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Time-Resolved Stochastic Dynamics of Quantum Thermal Machines
Abhaya S Hegde1, Patrick P Potts2, Gabriel T Landi1
1University of Rochester, Department of Physics and Astronomy, Rochester, New York 14627, USA.
Physical Review Letters
|May 2, 2025
Summary
We developed a framework to analyze quantum thermal machines by classifying their dynamics into enginelike, coolinglike, or idle cycles. This helps determine useful cycle fractions and operational consistency, crucial for quantum dot experiments.
Area of Science:
- Quantum thermodynamics
- Mesoscopic physics
- Statistical mechanics
Background:
- Quantum thermal machines exhibit continuous heat flow at steady state.
- Discrete quantum jumps represent finite heat exchange with the environment.
- Understanding cycle dynamics is key to characterizing machine performance.
Purpose of the Study:
- To resolve quantum thermal machine dynamics into discrete cycles.
- To analyze cycle statistics and durations for thermodynamic tasks.
- To introduce intermittency as a measure of operational consistency.
Main Methods:
- Framework for classifying dynamics into enginelike, coolinglike, and idle cycles.
- Statistical analysis of individual cycle types and their durations.
- Assessment of intermittency through idle cycle frequency and distribution.
Main Results:
- Quantification of the fraction of cycles useful for thermodynamic tasks.
- Determination of average waiting times between specific cycle types.
- Characterization of operational consistency using intermittency.
Conclusions:
- The framework provides a novel approach to characterizing quantum thermal machines.
- Analysis of cycle statistics and intermittency offers deeper insights into machine performance.
- Significant relevance for experiments on mesoscopic transport in quantum dots.
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