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Quantum Foundations of Classical Reversible Computing.

Michael P Frank¹, Karpur Shukla²

¹Center for Computing Research, Sandia National Laboratories, Albuquerque, NM 87185, USA.

Entropy (Basel, Switzerland)

|July 2, 2021

Summary

This summary is machine-generated.

Reversible computing offers a path to overcome energy efficiency limits in digital computing. By avoiding entropy generation, reversible computation can potentially enable indefinite improvement in computing technology efficiency.

Keywords:

Gorini-Kossakowski-Sudarshan-Lindblad dynamics Landauer limit Landauer’s principle Lindbladians Rényi entropy non-equilibrium quantum thermodynamics open quantum systems resource theory of quantum thermodynamics reversible computing thermodynamics of computing von Neumann entropy

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Area of Science:

Thermodynamics
Computer Science
Quantum Physics

Background:

Conventional digital computing faces thermodynamic limits to energy efficiency.
Classical reversible computing (RC) lacks a formal foundation in modern non-equilibrium quantum thermodynamics (NEQT).

Purpose of the Study:

To develop an NEQT-based foundation for the physics of reversible computing.
To analyze the energy efficiency of reversible versus non-reversible computing paradigms.

Main Methods:

Utilizing the Gorini-Kossakowski-Sudarshan-Lindblad dynamics (Lindbladians) framework.
Incorporating resource theory, full counting statistics, and stochastic thermodynamics.
Analyzing entropy generation and correlation loss in computing architectures.

Main Results:

Landauer's Principle confirms entropy generation limits in non-reversible computing due to correlation loss.
Reversible computing implementations can potentially avoid these losses and circumvent the Landauer limit.
This suggests a pathway for indefinite improvement in digital computing efficiency.

Conclusions:

NEQT provides a robust framework for understanding the physics of reversible computing.
Reversible computing holds the potential to break through current energy efficiency barriers.
Future research will focus on determining the minimum energy dissipation for reversible computing machines based on speed.