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qSWIFT: High-order randomized compiler for Hamiltonian simulation

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arxiv 2302.14811 v2 pith:JUDCN7ZV submitted 2023-02-28 quant-ph

classification quant-ph
keywords qswiftnumberrequiredgateshamiltonianqdrifterrorprecision
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abstract

Hamiltonian simulation is known to be one of the fundamental building blocks of a variety of quantum algorithms such as its most immediate application, that of simulating many-body systems to extract their physical properties. In this work, we present qSWIFT, a high-order randomized algorithm for Hamiltonian simulation. In qSWIFT, the required number of gates for a given precision is independent of the number of terms in Hamiltonian, while the systematic error is exponentially reduced with regards to the order parameter. In this respect, our qSWIFT is a higher-order counterpart of the previously proposed quantum stochastic drift protocol (qDRIFT), in which the number of gates scales linearly with the inverse of the precision required. We construct the qSWIFT channel and establish a rigorous bound for the systematic error quantified by the diamond norm. qSWIFT provides an algorithm to estimate given physical quantities using a system with one ancilla qubit, which is as simple as other product-formula-based approaches such as regular Trotter-Suzuki decompositions and qDRIFT. Our numerical experiment reveals that the required number of gates in qSWIFT is significantly reduced compared to qDRIFT. Particularly, the advantage is significant for problems where high precision is required; for example, to achieve a systematic relative propagation error of $10^{-6}$, the required number of gates in third-order qSWIFT is 1000 times smaller than that of qDRIFT.

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Forward citations

Cited by 3 Pith papers

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

  1. Optimal Lower Bounds for Hamiltonian Simulation

    quant-ph 2026-07 conditional novelty 7.0 of 10

    There exist simple weighted-local Hamiltonians for which quantum simulation requires Ω(min over K of (Kt + t²λ_K²/ε)) gates — exactly matching the composite qDRIFT algorithm's cost.

  2. Quantum Channel Polynomial Processing

    quant-ph 2026-07 conditional novelty 6.0 of 10

    QCPP implements polynomial transformations of Hamiltonians via stochastic mixtures of unitary channels, achieving a tunable tradeoff between query and sample complexity.

  3. Circuit-Efficient Randomized Quantum Simulation of Non-Unitary Dynamics with Observable-Driven and Symmetry-Aware Designs

    quant-ph 2025-09 reject novelty 5.0 of 10

    A randomized compilation of LCHS for non-unitary dynamics, with an observable-driven variant and a symmetry-aware sampler, claims reduced ancilla and circuit depth at the cost of more repetitions.

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