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Simulating Quantum Computations on Classical Machines: A Survey

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arxiv 2311.16505 v1 pith:VJ7RFCXZ submitted 2023-11-28 quant-ph

Simulating Quantum Computations on Classical Machines: A Survey

classification quant-ph
keywords simulatorsquantumsimulationmethodsactivelyclassicalefficientmaintained
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved
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We present a comprehensive study of quantum simulation methods and quantum simulators for classical computers. We first study an exhaustive set of 150+ simulators and quantum libraries. Then, we short-list the simulators that are actively maintained and enable simulation of quantum algorithms for more than 10 qubits. As a result, we realize that most efficient and actively maintained simulators have been developed after 2010. We also provide a taxonomy of the most important simulation methods, namely Schrodinger-based, Feynman path integrals, Heisenberg-based, and hybrid methods. We observe that most simulators fall in the category of Schrodinger-based approaches. However, there are a few efficient simulators belonging to other categories. We also make note that quantum frameworks form their own class of software tools that provide more flexibility for algorithm designers with a choice of simulators/simulation method. Another contribution of this study includes the use and classification of optimization methods used in a variety of simulators. We observe that some state-of-the-art simulators utilize a combination of software and hardware optimization techniques to scale up the simulation of quantum circuits. We summarize this study by providing a roadmap for future research that can further enhance the use of quantum simulators in education and research.

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Cited by 3 Pith papers

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  1. EQE-QAOA: An Equivalence-Preserving Qubit Efficient Framework for Combinatorial Optimization

    cs.ET 2026-04 unverdicted novelty 6.0

    EQE-QAOA reduces qubit count for QAOA while exactly preserving optimization performance by confining dynamics to an invariant subspace and applying an isometric re-encoding.

  2. Orkan: Cache-friendly simulation of quantum operations on hermitian operators

    quant-ph 2026-04 unverdicted novelty 6.0

    Orkan simulates quantum operations on Hermitian operators using a cache-friendly tiled lower-triangle layout, halving memory and achieving 2-4x speedups over Qiskit Aer, QuEST, and Qulacs.

  3. Federated Learning with Quantum Enhanced LSTM for Applications in High Energy Physics

    cs.LG 2026-04 unverdicted novelty 4.0

    A federated QLSTM model achieves near-classical accuracy on SUSY classification with under 300 parameters and 20K data points, claiming 100x efficiency gains over baselines.