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Enhanced hyperuniformity from random reorganization.

Daniel Hexner1,2, Paul M Chaikin3, Dov Levine1

  • 1Department Physics, Technion-Israel Institute of Technology, Haifa 32000, Israel.

Proceedings of the National Academy of Sciences of the United States of America
|April 12, 2017
PubMed
Summary
This summary is machine-generated.

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Driven nonequilibrium systems can exhibit hyperuniformity, a state of extreme uniformity. This study shows that absorbing states in such systems are robust against noise and fluctuations, leading to controllable density uniformity.

Area of Science:

  • Statistical Physics
  • Condensed Matter Physics
  • Complex Systems

Background:

  • Diffusion typically leads to uniform random states.
  • Hyperuniform systems exhibit suppressed density fluctuations beyond random.
  • Equilibrium dynamics do not yield hyperuniform states, but nonequilibrium dynamics may.

Purpose of the Study:

  • To investigate hyperuniformity in driven nonequilibrium systems.
  • To determine if hyperuniformity survives noise and thermal fluctuations.
  • To explore the robustness and characteristics of absorbing states in these systems.

Main Methods:

  • Simulating a model of overlapping particles with random displacements.
  • Analyzing density fluctuations and their scaling with volume.
Keywords:
Manna modelabsorbing stateshyperuniformityrandom organization

Related Experiment Videos

  • Investigating the behavior of absorbing states below a critical particle density.

    • Main Results:

    • An absorbing state emerges below a critical density, exhibiting hyperuniformity.
    • Hyperuniformity is robust against noise, diffusion, and activity.
    • Perturbations reduce fluctuations towards a limiting behavior, [Formula: see text].

    Conclusions:

    • Driven nonequilibrium dynamics can generate robust hyperuniform states.
    • Absorbing states in these systems display controllable density uniformity.
    • Hyperuniformity offers a pathway to achieving specific material properties and understanding complex phenomena.