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This study experimentally demonstrates thermodynamically optimal transport in finite time using microparticles. It confirms optimal information erasure protocols and achieves fundamental bounds on speed, dissipation, and accuracy.

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Area of Science:

  • Physics
  • Information Theory
  • Statistical Mechanics

Background:

  • Optimal transport theory provides a framework for optimization across disciplines.
  • In physics, it sets fundamental bounds on thermodynamic dissipation in finite-time processes, extending the second law.
  • Conventional laws cannot characterize dissipation in finite-time processes.

Purpose of the Study:

  • To experimentally realize thermodynamically optimal transport in finite time.
  • To apply optimal transport to information processing, specifically information erasure.
  • To investigate the trade-off between speed, dissipation, and accuracy in information erasure.

Main Methods:

  • Experimental realization using optically trapped microparticles.
  • Development of scanning optical tweezers for precise control of potential profiles.
  • Implementation of optimal finite-time protocols for information erasure.

Main Results:

  • Achieved minimal thermodynamic dissipation within a finite time.
  • Confirmed that excess dissipation in information erasure is determined by the Wasserstein distance.
  • Saturated the bound governing the trade-off between speed, dissipation, and accuracy.

Conclusions:

  • Experimental validation of thermodynamically optimal transport principles.
  • Demonstrated the link between optimal transport geometry (Wasserstein distance) and information erasure costs.
  • Provided guiding principles for efficient information processing by saturating fundamental trade-off bounds.