Quantum Markov chains and logarithmic trace inequalities
- Publication Type:
- Conference Proceeding
- IEEE International Symposium on Information Theory - Proceedings, 2017, pp. 1988 - 1992
- Issue Date:
Copyright Clearance Process
- Recently Added
- In Progress
- Closed Access
This item is closed access and not available.
© 2017 IEEE. A Markov chain is a tripartite quantum state ρ ABC where there exists a recovery map R B→BC such that ρ ABC = R B→BC (ρ AB ). More generally, an approximate Markov chain ρ ABC is a state whose distance to the closest recovered state R B→BC (ρ AB ) 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.
Please use this identifier to cite or link to this item: