On the optimal error exponents for classical and quantum antidistinguishability
Hemant K. Mishra, Michael Nussbaum, Mark M. Wilde

TL;DR
This paper investigates the asymptotic error rates in classical and quantum antidistinguishability, providing exact and bounded expressions, and linking classical divergence measures to quantum state discrimination.
Contribution
It derives the classical optimal error exponent as the multivariate Chernoff divergence and offers bounds for the quantum case, advancing understanding of quantum state elimination.
Findings
Classical optimal error exponent equals multivariate Chernoff divergence.
Quantum bounds are established using pairwise Chernoff and SDP methods.
Open problem remains for an explicit quantum optimal error exponent.
Abstract
The concept of antidistinguishability of quantum states has been studied to investigate foundational questions in quantum mechanics. It is also called quantum state elimination, because the goal of such a protocol is to guess which state, among finitely many chosen at random, the system is not prepared in (that is, it can be thought of as the first step in a process of elimination). Antidistinguishability has been used to investigate the reality of quantum states, ruling out -epistemic ontological models of quantum mechanics [Pusey et al., Nat. Phys., 8(6):475-478, 2012]. Thus, due to the established importance of antidistinguishability in quantum mechanics, exploring it further is warranted. In this paper, we provide a comprehensive study of the optimal error exponent -- the rate at which the optimal error probability vanishes to zero asymptotically -- for classical and quantum…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsQuantum Mechanics and Applications · Quantum Information and Cryptography · Statistical Mechanics and Entropy
