Fig. 2: Schematic representation of our algorithm to learn phases of matter.
From: Efficient learning of ground and thermal states within phases of matter
The training stage just consists of collecting shadows corresponding to various parameters. In the prediction stage, given an observable O and corresponding parameter y supported on a region R, we search for parameters xi we sampled that have parameters close to y on an enlarged region, R(r) around R and compute the expectation value of O on the corresponding shadows. The prediction is then a median of means estimate on the values. Note that no machine learning techniques are required for the estimate.
