An epoch-based algorithm learns d-dimensional pure states with cumulative regret O(d^3 log^2 T) and online infidelity O(d^3 log T / t) by using local tangent-direction measurements and a variance-adaptive estimator.
The algorithm freezes the base stateC m during each epoch, performs all linear estimation in the tangent spaceT CmM, and carries only the scalar precision µm to the next epoch
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Learning Pure Quantum States in Any Dimension (Almost) Without Regret
An epoch-based algorithm learns d-dimensional pure states with cumulative regret O(d^3 log^2 T) and online infidelity O(d^3 log T / t) by using local tangent-direction measurements and a variance-adaptive estimator.