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This research presents an optimal quantum algorithm for ground-state energy estimation that reduces query complexity by a factor of $\log(1/\gamma)$ compared to previous methods. By leveraging transducers, the approach achieves this efficiency without incurring overhead from error reduction, effectively resolving an open question regarding lower bounds in guided settings. The work advances fundamental limits on Hamiltonian simulation and eigenphase estimation within quantum computational theory.
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Optimal Quantum Algorithm for Ground-State Energy Estimation with a Guiding State

arXiv2 min read

arXiv:2608.24494v1 Announce Type: new Abstract: In the problem of ground-state energy estimation, one aims to estimate the smallest eigenvalue of a Hamiltonian, often given a guiding state, with some promised overlap $\gamma$ with the ground space. The main approach to this problem is to simulate its evolution, and estimate the smallest (or equivalently, largest) eigenphase of the resulting unitary $U$. We give a quantum algorithm that estimates the largest eigenphase of a unitary $U$ in this guided setting using a factor of $\log\frac{1}{\gamma}$ fewer queries to $U$ than the previous best approach. The result matches an existing lower bound, and answers an open question from Mande and de Wolf. The algorithm is based on transducers, which often allow composition of quantum algorithms without overhead from error reduction.

Abstract:In the problem of ground-state energy estimation, one aims to estimate the smallest eigenvalue of a Hamiltonian, often given a guiding state, with some promised overlap $\gamma$ with the ground space. The main approach to this problem is to simulate its evolution, and estimate the smallest (or equivalently, largest) eigenphase of the resulting unitary $U$. We give a quantum algorithm that estimates the largest eigenphase of a unitary $U$ in this guided setting using a factor of $\log\frac{1}{\gamma}$ fewer queries to $U$ than the previous best approach. The result matches an existing lower bound, and answers an open question from Mande and de Wolf. The algorithm is based on transducers, which often allow composition of quantum algorithms without overhead from error reduction.

Quantum Physics (quant-ph); Computational Complexity (cs.CC); Data Structures and Algorithms (cs.DS)

arXiv:2608.24494 [quant-ph]

(or arXiv:2608.24494v1 [quant-ph] for this version)

https://doi.org/10.48550/arXiv.2608.24494 Focus to learn more arXiv-issued DOI via DataCite (pending registration)

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