vydané v: | IEEE transactions on computer-aided design of integrated circuits and systems s. 1 |
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| Médium: | Journal Article |
| Jazyk: | English |
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IEEE
2025
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| ISSN: | 0278-0070, 1937-4151 |
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| Abstract | In the current NISQ (Noisy Intermediate-Scale Quantum) era, simulating and verifying noisy quantum circuits is crucial but faces challenges such as quantum state explosion and complex noise representations, constraining simulation and equivalence checking to circuits with a limited number of qubits. This paper introduces an approximation algorithm for simulating and assessing the equivalence of noisy quantum circuits, specifically designed to improve scalability under low-noise conditions. The approach utilizes a novel tensor network diagram combined with singular value decomposition to approximate the tensors of quantum noises. The implementation is based on Google's TensorNetwork Python package for contraction. Experimental results on realistic quantum circuits with realistic hardware noise models indicate that our algorithm can simulate and check the equivalence of QAOA (Quantum Approximate Optimization Algorithm) circuits with around 200 qubits and 20 noise operators, outperforming state-of-the-art approaches in scalability and speed. |
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| AbstractList | In the current NISQ (Noisy Intermediate-Scale Quantum) era, simulating and verifying noisy quantum circuits is crucial but faces challenges such as quantum state explosion and complex noise representations, constraining simulation and equivalence checking to circuits with a limited number of qubits. This paper introduces an approximation algorithm for simulating and assessing the equivalence of noisy quantum circuits, specifically designed to improve scalability under low-noise conditions. The approach utilizes a novel tensor network diagram combined with singular value decomposition to approximate the tensors of quantum noises. The implementation is based on Google's TensorNetwork Python package for contraction. Experimental results on realistic quantum circuits with realistic hardware noise models indicate that our algorithm can simulate and check the equivalence of QAOA (Quantum Approximate Optimization Algorithm) circuits with around 200 qubits and 20 noise operators, outperforming state-of-the-art approaches in scalability and speed. |
| Author | Guan, Ji Fang, Wang Huang, Mingyu Ying, Mingsheng |
| Author_xml | – sequence: 1 givenname: Mingyu orcidid: 0009-0000-3219-1380 surname: Huang fullname: Huang, Mingyu email: huangmy@ios.ac.cn organization: Institute of Software, Key Laboratory of System Software (Chinese Academy of Sciences) and State Key Laboratory of Computer Science, Chinese Academy of Sciences, Beijing, China – sequence: 2 givenname: Ji surname: Guan fullname: Guan, Ji email: guanj@ios.ac.cn organization: Institute of Software, Key Laboratory of System Software (Chinese Academy of Sciences) and State Key Laboratory of Computer Science, Chinese Academy of Sciences, Beijing, China – sequence: 3 givenname: Wang surname: Fang fullname: Fang, Wang email: wang.fang@ed.ac.uk organization: School of Informatics, University of Edinburgh, Edinburgh, United Kingdom – sequence: 4 givenname: Mingsheng orcidid: 0000-0003-4847-702X surname: Ying fullname: Ying, Mingsheng email: Mingsheng.Ying@uts.edu.au organization: Centre for Quantum Software and Information, University of Technology Sydney, Ultimo, NSW, Australia |
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| SubjectTerms | approximation algorithm Approximation algorithms Circuit faults Circuits equivalence checking Logic gates Noise Noise measurement noisy simulation Quantum circuit Quantum circuits Quantum computing Qubit tensor network Tensors |
| Title | Approximation Methods for Simulation and Equivalence Checking of Noisy Quantum Circuits |
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