TetrisCNN for interpretable detection of phases of matter from experimental quantum simulator data

Paper recorded by Signals 4 on 2026-09-17 in cs.LG. Abstract reproduced from arXiv; link to the original below.

Published 2026-09-17 on arXiv · recorded by Signals 4 on 2026-09-18

Category: cs.LG · 机器学习 · first seen 2026-09-18

Abstract

Detecting phases of matter in general relies on identifying the correct order parameter - a task that remains notoriously difficult for unknown transitions and traditionally is guided by physical intuition and educated guess. Neural networks have recently offered an alternative route by locating phase transitions in known models without any a priori physical knowledge. Yet these approaches remain

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