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This paper presents a novel quantum algorithm utilizing the Quantum Singular Value Transform (QSVT) framework to estimate modular flow, addressing a previously unsolved procedure in characterizing subsystem entanglement. The authors establish query complexity lower bounds proving the optimality of their approach and demonstrate applications such as extracting chiral central charges in topologically ordered systems within holographic models.
A quantum algorithm for modular flow
arXiv:2508.16826v2 Announce Type: replace Abstract: Entanglement is a defining property of quantum systems. For a subsystem of a larger quantum system, one can formally define an operator known as the modular Hamiltonian, which is closely linked to the entanglement properties of that subsystem, and a corresponding operator flow called the modular flow. Algorithms for estimating the von Neumann entropy, the best-known entanglement measure, are well-established, but no equivalent procedures have been previously described for the modular flow. In this work, we briefly review the quantum singular value transform (QSVT) framework for developing quantum algorithms, and then discuss the implementation of modular flow within this framework. We conclude by describing select applications of our modular flow algorithm, such as extracting the chiral central charge of a topologically ordered system and simulating the experience of the bulk observer in holography. We also prove a query complexity lower bound for modular flow, which shows that our method cannot be improved further substantially.
Abstract:Entanglement is a defining property of quantum systems. For a subsystem of a larger quantum system, one can formally define an operator known as the modular Hamiltonian, which is closely linked to the entanglement properties of that subsystem, and a corresponding operator flow called the modular flow. Algorithms for estimating the von Neumann entropy, the best-known entanglement measure, are well-established, but no equivalent procedures have been previously described for the modular flow. In this work, we briefly review the quantum singular value transform (QSVT) framework for developing quantum algorithms, and then discuss the implementation of modular flow within this framework. We conclude by describing select applications of our modular flow algorithm, such as extracting the chiral central charge of a topologically ordered system and simulating the experience of the bulk observer in holography. We also prove a query complexity lower bound for modular flow, which shows that our method cannot be improved further substantially.
v2: replaced Chebyshev construction with a result from Gilyen and Li, which resulted in a slightly improved scaling in the main result. Minor updates to discussion of the query complexity lower bound. Updated style to PRA style
arXiv:2508.16826 [quant-ph]
(or arXiv:2508.16826v2 [quant-ph] for this version)
Full text under the publisher's open licence · 199 words
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