Exploiting many-body localization for scalable variational quantum simulation

• URL: http://arxiv.org/abs/2404.17560v3
• Date: Tue, 02 Sep 2025 09:20:41 GMT
• Title: Exploiting many-body localization for scalable variational quantum simulation
• Authors: Chenfeng Cao, Yeqing Zhou, Swamit Tannu, Nic Shannon, Robert Joynt,
• Abstract summary: Variational quantum algorithms (VQAs) represent a promising pathway toward achieving practical quantum advantage on near-term hardware.<n>We demonstrate that initializing a hardware-efficient, Floquet-structured Ansatz within the many-body localized (MBL) phase mitigates barren plateaus and enhances algorithmic trainability.
• Score: 1.4509156851822589
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Variational quantum algorithms (VQAs) represent a promising pathway toward achieving practical quantum advantage on near-term hardware. Despite this promise, for generic, expressive ansatze, their scalability is critically hindered by barren plateaus--regimes of exponentially vanishing gradients. We demonstrate that initializing a hardware-efficient, Floquet-structured Ansatz within the many-body localized (MBL) phase mitigates barren plateaus and enhances algorithmic trainability. Through analysis of the inverse participation ratio, entanglement entropy, and a novel low-weight stabilizer R\'enyi entropy, we characterize a distinct MBL-thermalization transition. Below a critical kick strength, the circuit avoids forming a unitary 2-design, exhibits robust area-law entanglement, and maintains non-vanishing gradients. Leveraging this MBL regime facilitates the efficient variational preparation of ground states for several model Hamiltonians with significantly reduced computational resources. Crucially, experiments on IBM's 127-qubit Brisbane processor provide evidence for the preservation of trainable gradients in the MBL phase for a kicked Heisenberg chain, validating our approach on contemporary noisy hardware. Our findings position MBL-based initialization as a viable strategy for developing scalable VQAs and motivate the broader integration of localization phenomena into quantum algorithm design.

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