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This paper establishes the optimal query complexity for preparing quantum ground states, providing matching upper and lower bounds when spectral gap thresholds are known. By leveraging amplitude amplification with constant-accuracy spectral filters, the authors derive efficient algorithms that minimize calls to Hamiltonian block-encodings and state-preparation oracles. These theoretical limits define the fundamental efficiency frontier for variational quantum eigensolvers and other protocols relying on precise ground-state initialization.
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Optimal Query Complexity for Ground-State Preparation

arXiv3 min read

arXiv:2609.35668v1 Announce Type: new Abstract: We determine the optimal query complexity of ground-state preparation to trace-distance error $\varepsilon$ when an energy threshold in the spectral gap is known. Let $U_H$ be an $\alpha$-block-encoding of a Hamiltonian with unique ground state $|\psi_0\rangle$, and suppose $|\langle\psi_0|U_I|0\rangle|\ge\gamma$ for a state-preparation oracle $U_I$. The threshold lies at least $\Delta/2$ above the ground-state energy and at least $\Delta/2$ below every excited-state energy. We give two algorithms that prepare a state within trace distance $\varepsilon$ of the ground state. One uses $O((\alpha/\Delta)(\gamma^{-1}+\log(1/\varepsilon)))$ calls to $U_H$ in expectation; the other uses $O((\alpha/(\gamma\Delta))\log(1/\varepsilon))$ calls to $U_H$ in the worst case. We prove a lower bound matching the expected query count; the corresponding worst-case lower bound follows from Somma and de Wolf [SdW26]. The respective bounds on calls to $U_I$ are $O(1/\gamma)$ in expectation and $O(\gamma^{-1}\log(1/\varepsilon))$ in the worst case. On $(N+1)$-dimensional systems, these $U_I$ bounds are also optimal when the expected or worst-case count of $U_H$ calls, respectively, is $o((\alpha/\Delta)\sqrt N)$. Both algorithms use a constant-accuracy spectral filter to construct a purifier, which we then sequentially compose during amplitude amplification to prepare a state with constant overlap with the ground state. The expected-query algorithm repeats the preparation followed by one high-accuracy spectral filter until success. The worst-case algorithm uses filters of increasing accuracy and limits the total number of queries.

Abstract:We determine the optimal query complexity of ground-state preparation to trace-distance error $\varepsilon$ when an energy threshold in the spectral gap is known. Let $U_H$ be an $\alpha$-block-encoding of a Hamiltonian with unique ground state $|\psi_0\rangle$, and suppose $|\langle\psi_0|U_I|0\rangle|\ge\gamma$ for a state-preparation oracle $U_I$. The threshold lies at least $\Delta/2$ above the ground-state energy and at least $\Delta/2$ below every excited-state energy. We give two algorithms that prepare a state within trace distance $\varepsilon$ of the ground state. One uses $O((\alpha/\Delta)(\gamma^{-1}+\log(1/\varepsilon)))$ calls to $U_H$ in expectation; the other uses $O((\alpha/(\gamma\Delta))\log(1/\varepsilon))$ calls to $U_H$ in the worst case. We prove a lower bound matching the expected query count; the corresponding worst-case lower bound follows from Somma and de Wolf [SdW26]. The respective bounds on calls to $U_I$ are $O(1/\gamma)$ in expectation and $O(\gamma^{-1}\log(1/\varepsilon))$ in the worst case. On $(N+1)$-dimensional systems, these $U_I$ bounds are also optimal when the expected or worst-case count of $U_H$ calls, respectively, is $o((\alpha/\Delta)\sqrt N)$. Both algorithms use a constant-accuracy spectral filter to construct a purifier, which we then sequentially compose during amplitude amplification to prepare a state with constant overlap with the ground state. The expected-query algorithm repeats the preparation followed by one high-accuracy spectral filter until success. The worst-case algorithm uses filters of increasing accuracy and limits the total number of queries.

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

arXiv:2609.35668 [quant-ph]

(or arXiv:2609.35668v1 [quant-ph] for this version)

https://doi.org/10.48550/arXiv.2609.35668 Focus to learn more arXiv-issued DOI via DataCite (pending registration)

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