Papers
Topics
Authors
Recent
2000 character limit reached

Quantum chi-squared tomography and mutual information testing (2305.18519v2)

Published 29 May 2023 in quant-ph and cs.DS

Abstract: For quantum state tomography on rank-$r$ dimension-$d$ states, we show that $\widetilde{O}(r{.5}d{1.5}/\epsilon) \leq \widetilde{O}(d2/\epsilon)$ copies suffice for accuracy~$\epsilon$ with respect to (Bures) $\chi2$-divergence, and $\widetilde{O}(rd/\epsilon)$ copies suffice for accuracy~$\epsilon$ with respect to quantum relative entropy. The best previous bound was $\widetilde{O}(rd/\epsilon) \leq \widetilde{O}(d2/\epsilon)$ with respect to infidelity; our results are an improvement since infidelity is bounded above by both the relative entropy and the $\chi2$-divergence. For algorithms that are required to use single-copy measurements, we show that $\widetilde{O}(r{1.5} d{1.5}/\epsilon) \leq \widetilde{O}(d3/\epsilon)$ copies suffice for $\chi2$-divergence, and $\widetilde{O}(r{2} d/\epsilon)$ suffice for relative entropy. Using this tomography algorithm, we show that $\widetilde{O}(d{2.5}/\epsilon)$ copies of a $d\times d$-dimensional bipartite state suffice to test if it has quantum mutual information~$0$ or at least~$\epsilon$. As a corollary, we also improve the best known sample complexity for the \emph{classical} version of mutual information testing to $\widetilde{O}(d/\epsilon)$.

Citations (13)

Summary

We haven't generated a summary for this paper yet.

Whiteboard

Open Problems

We haven't generated a list of open problems mentioned in this paper yet.

Continue Learning

We haven't generated follow-up questions for this paper yet.

Collections

Sign up for free to add this paper to one or more collections.