超卡诺奥托信息引擎中的无界功提取与零功涨落
Unbounded Work Extraction and Zero Work Fluctuations in a Super-Carnot Otto Information Engine
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中文总结 AI 辅助
该研究在量子奥托循环中引入两个连续麦克斯韦妖，构建奥托信息引擎，实现仅依赖能级间隙的无界功提取和零功涨落，且效率可超越卡诺极限，并具有优越输出功率。
中文摘要 AI 辅助
通常，随机热机的功输出受随机轨迹分布和能谱的支配。由于轨迹分布依赖于热库温度，功输出不仅受温度约束，还易受热涨落影响。为解决这些限制，我们在量子奥托循环中引入两个连续的麦克斯韦妖，形成奥托信息引擎（OIE）。我们证明，OIE的功输出仅依赖于能级间隙，从而能够实现任意功提取并消除功涨落，确保循环间功输出完全一致。此外，我们表明，即使在计入妖的记忆擦除能量成本后，该引擎的效率仍能超越标准卡诺效率。最后，我们证明，即使在考虑妖的测量时间的情况下，OIE也能提供优越的输出功率，并已执行相应的蒙特卡洛模拟。
英文摘要
Generally, the work output of stochastic heat engines is governed by the stochastic trajectory distribution and the energy spectrum. Because the trajectory distribution depends on the thermal reservoir temperatures, the work output is not only constrained by temperature but is also susceptible to thermal fluctuations. To address these limitations, we introduce two continuous Maxwell's demons into a quantum Otto cycle, forming an Otto information engine (OIE). We demonstrate that the work output of the OIE depends solely on the energy level gap, enabling arbitrary work extraction while eliminating work fluctuations, thereby ensuring cycle-to-cycle identical work output. Furthermore, we show that the engine's efficiency can surpass the standard Carnot efficiency even after accounting for the energy cost of demon's memory erasure. Finally, we show that the OIE can deliver superior output power even when the demon's measurement time is taken into account, and the corresponding Monte Carlo simulation has been executed.
发表机构
- College of Physics, Jilin University（吉林大学物理学院）
- Department of Chemistry and Department of Physics and Astronomy, State University of New York at Stony Brook（纽约州立大学石溪分校化学系和物理与天文学系）
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