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Near-Term Quantum Computing Techniques: Variational Quantum Algorithms, Error Mitigation, Circuit Compilation, Benchmarking and Classical Simulation

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arxiv 2211.08737 v3 pith:RQ66EB52 submitted 2022-11-16 quant-ph cs.AIcs.LG

classification quant-phcs.AIcs.LG
keywords quantumnear-termcomputingtechniquesalgorithmsdeviceswillapplications
verification ladder T0 review T1 audit T2 compute T3 formal
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Quantum computing is a game-changing technology for global academia, research centers and industries including computational science, mathematics, finance, pharmaceutical, materials science, chemistry and cryptography. Although it has seen a major boost in the last decade, we are still a long way from reaching the maturity of a full-fledged quantum computer. That said, we will be in the Noisy-Intermediate Scale Quantum (NISQ) era for a long time, working on dozens or even thousands of qubits quantum computing systems. An outstanding challenge, then, is to come up with an application that can reliably carry out a nontrivial task of interest on the near-term quantum devices with non-negligible quantum noise. To address this challenge, several near-term quantum computing techniques, including variational quantum algorithms, error mitigation, quantum circuit compilation and benchmarking protocols, have been proposed to characterize and mitigate errors, and to implement algorithms with a certain resistance to noise, so as to enhance the capabilities of near-term quantum devices and explore the boundaries of their ability to realize useful applications. Besides, the development of near-term quantum devices is inseparable from the efficient classical simulation, which plays a vital role in quantum algorithm design and verification, error-tolerant verification and other applications. This review will provide a thorough introduction of these near-term quantum computing techniques, report on their progress, and finally discuss the future prospect of these techniques, which we hope will motivate researchers to undertake additional studies in this field.

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  1. Comparing performance of variational quantum algorithm simulations on HPC systems

    quant-ph 2025-07 conditional novelty 5.0 of 10

    A parser-based toolchain can port the same Hamiltonian and ansatz across seven quantum simulators, but variational algorithms on 15 to 20 qubits show limited parallel speedup.

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