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Role of interactions in nonequilibrium transformations.

Maria Rose1, Sreekanth K Manikandan2

  • 1School of Pure and Applied Physics, Mahatma Gandhi University, 686560 Kottayam, India.

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|May 17, 2024
PubMed
Summary
This summary is machine-generated.

We developed a method to decompose the distance in complex systems into independent and interaction terms. This helps understand how interactions affect nonequilibrium transformations and system dynamics.

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Area of Science:

  • Statistical Mechanics
  • Complex Systems Theory
  • Information Theory

Background:

  • Understanding nonequilibrium transformations in complex systems is challenging.
  • Quantifying the role of interactions in these transformations is crucial.
  • Existing methods often struggle to disentangle different orders of interactions.

Purpose of the Study:

  • To develop a general framework for decomposing the distance to a target state in complex systems.
  • To quantify the contributions of different orders of interactions to nonequilibrium transformations.
  • To provide practical insights into controlling and facilitating transformations by manipulating interactions.

Main Methods:

  • Decomposition of state distance into independent and interaction-dependent terms.
  • Quantification of interactions using relative mutual information.
  • Application to thermal relaxation of interacting colloidal particles.
  • Analysis of systems with pairwise and triplet interactions.

Main Results:

  • The distance metric successfully decomposes into independent and interaction terms.
  • Increasing pairwise interaction strength prolongs the nonequilibrium state in colloidal systems.
  • The approach distinguishes contributions from pairwise and triplet interactions.
  • Demonstrated ability to identify interactions that facilitate transformations.

Conclusions:

  • The proposed decomposition provides a powerful tool for analyzing complex systems.
  • Relative mutual information effectively quantifies interaction effects on transformations.
  • This framework offers a pathway to engineer systems by controlling interaction strengths.