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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Veröffentlicht in:IEEE transactions on computer-aided design of integrated circuits and systems S. 1
Hauptverfasser: Huang, Mingyu, Guan, Ji, Fang, Wang, Ying, Mingsheng
Format: Journal Article
Sprache:Englisch
Veröffentlicht: IEEE 2025
Schlagworte:
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
ISSN:0278-0070, 1937-4151
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Zusammenfassung: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.
ISSN:0278-0070
1937-4151
DOI:10.1109/TCAD.2025.3623498