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Experimental Realization of Diffusion with Stochastic Resetting.

Ofir Tal-Friedman1, Arnab Pal2, Amandeep Sekhon2

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Researchers experimentally realized stochastic resetting of colloidal particles using holographic optical tweezers. This study validates theoretical predictions and reveals fundamental energetic costs for realistic resetting protocols.

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Area of Science:

  • Physics
  • Statistical Mechanics
  • Soft Matter

Background:

  • Stochastic resetting is a key concept in nonequilibrium statistical mechanics, observed in diverse natural and artificial systems.
  • Diffusion with stochastic resetting is a fundamental model, but experimental platforms for its study are lacking, hindering research progress.

Purpose of the Study:

  • To experimentally realize and investigate diffusion with stochastic resetting using a controlled platform.
  • To validate existing theoretical predictions for stochastic resetting phenomena.
  • To quantify the energetic cost associated with resetting processes in different scenarios.

Main Methods:

  • Utilized holographic optical tweezers to create a precisely controlled environment for colloidal particle manipulation.
  • Implemented a stochastic resetting protocol for diffusing colloidal particles within the optical trap.
  • Measured steady-state and first-passage properties to analyze the resetting dynamics and energetic costs.

Main Results:

  • Successfully demonstrated the experimental realization of colloidal particle diffusion and resetting.
  • Provided the first experimental validation of key theoretical results in stochastic resetting.
  • Quantified the energetic cost of resetting, showing it cannot be minimized indefinitely due to practical constraints.

Conclusions:

  • The developed holographic optical tweezer platform enables robust experimental studies of stochastic resetting phenomena.
  • Fundamental energetic costs are associated with realistic resetting protocols, challenging assumptions of arbitrary energy minimization.
  • This work paves the way for exploring more complex resetting dynamics beyond simple diffusion.