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A Herculean task: Classical simulation of quantum computers

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arxiv 2302.08880 v1 pith:YZTQKZTR submitted 2023-02-17 quant-ph

classification quant-ph
keywords quantumclassicalcomputersmethodssimulationalgorithmscomputerdesign
verification ladder T0 review T1 audit T2 compute T3 formal
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In the effort to develop useful quantum computers simulating quantum machines with conventional computing resources is a key capability. Such simulations will always face limits preventing the emulation of quantum computers of substantial scale but by pushing the envelope as far as possible through optimal choices of algorithms and hardware the value of the simulator tool is maximized. This work reviews the state-of-the-art numerical simulation methods i.e. the classical algorithms that emulate quantum computer evolution under specific operations. We focus on the mainstream state-vector and tensor-network paradigms while briefly mentioning alternative methods. Moreover we review the diverse applications of simulation across different facets of quantum computer development such as understanding the fundamental difference between quantum and classical computations exploring algorithm design spaces for quantum advantage predicting quantum processor performance at the design stage and characterizing fabricated devices efficiently for fast iterations. This review complements recent surveys on today's tools and implementations here we seek to acquaint the reader with an essential understanding of the theoretical basis of classical simulations detailed discussions on the advantages and limitations of different methods and the demands and challenges arising from practical use cases.

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Cited by 7 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. A Method for Constructing Quasi-Random Peaked Quantum Circuits

    quant-ph 2025-08 reject novelty 6.0 of 10

    A scalable algorithm constructs quasi-random "peaked" quantum circuits that concentrate measurement outcomes on a predetermined bitstring, and the paper shows MPS simulation cannot reliably recover that bitstring for ...

  2. Characterizing Pauli Propagation via Operator Complexity

    quant-ph 2025-10 conditional novelty 5.0 of 10

    Truncation error in Pauli propagation is bounded by Operator Stabilizer Rényi entropy, giving a Top-K budget formula, and the 1D XY chain's evolved local operator has O(s²) Pauli terms.

  3. 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.

  4. MPS-JuliQAOA: User-friendly, Scalable MPS-based Simulation for Quantum Optimization

    quant-ph 2025-08 unverdicted novelty 4.0 of 10

    MPS-JuliQAOA is a user-friendly MPS-based simulator that scales QAOA to 512 qubits and 20 rounds on 3-regular MaxCut problems.

  5. Toolchain for Faster Iterations in Quantum Software Development

    quant-ph 2025-07 conditional novelty 4.0 of 10

    A q8s Jupyter kernel offloads quantum circuit simulation to remote GPU clusters, showing up to 10x faster execution for 29-qubit circuits than a local CPU laptop.

  6. Qymera: Simulating Quantum Circuits using RDBMS

    quant-ph 2025-06 conditional novelty 4.0 of 10

    Qymera translates quantum circuits into SQL over integer-encoded state tables, runs them in SQLite or DuckDB, and provides a circuit builder and benchmarking tools.

  7. How to Write a Simulator for Quantum Circuits from Scratch: A Tutorial

    quant-ph 2025-06 unverdicted novelty 4.0 of 10

    A tutorial with pseudocode and a compact JavaScript simulator that shows how to simulate quantum circuits of 20+ qubits using qubit-wise multiplication and partial trace.

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