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Research PaperResearchia:202609.16032

Query-optimal quantum simulation of Lindblad evolution

Chunhao Wang

Abstract

For the problem of simulating Lindblad evolution for time $t$ to precision $ε$, Hamiltonian simulation provides an additive query lower bound, informally, $Ω(t + \mathrm{polylog}(1/ε))$. However, the best previously known algorithms for general Lindblad simulation achieve a multiplicative upper bound, informally, $\mathcal{O}(t\,\mathrm{polylog}(1/ε))$, in gate complexity. It has remained open whether this multiplicative dependence is necessary. In this paper, we close the gap in query complexit...

Submitted: September 16, 2026Subjects: Quantum Physics; Quantum Computing

Description / Details

For the problem of simulating Lindblad evolution for time tt to precision εε, Hamiltonian simulation provides an additive query lower bound, informally, Ω(t+polylog(1/ε))Ω(t + \mathrm{polylog}(1/ε)). However, the best previously known algorithms for general Lindblad simulation achieve a multiplicative upper bound, informally, O(tpolylog(1/ε))\mathcal{O}(t\,\mathrm{polylog}(1/ε)), in gate complexity. It has remained open whether this multiplicative dependence is necessary. In this paper, we close the gap in query complexity by giving an algorithm with optimal additive dependence on evolution time and precision in the block-encoding model. Our approach uses the transducer framework to reduce the query cost of composing first-order approximations to the evolution channel, together with linear combinations of reuse circuits of different lengths to suppress catalyst-removal error. Although our additional gate complexity is higher than that of existing algorithms, our optimal query complexity resolves the question of how much oracle access is fundamentally necessary and identifies the remaining challenge to achieve the optimal gate complexity.


Source: arXiv:2609.17490v1 - http://arxiv.org/abs/2609.17490v1 PDF: https://arxiv.org/pdf/2609.17490v1 Original Link: http://arxiv.org/abs/2609.17490v1

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Date:
Sep 16, 2026
Topic:
Quantum Computing
Area:
Quantum Physics
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