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Exploiting Live Imaging to Track Nuclei During Myoblast Differentiation and Fusion

Exploiting Live Imaging to Track Nuclei During Myoblast Differentiation and Fusion

Published on: April 13, 2019

Information ratchets exploiting spatially structured information reservoirs.

Richard E Spinney¹, Mikhail Prokopenko¹, Dominique Chu²

¹Complex Systems Research Group and Centre for Complex Systems, The University of Sydney, Sydney, New South Wales 2006, Australia.

Physical Review. E

|September 27, 2018

Summary

This summary is machine-generated.

Mechanized Maxwell's demons extract work using information reservoirs. Their efficiency depends critically on the reservoir's dimensionality, with higher dimensions enabling greater work extraction.

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Area of Science:

Statistical Physics
Information Theory
Computational Science

Background:

Maxwell's demons, or information ratchets, link computation, information theory, and statistical physics.
They extract work from heat reservoirs by exploiting low-entropy information reservoirs.
Prior models often neglected the cost of accessing information or assumed idealized reservoirs.

Purpose of the Study:

To investigate the impact of information reservoir dimensionality on the performance of mechanized Maxwell's demons.
To account for the physical cost of accessing information from structured reservoirs.
To analyze work extraction efficiency and phase diagrams based on reservoir dimensions.

Main Methods:

Developing a model that incorporates the cost of delivering bits to the demon.
Analyzing biased random walks on d-dimensional (Z^d) information reservoirs.
Deriving expressions for net-extracted work and exact probabilities of recurrence.

Main Results:

The dimensionality of the information reservoir significantly affects the demon's performance and phase diagram.
Work extraction is greatly reduced for conventional one-dimensional information tapes.
Two critical dimensions were identified: d>2 for zero-bias work extraction and d>4 for optimal unbiased work extraction.

Conclusions:

The physical structure and dimensionality of information reservoirs are crucial for understanding information ratchets.
Higher-dimensional reservoirs offer greater potential for work extraction.
The study provides a generalized framework for analyzing information ratchets in various dimensionalities.