Fig. 5: Illustration of Algorithm 2.
From: Learning properties of quantum states without the IID assumption
Algorithm 2 measures a large number of the state’s subsystems using the measurement device with low distortion \({{{{\mathcal{M}}}}}_{{{{\rm{dist}}}}}^{l-k}\) (red and green parts). Then, in order to predict the property, Algorithm 2 applies the data processing of Algorithm \({{{\mathcal{A}}}}\) to the outcomes of a part these subsystems (green part) leading to a prediction p. Algorithm 2 returns the remaining outcomes as calibration w. Success occurs if p is (approximately) compatible with the remaining post-measurement test copy \({\rho }_{l,{{{\bf{w}}}},p}^{{A}_{N}}\).
