Probabilistic imaginary-time evolution via compiled diagonal representations
Hengyue Li, Huazhe Lou, Yang Li, Mingyu Huang, Yusheng Yang, Jianyong Sheng, Jian Sun, Shenggang Ying
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.
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