Year: 2026
Type: preprint
Abstract: We introduce a probabilistic imaginary-time evolution scheme based on a compiled approximate diagonal representation of the Hamiltonian. A basis transformation is optimized offline. For a fixed compiled representation, the online circuit structure and gate count per attempt are independent of the imaginary time, and the same representation can be reused across different input states and evolution times. We derive a condition for enhanced success probability. Numerical tests show reduced online cost relative to termwise Pauli-based methods at a common accuracy threshold. We also examine how approximation errors and offline preparation costs affect the overall benefit.
Source: arXiv (Cornell University)
Institutions: Chinese Academy of Sciences, Institute of Software
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W7224907161