Autonomous Quantum Heat Engines in Superconducting Electromechanical Circuits: Exergy Optimization and Fluctuations
Indonesia 
Timor-Leste Timor-Leste 
Abstract
Autonomous quantum heat engines offer a promising route for converting microscopic thermal gradients into useful energy, yet conventional power and efficiency metrics often overlook output quality and stochastic instability. This study aimed to optimize exergy conversion and characterize energy-transfer fluctuations in a superconducting electromechanical circuit operating without time-dependent external control. A quantitative computational design combined a Lindblad master-equation model, nonequilibrium exergy analysis, full counting statistics, quantum-trajectory simulations, and constrained multiobjective optimization. Ten thousand physically plausible circuit configurations were screened, of which 2,184 satisfied stability, positivity, energy-conservation, and positive-output criteria. Power-only optimization generated 1.71 fW of useful power, with 47.3% exergy efficiency, 1.17 fW exergy destruction, and a Fano factor of 1.89. Exergy optimization increased efficiency to 68.9% while retaining 1.12 fW of useful power. Fluctuation-aware optimization produced 1.06 fW at 64.7% exergy efficiency, reduced exergy destruction to 0.39 fW, and yielded a sub-Poissonian Fano factor of 0.62. Moderate electromechanical coupling, near-zero detuning, and balanced load extraction consistently improved useful energy quality and operational stability. These findings demonstrate that maximum power is not the most favorable thermodynamic criterion and establish exergy and fluctuation statistics as complementary design measures for reliable autonomous superconducting quantum thermal machines under experimentally realistic parameter constraints.
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Copyright (c) 2026 Fiqih Ananda, Victor Gonçalves, Ana Costa
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