Qubit-Adaptive Variational Quantum Imaginary Time Evolution: A Resource-Efficient Algorithm for Ground-State Preparation of Correlated Molecules on Near-Term Quantum Computers

Abstract Preparing ground states of correlated molecules on near-term quantum computers requires algorithms that are both accurate and resource-efficient. We introduce the qubit-adaptive variational quantum imaginary time evolution (QAITE) algorithm, which synthesizes the systematic convergence of imaginary-time evolution with hardware-efficient, adaptive ansatz construction. By integrating the linear-scaling qubit operator pool into the adaptive variational quantum imaginary time evolution framework, QAITE deterministically constructs a compact ansatz without costly classical optimization loops. Numerical simulations for molecular systems (H4, LiH, H2O, BeH2), benchmarked against our own implementations of established adaptive algorithms under identical conditions, show that QAITE achieves chemical accuracy with a 15–45% reduction in CNOT gates compared to the standard adaptive variational quantum imaginary time evolution (AVQITE) method. For hydrogen chains (RHH = 1.5 Å, N = 6–16 qubits), QAITE’s circuit complexity grows approximately quadratically and remains the lowest of the four methods at every system size, reaching 31% fewer CNOT gates than AVQITE at 16 qubits─a saving of 1322 gates. This efficiency extends to heterogeneous (LiH)n and (HBe)n chains, where QAITE maintains a CNOT gate ratio below 1 for all sizes studied (e.g., 0.81 for (LiH)2). We further show that the deterministic parameter update is numerically robust: the results are insensitive to the regularization of the quantum geometric tensor over at least 4 orders of magnitude, and chemical accuracy is retained under realistic shot noise applied to both the quantum geometric tensor and the force vector. By outperforming established adaptive algorithms in both absolute gate count and scaling, QAITE establishes a promising, scalable pathway for quantum molecular simulations on noisy intermediate-scale quantum devices.

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Publication Details

Journal
Journal of Chemical Theory and Computation
Published
2026-09-26
DOI
https://doi.org/10.1021/acs.jctc.6c01171
Primary Topic
Quantum Computing Algorithms and Architecture
Type
article
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article

Qubit-Adaptive Variational Quantum Imaginary Time Evolution: A Resource-Efficient Algorithm for Ground-State Preparation of Correlated Molecules on Near-Term Quantum Computers

Jin‐Shi Xu, Wiwittawin Sukmas, Zhongfan Liu, Thitiwuth Chaiyatho et al.
Journal of Chemical Theory and Computation
Quantum Computing Algorithms and Architecture
article

Qubit-Adaptive Variational Quantum Imaginary Time Evolution: A Resource-Efficient Algorithm for Ground-State Preparation of Correlated Molecules on Near-Term Quantum Computers

Jin‐Shi Xu, Wiwittawin Sukmas, Zhongfan Liu, Thitiwuth Chaiyatho, Xiao-Ye Xu
article en

Abstract

Abstract Preparing ground states of correlated molecules on near-term quantum computers requires algorithms that are both accurate and resource-efficient. We introduce the qubit-adaptive variational quantum imaginary time evolution (QAITE) algorithm, which synthesizes the systematic convergence of imaginary-time evolution with hardware-efficient, adaptive ansatz construction. By integrating the linear-scaling qubit operator pool into the adaptive variational quantum imaginary time evolution framework, QAITE deterministically constructs a compact ansatz without costly classical optimization loops. Numerical simulations for molecular systems (H4, LiH, H2O, BeH2), benchmarked against our own implementations of established adaptive algorithms under identical conditions, show that QAITE achieves chemical accuracy with a 15–45% reduction in CNOT gates compared to the standard adaptive variational quantum imaginary time evolution (AVQITE) method. For hydrogen chains (RHH = 1.5 Å, N = 6–16 qubits), QAITE’s circuit complexity grows approximately quadratically and remains the lowest of the four methods at every system size, reaching 31% fewer CNOT gates than AVQITE at 16 qubits─a saving of 1322 gates. This efficiency extends to heterogeneous (LiH)n and (HBe)n chains, where QAITE maintains a CNOT gate ratio below 1 for all sizes studied (e.g., 0.81 for (LiH)2). We further show that the deterministic parameter update is numerically robust: the results are insensitive to the regularization of the quantum geometric tensor over at least 4 orders of magnitude, and chemical accuracy is retained under realistic shot noise applied to both the quantum geometric tensor and the force vector. By outperforming established adaptive algorithms in both absolute gate count and scaling, QAITE establishes a promising, scalable pathway for quantum molecular simulations on noisy intermediate-scale quantum devices.

Journal of Chemical Theory and Computation
University of Science and Technology of China (CN), Chulalongkorn University (TH)
Openalex Percentile: Top 9%
Quantum Computing Algorithms and Architecture
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