---
res:
bibo_abstract:
- Most natural and engineered information-processing systems transmit information
via signals that vary in time. Computing the information transmission rate or
the information encoded in the temporal characteristics of these signals requires
the mutual information between the input and output signals as a function of time,
i.e., between the input and output trajectories. Yet, this is notoriously difficult
because of the high-dimensional nature of the trajectory space, and all existing
techniques require approximations. We present an exact Monte Carlo technique called
path weight sampling (PWS) that, for the first time, makes it possible to compute
the mutual information between input and output trajectories for any stochastic
system that is described by a master equation. The principal idea is to use the
master equation to evaluate the exact conditional probability of an individual
output trajectory for a given input trajectory and average this via Monte Carlo
sampling in trajectory space to obtain the mutual information. We present three
variants of PWS, which all generate the trajectories using the standard stochastic
simulation algorithm. While direct PWS is a brute-force method, Rosenbluth-Rosenbluth
PWS exploits the analogy between signal trajectory sampling and polymer sampling,
and thermodynamic integration PWS is based on a reversible work calculation in
trajectory space. PWS also makes it possible to compute the mutual information
between input and output trajectories for systems with hidden internal states
as well as systems with feedback from output to input. Applying PWS to the bacterial
chemotaxis system, consisting of 182 coupled chemical reactions, demonstrates
not only that the scheme is highly efficient but also that the number of receptor
clusters is much smaller than hitherto believed, while their size is much larger.@eng
bibo_authorlist:
- foaf_Person:
foaf_givenName: Manuel
foaf_name: Reinhardt, Manuel
foaf_surname: Reinhardt
- foaf_Person:
foaf_givenName: Gašper
foaf_name: Tkačik, Gašper
foaf_surname: Tkačik
foaf_workInfoHomepage: http://www.librecat.org/personId=3D494DCA-F248-11E8-B48F-1D18A9856A87
orcid: 0000-0002-6699-1455
- foaf_Person:
foaf_givenName: Pieter Rein
foaf_name: Ten Wolde, Pieter Rein
foaf_surname: Ten Wolde
bibo_doi: 10.1103/PhysRevX.13.041017
bibo_issue: '4'
bibo_volume: 13
dct_date: 2023^xs_gYear
dct_isPartOf:
- http://id.crossref.org/issn/2160-3308
dct_language: eng
dct_publisher: American Physical Society@
dct_title: 'Path weight sampling: Exact Monte Carlo computation of the mutual information
between stochastic trajectories@'
...