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quant-ph2025
Universal quantum phase classification on quantum computers from machine learning
Weicheng Ye, Shuwei Liu, Shiyu Zhou +1
The classification of quantum phases of matter remains a fundamental challenge in condensed matter physics. We present a novel framework that combines shadow tomography with modern…
quant-ph2025
Noise-strength-adapted approximate quantum codes inspired by machine learning
Shuwei Liu, Shiyu Zhou, Zi-Wen Liu +1
We demonstrate that machine learning provides a powerful tool for discovering new approximate quantum error-correcting (AQEC) codes beyond conventional algebraic frameworks. Buildi…
quant-ph2024
Learning effective Hamiltonians for adaptive time-evolution quantum algorithms
Hongzheng Zhao, Ao Chen, Shu-Wei Liu +3
Digital quantum simulation of many-body dynamics relies on Trotterization to decompose the target time evolution into elementary quantum gates operating at a fixed equidistant time…