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Published June 2017 | public
Book Section - Chapter

Quantum Markov chains and logarithmic trace inequalities

Abstract

A Markov chain is a tripartite quantum state ρABC where there exists a recovery map RB→BC such that ρABC = RB→BC(ρAB). More generally, an approximate Markov chain ρABC is a state whose distance to the closest recovered state RB→BC(ρAB) is small. Recently it has been shown that this distance can be bounded from above by the conditional mutual information I(A : C|B)ρ of the state. We improve on this connection by deriving the first bound that is tight in the commutative case and features an explicit recovery map that only depends on the reduced state pBC. The key tool in our proof is a multivariate extension of the Golden-Thompson inequality, which allows us to extend logarithmic trace inequalities from two to arbitrarily many matrices.

Additional Information

© 2017 IEEE. DS acknowledges support by the Swiss National Science Foundation (SNSF) via the National Centre of Competence in Research "QSIT" and by the European Commission via the project "RAQUEL". MB acknowledges funding by the SNSF through a fellowship, funding by the Institute for Quantum Information and Matter (IQIM), an NSF Physics Frontiers Center (NFS Grant PHY-1125565) with support of the Gordon and Betty Moore Foundation (GBMF-12500028), and funding support form the ARO grant for Research on Quantum Algorithms at the IQIM (W911NF-12-1-0521). MT is funded by an ARC Discovery Early Career Researcher Award (DECRA) fellowship and acknowledges support from the ARC Centre of Excellence for Engineered Quantum Systems (EQUS).

Additional details

Created:
August 19, 2023
Modified:
October 17, 2023