



01398nas a2200169   4500008004100000245006100041210006000102260001500162520088000177100002701057700001601084700001801100700002601118700002701144700002001171856003701191       2017                        eng d00aProvable quantum state tomography via non-convex methods0 aProvable quantum state tomography via nonconvex methods  c2017/11/193 a<p>With nowadays steadily growing quantum processors, it is required to develop new quantum tomography tools that are tailored for high-dimensional systems. In this work, we describe such a computational tool, based on recent ideas from non-convex optimization. The algorithm excels in the compressed-sensing-like setting, where only a few data points are measured from a lowrank or highly-pure quantum state of a high-dimensional system. We show that the algorithm can practically be used in quantum tomography problems that are beyond the reach of convex solvers, and, moreover, is faster than other state-of-the-art non-convex approaches. Crucially, we prove that, despite being a non-convex program, under mild conditions, the algorithm is guaranteed to converge to the global minimum of the problem; thus, it constitutes a provable quantum state tomography protocol.</p>1 aKyrillidis, Anastasios1 aKalev, Amir1 aPark, Dohuyng1 aBhojanapalli, Srinadh1 aCaramanis, Constantine1 aSanghavi, Sujay  uhttps://arxiv.org/abs/1711.02524