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Mode Selection in Compressible Active Flow Networks.

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This summary is machine-generated.

Active friction in complex networks drives large-scale dynamics by selecting discrete states. This contrasts with thermal systems, suggesting reduced modes dominate macroscopic responses in active matter.

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Area of Science:

  • Nonlinear dynamics
  • Active matter physics
  • Network science

Background:

  • Many nonequilibrium systems exhibit large-scale dynamics driven by local energy inputs.
  • Understanding the behavior of active flow networks is crucial in physics and biology.

Purpose of the Study:

  • To introduce and analyze a nonlinear model for compressible active flow networks.
  • To investigate how active friction influences network dynamics and state selection.

Main Methods:

  • Developed an analytically tractable nonlinear model for active flow networks.
  • Applied perturbation theory to predict stationary states in noisy networks.
  • Utilized Bayesian state estimation with a hidden Markov model on simulated data.

Main Results:

  • Active friction selects discrete dynamical states with limited oscillation modes.
  • Predicted stationary states show good agreement with hidden Markov model analysis.
  • Macroscopic responses are dominated by a reduced number of modes, unlike thermal equilibrium.

Conclusions:

  • Active friction provides a mechanism for state selection and mode reduction in nonequilibrium networks.
  • The findings offer insights into actomyosin networks, cytoplasmic flows, and topological sound modes.
  • The model serves as a tool for studying spectral band gaps in active matter.