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Area of Science:

  • Active Matter Physics
  • Statistical Mechanics
  • Soft Condensed Matter

Background:

  • Overdamped models often neglect inertial effects in active matter.
  • Inertia can significantly influence the dynamics of self-propelled particles.
  • Understanding these effects is key to predicting active matter behavior.

Purpose of the Study:

  • To investigate the role of inertial effects in one-dimensional chains of interacting active particles.
  • To analyze the interplay between persistence, interaction, and inertial timescales.
  • To identify experimentally observable signatures of inertia in active matter systems.

Main Methods:

  • Utilized a Green's function approach to derive key dynamic quantities.
  • Analyzed mean-squared displacement and mean-squared change in velocity.
  • Quantified non-Gaussian deviations using excess kurtosis and studied probability distributions.

Main Results:

  • Identified multiple crossovers between ballistic, diffusive, and subdiffusive regimes.
  • Derived analytic expressions for scaling coefficients and crossover times.
  • Observed time-dependent probability distributions showing distinct data collapses, confirming scaling behavior.

Conclusions:

  • Inertial effects significantly alter the dynamics of interacting active particles.
  • The developed framework connects multiparticle interactions to microscopic dynamics.
  • The study provides experimentally accessible signatures for detecting inertia in active matter.