Efficiency statistics of a quantum Otto cycle

Abstract

The stochastic efficiency [G. Verley et al., Nat. Commun. 5, 4721 (2014)] was introduced to evaluate the performance of energy-conversion machines in micro-scale. However, such an efficiency generally diverges when no heat is absorbed while work is produced in a thermodynamic cycle. As a result, any statistical moments of the efficiency do not exist. In this study, we come up with a different version of the definition for the stochastic efficiency which is always finite. Its mean value is equal to the conventional efficiency, and higher moments characterize the fluctuations of the cycle. In addition, the fluctuation theorems are re-expressed via the efficiency. For working substance satisfying the equipartition theorem, we clarify that the thermodynamic uncertainty relation for efficiency is valid in an Otto engine. To demonstrate our general discussions, the efficiency statistics of a quantum harmonic-oscillator Otto engine is systematically investigated. The probability that the stochastic efficiency surpasses the Carnot efficiency is explicitly obtained. This work may shed new insight for optimizing micro-machines with fluctuations.

References in corpus (9)

• Thermodynamic uncertainty relation for biomolecular processes
• Quantum Thermodynamic Cycles and quantum heat engines
• Single ion heat engine with maximum efficiency at maximum power
• The unlikely Carnot efficiency
• Efficiency statistics at all times: Carnot limit at finite power
• Universal theory of efficiency fluctuations
• Efficiency fluctuations in microscopic machines
• Group-theoretical approach to the calculation of quantum work distribution
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Cited by in corpus (6)

• Optimizing Thermodynamic Cycles with Two Finite-Sized Reservoirs
• Inelastic thermoelectric transport and fluctuations in mesoscopic system
• A microscopic theory of Curzon-Ahlborn heat engine
• Quantum Otto engine with quantum correlations
• Optimization of Asymmetric Quantum Otto Engine Cycles
• Quantum unital Otto heat engines: using Kirkwood-Dirac quasi-probability for the engine's coherence to stay alive