发表机构
Graduate School of China Academy of Engineering Physics; School of Physics and Astronomy, Beijing Normal University（中国工程物理研究院研究生院; 北京师范大学物理与天文学院）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
该研究提出由概率非正交态区分驱动的双热源量子机器，揭示其在η_C-μ参数空间的功能相变，明确量子力学与热力学共同约束信息到能量的转换。
AI 中文摘要
虽然完美识别非正交态的不可能性是量子信息科学的基石，但对其进行概率性区分是允许的。本文提出一种由该机制驱动的双热源量子机器，以在态重叠度μ和卡诺效率η_C的参数空间中绘制其功能边界。在η_C-μ平面内，该机器表现出类似相变的功能切换，分为纯热机相、混合相和耗散相。我们确定了控制这些转变的临界阈值：强热驱动（η_C ≥ 0.5）无条件保证正功提取，而弱驱动（η_C ≲ 0.13）会引发异常的重入转变，即增大μ会在纯耗散态后意外恢复机器功能。我们的结果明确展示了量子力学与热力学如何共同约束信息到能量的转换。
英文摘要
While the impossibility of perfectly identifying non-orthogonal states is a cornerstone of quantum information science, they can nevertheless be distinguished with a finite error probability. Here, we propose a two-reservoir quantum machine driven by such non-orthogonal-state discrimination to map its functional boundaries across the parameter space of the state overlap $μ$ and the Carnot efficiency $η_C$. Within this $η_C$-$μ$ 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 ($η_C>0.5$) unconditionally guarantees positive work extraction, whereas weak driving ($η_C \lesssim 0.13$) induces an anomalous reentrant transition, where increasing $μ$ unexpectedly restores engine functionality after a purely dissipative regime. Our results explicitly demonstrate how quantum mechanics and thermodynamics jointly constrain information-to-energy conversion.
Comments6 pages, 3 figures, comments are welcome!
