Fast state tomography with optimal error bounds

Projected least squares is an intuitive and numerically cheap technique for quantum state tomography: compute the least-squares estimator and project it onto the space of states. The main result of this paper equips this point estimator with rigorous, non-asymptotic convergence guarantees expressed in terms of the trace distance. The estimator's sample complexity is comparable to the strongest convergence guarantees available in the literature and-in the case of the uniform POVM-saturates fundamental lower bounds. Numerical simulations support these competitive features.