Error regions in quantum state tomography: computational complexity   caused by geometry of quantum states
  The outcomes of quantum mechanical experiments are inherently random. It is therefore necessary to develop stringent methods for quantifying the degree of statistical uncertainty about the results of quantum experiments. For the particularly relevant task of quantum state estimation, it has been shown that a significant reduction in uncertainty can be achieved by taking the positivity of quantum states into account. However -- the large number of partial results and heuristics notwithstanding -- no efficient general algorithm is known that produces an optimal uncertainty region from experimental data and the prior constraint of positivity. Here, we make this problem precise and show that the general case is NP-hard. Our result leaves room for the existence of efficient approximate solutions, and therefore does not yet imply that the practical task of quantum uncertainty quantification is intractable. However, it does show that there exists a non-trivial trade-off between optimality and computational efficiency for error regions. We prove two versions of the result: One for frequentist and one for Bayesian statistics. 
Daniel Suess, {\L}ukasz Rudnicki, Thiago O. Maciel, David Gross
quant-ph