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Recently, the partial information decomposition emerged as a promising framework for identifying the meaningful components of the information contained in a joint distribution. Its adoption and practical application, however, have been…

Information Theory · Computer Science 2018-08-28 Ryan G. James , Jeffrey Emenheiser , James P. Crutchfield

We take a closer look at the structure of bivariate dependency induced by a pair of predictor random variables $(X_1, X_2)$ trying to synergistically, redundantly or uniquely encode a target random variable $Y$. We evaluate a recently…

Information Theory · Computer Science 2015-03-03 Pradeep Kr. Banerjee

One of the most fundamental questions one can ask about a pair of random variables X and Y is the value of their mutual information. Unfortunately, this task is often stymied by the extremely large dimension of the variables. We might hope…

Statistical Mechanics · Physics 2017-06-21 Ryan G. James , John R. Mahoney , James P. Crutchfield

In this paper, we first provide three general norm inequalities, which are used to give new uncertainty relations of any finite observables and quantum channels via metric-adjusted skew information. The results are applicable to its special…

Quantum Physics · Physics 2023-04-27 Hui Li , Ting Gao , Fengli Yan

We propose two new measures for extracting the unique information in $X$ and not $Y$ about a message $M$, when $X, Y$ and $M$ are joint random variables with a given joint distribution. We take a Markov based approach, motivated by…

Information Theory · Computer Science 2023-07-21 Keerthana Gurushankar , Praveen Venkatesh , Pulkit Grover

The integration and transfer of information from multiple sources to multiple targets is a core motive of neural systems. The emerging field of partial information decomposition (PID) provides a novel information-theoretic lens into these…

Information Theory · Computer Science 2021-10-28 Ari Pakman , Amin Nejatbakhsh , Dar Gilboa , Abdullah Makkeh , Luca Mazzucato , Michael Wibral , Elad Schneidman

We give a short proof that the coherent information is an achievable rate for the transmission of quantum information through a noisy quantum channel. Our method is to produce random codes by performing a unitarily covariant projective…

Quantum Physics · Physics 2016-11-17 Patrick Hayden , Michal Horodecki , Andreas Winter , Jon Yard

We consider a new formulation of a class of synchronization error channels and derive analytical bounds and numerical estimates for the capacity of these channels. For the binary channel with only deletions, we obtain an expression for the…

Information Theory · Computer Science 2016-11-17 Aravind R. Iyengar , Paul H. Siegel , Jack K. Wolf

The partial information decomposition (PID) is perhaps the leading proposal for resolving information shared between a set of sources and a target into redundant, synergistic, and unique constituents. Unfortunately, the PID framework has…

Statistical Mechanics · Physics 2018-10-30 Ryan G. James , Jeffrey Emenheiser , James P. Crutchfield

Inspired by works on information transmission through quantum channels, we propose the use of a couple of mutual entropies to quantify the efficiency of continual measurement schemes in extracting information on the measured quantum system.…

Quantum Physics · Physics 2009-10-09 Albert Barchielli , Giancarlo Lupieri

We consider the problem of quantifying the information shared by a pair of random variables $X_{1},X_{2}$ about another variable $S$. We propose a new measure of shared information, called extractable shared information, that is left…

Information Theory · Computer Science 2017-11-13 Johannes Rauh , Pradeep Kr. Banerjee , Eckehard Olbrich , Jürgen Jost , Nils Bertschinger

Quantum information quantities, such as mutual information and entropies, are essential for characterizing quantum systems and protocols in quantum information science. In this contribution, we identify types of information measures based…

Quantum Physics · Physics 2025-10-21 Christopher Popp , Tobias C. Sutter , Beatrix C. Hiesmayr

What are the distinct ways in which a set of predictor variables can provide information about a target variable? When does a variable provide unique information, when do variables share redundant information, and when do variables combine…

Information Theory · Computer Science 2018-05-04 Conor Finn , Joseph T Lizier

The coherent information concept is used to analyze a variety of simple quantum systems. Coherent information was calculated for the information decay in a two-level atom in the presence of an external resonant field, for the information…

Quantum Physics · Physics 2009-10-31 B. A. Grishanin , V. N. Zadkov

In this paper, we investigate the quantization of the output of a binary input discrete memoryless channel that maximizing the mutual information between the input and the quantized output under an entropy-constrained of the quantized…

Information Theory · Computer Science 2020-01-08 Thuan Nguyen , Thinh Nguyen

Williams and Beer (2010) proposed a nonnegative mutual information decomposition, based on the construction of information gain lattices, which allows separating the information that a set of variables contains about another into components…

Data Analysis, Statistics and Probability · Physics 2017-04-05 Daniel Chicharro , Stefano Panzeri

Conventional distributed approaches to coverage control may suffer from lack of convergence and poor performance, due to the fact that agents have limited information, especially in non-convex discrete environments. To address this issue,…

Computer Science and Game Theory · Computer Science 2024-04-09 Tatsuya Iwase , Aurélie Beynier , Nicolas Bredeche , Nicolas Maudet , Jason R. Marden

We derive a tight lower bound on equivocation (conditional entropy), or equivalently a tight upper bound on mutual information between a signal variable and channel outputs. The bound is in terms of the joint distribution of the signals and…

Information Theory · Computer Science 2019-01-14 Michal Hledík , Thomas R. Sokolowski , Gašper Tkačik

This brief note considers the problem of estimating temporal synergy and integrated information in dyadic dynamical processes. One of the standard estimators of dynamic synergy is based on the minimal mutual information between sets of…

Information Theory · Computer Science 2024-07-24 Thomas F. Varley

The decomposition of channel information into synergies of different order is an open, active problem in the theory of complex systems. Most approaches to the problem are based on information theory, and propose decompositions of mutual…

Information Theory · Computer Science 2015-12-14 Paolo Perrone , Nihat Ay