Conditional Decoupling of Quantum Information

08/01/2018
by   Mario Berta, et al.
0

Insights from quantum information theory show that correlation measures based on quantum entropy are fundamental tools that reveal the entanglement structure of multipartite states. In that spirit, Groisman, Popescu, and Winter [Physical Review A 72, 032317 (2005)] showed that the quantum mutual information I(A;B) quantifies the minimal rate of noise needed to erase the correlations in a bipartite state of quantum systems AB. Here, we investigate correlations in tripartite systems ABE. In particular, we are interested in the minimal rate of noise needed to apply to the systems AE in order to erase the correlations between A and B given the information in system E, in such a way that there is only negligible disturbance on the marginal BE. We present two such models of conditional decoupling, called deconstruction and conditional erasure cost of tripartite states ABE. Our main result is that both are equal to the conditional quantum mutual information I(A;B|E) -- establishing it as an operational measure for tripartite quantum correlations.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
01/23/2020

On lower semicontinuity of the quantum conditional mutual information and its corollaries

It is well known that the quantum mutual information and its conditional...
research
05/23/2023

Quantum Kolmogorov complexity and quantum correlations in deterministic-control quantum Turing machines

This work presents a study of Kolmogorov complexity for general quantum ...
research
07/21/2020

Graph-theoretic approach to dimension witnessing

A fundamental problem in quantum computation and quantum information is ...
research
04/18/2021

One-shot quantum state redistribution and quantum Markov chains

We revisit the task of quantum state redistribution in the one-shot sett...
research
01/11/2023

One-Shot Distributed Source Simulation: As Quantum as it Can Get

Distributed source simulation is the task where two (or more) parties sh...
research
11/21/2017

Information sensitivity functions to assess parameter information gain and identifiability of dynamical systems

A new class of functions, called the `Information sensitivity functions'...
research
02/09/2018

Optimized Bacteria are Environmental Prediction Engines

Experimentalists have observed phenotypic variability in isogenic bacter...

Please sign up or login with your details

Forgot password? Click here to reset