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arXiv · 2509.13034

Slice-Wise Initial State Optimization to Improve Cost and Accuracy of the VQE on Lattice Models

Cedric Gaberle·Manpreet Singh Jattana
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Abstract

We propose an optimization method for the Variational Quantum Eigensolver (VQE) that combines adaptive and physics-inspired ansatz design. Instead of optimizing multiple layers simultaneously, the ansatz is built incrementally from its operator subsets, enabling subspace optimization that provides better initialization for subsequent steps. This quasi-dynamical approach preserves expressivity and hardware efficiency while avoiding the overhead of operator selection associated with adaptive methods. Benchmarks on one- and two-dimensional Heisenberg and Hubbard models with up to 20 qubits show improved fidelities, reduced function evaluations, or both, compared to fixed-layer VQE. The method is simple, cost-effective, and particularly well-suited for current noisy intermediate-scale quantum (NISQ) devices.

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Cedric Gaberle, Manpreet Singh Jattana. 2025-09-16. Slice-Wise Initial State Optimization to Improve Cost and Accuracy of the VQE on Lattice Models. https://doi.org/10.1088/1402-4896%2Fae26f8

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