Random Clifford measurements produce a classical shadow of a quantum state that predicts M linear features using only O(log M) measurements, independent of system size, with a matching lower bound.
Applications range from quantum error correction [46], to measurement-based quantum computation [9, 49] and randomized benchmarking [15, 37, 43]
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Predicting Features of Quantum Systems from Very Few Measurements
Random Clifford measurements produce a classical shadow of a quantum state that predicts M linear features using only O(log M) measurements, independent of system size, with a matching lower bound.