Information flow in bipartite Markov systems is split into a housekeeping part that maintains correlations through cyclic modes and an excess part that changes mutual information through conservative forces.
Schnakenberg, Network theory of microscopic and macro- scopic behavior of master equation systems, Reviews of Mod- ern physics48, 571 (1976)
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cond-mat.stat-mech 1years
2025 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
Geometric decomposition of information flow: New insights into information thermodynamics
Information flow in bipartite Markov systems is split into a housekeeping part that maintains correlations through cyclic modes and an excess part that changes mutual information through conservative forces.