With rapid progress in simulation of strongly interacting quantum
Hamiltonians, the challenge in characterizing unknown phases becomes a
bottleneck for scientific progress. We demonstrate that a Quantum-Classical
hybrid approach (QuCl) of mining the projective snapshots with interpretable
classical machine learning, can unveil new signatures of seemingly fea