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arXiv · 2608.16623

Carnot Meets Quantum Information: Thermal Machine Driven by Probabilistic Non-orthogonal State Discrimination

Tan-Ji Zhou·Yun-Qian Lin·Yu-Han Ma·C. P. Sun
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Abstract

While the impossibility of perfectly identifying non-orthogonal states is a cornerstone of quantum information science, their probabilistic discrimination is nonetheless permissible. Here, we propose a two-reservoir quantum machine driven by this mechanism to map its functional boundaries across the parameter space of the state overlap $\mu$ and the Carnot efficiency $\eta_C$. Within this $\eta_C$-$\mu$ plane, the machine exhibits phase-transition-like functional switching among a pure heat-engine phase, a mixed phase, and a dissipative phase. We identify critical thresholds governing these transitions: strong thermal driving ($\eta_C \ge 0.5$) unconditionally guarantees positive work extraction, whereas weak driving ($\eta_C \lesssim 0.13$) induces an anomalous reentrant transition, where increasing $\mu$ unexpectedly restores engine functionality after a purely dissipative regime. Our results explicitly demonstrate how quantum mechanics and thermodynamics jointly constrain information-to-energy conversion.

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Tan-Ji Zhou, Yun-Qian Lin, Yu-Han Ma, C. P. Sun. 2026-08-17. Carnot Meets Quantum Information: Thermal Machine Driven by Probabilistic Non-orthogonal State Discrimination. https://arxiv.org/abs/2608.16623

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