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Stochastic resetting by a random amplitude.

Marcus Dahlenburg1,2, Aleksei V Chechkin1,3, Rina Schumer4

  • 1Institute for Physics & Astronomy, University of Potsdam, 14476 Potsdam, Germany.

Physical Review. E
|June 17, 2021
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Summary
This summary is machine-generated.

This study introduces generalized stochastic resetting with random amplitudes, enhancing search efficiency and optimizing encounter dynamics in various fields. The new model allows for partial resets or overshooting the origin, expanding its applicability.

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Area of Science:

  • Statistical Physics
  • Complex Systems

Background:

  • Stochastic resetting optimizes diffusion-based encounter dynamics.
  • Current models reset particles precisely to the origin.

Purpose of the Study:

  • Generalize stochastic resetting by introducing random resetting amplitudes.
  • Explore dynamics resulting from variable resetting magnitudes.

Main Methods:

  • Introduced random resetting amplitudes to the standard stochastic resetting model.
  • Analyzed different scenarios of the random-amplitude process.
  • Investigated the resulting diffusive dynamics.

Main Results:

  • Demonstrated that random resetting amplitudes can lead to partial resets or overshooting the origin.
  • Characterized the novel dynamics arising from these generalized resetting strategies.

Conclusions:

  • Random-amplitude stochastic resetting offers a more flexible and potentially more efficient strategy for optimizing diffusive processes.
  • The generalized model has broad applications in areas like geophysics, population dynamics, and financial markets.