Learning Pure Quantum States in Any Dimension (Almost) Without Regret
Josep Lumbreras, Marco Tomamichel

TL;DR
This paper presents a new quantum state tomography method for pure states in any finite dimension that minimizes disturbance and achieves near-optimal regret bounds, extending qubit techniques to qudits.
Contribution
It introduces a local geometric approach for pure-state tomography in arbitrary dimensions, overcoming previous limitations and providing provable regret guarantees.
Findings
Achieves cumulative regret of ^3 log^2 T for dimension d after T measurements.
Current estimate's infidelity decreases as ^3 log(T)/t over time.
Pure-state tomography with minimal disturbance extends from qubits to qudits due to geometric properties.
Abstract
We extend quantum state tomography with minimal cumulative disturbance, first investigated in [arXiv:2406.18370], to arbitrary finite-dimensional pure states. A learner sequentially receives fresh copies of an unknown pure state, chooses a rank-one projector for each copy using the previous outcomes, and performs the corresponding two-outcome projective measurement. The goal is to learn the state while keeping the chosen projectors close to the unknown state in order to minimize disturbance. The qubit solution relies on the special geometry of the Bloch sphere and does not extend directly to qudits, where pure states form a curved manifold. We show that this obstruction can be overcome by working locally on the pure-state manifold. The algorithm proceeds in epochs. In each epoch, it fixes a current estimate, measures pairs of nearby rank-one projectors obtained by moving in opposite…
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