论文标题

流体动力学空间长距离相关性的出现在非平衡多体系统中

Emergence of hydrodynamic spatial long-range correlations in nonequilibrium many-body systems

论文作者

Doyon, Benjamin, Perfetto, Gabriele, Sasamoto, Tomohiro, Yoshimura, Takato

论文摘要

在大型时空尺度上,流体动力学很好地描述了广泛的多体系统中局部可观察力的非平衡动力学。在Euler量表上,人们假设每个介质区域在可用的保护法所给出的约束下独立达到最大熵状态。远离相变,最大熵状态显示指数相关性衰减,并且可以假定流体细胞的独立性在时间演化过程中存在。我们表明,这张图是不正确的:在弹道缩放下,随着时间的流逝,宏观距离隔开的区域会形成远程相关性。这些相关性采用的通用形式仅取决于模型的Euler流体动力学。它们植根于相互作用的流体模式的大规模运动中,并且是从长波长,熵最大的态度从时间开始发展的主要长期相关性。它们需要相互作用和至少两种不同的流体模式,并且与众所周知的远程相关性具有根本不同的性质,而远距离扩散或以远程平衡淬灭产生的准粒子激发而产生的远程相关性。我们提供了一个通用的理论框架来精确评估它们,这是将宏观波动理论适应欧拉量表。我们通过与数值模拟并找到出色的一致性来验证硬杆气体中的确切预测。

At large scales of space and time, the nonequilibrium dynamics of local observables in extensive many-body systems is well described by hydrodynamics. At the Euler scale, one assumes that each mesoscopic region independently reaches a state of maximal entropy under the constraints given by the available conservation laws. Away from phase transitions, maximal entropy states show exponential correlation decay, and independence of fluid cells might be assumed to subsist during the course of time evolution. We show that this picture is incorrect: under ballistic scaling, regions separated by macroscopic distances develop long-range correlations as time passes. These correlations take a universal form that only depends on the Euler hydrodynamics of the model. They are rooted in the large-scale motion of interacting fluid modes, and are the dominant long-range correlations developing in time from long-wavelength, entropy-maximised states. They require the presence of interaction and at least two different fluid modes, and are of a fundamentally different nature from well-known long-range correlations occurring from diffusive spreading or from quasi-particle excitations produced in far-from-equilibrium quenches. We provide a universal theoretical framework to exactly evaluate them, an adaptation of the macroscopic fluctuation theory to the Euler scale. We verify our exact predictions in the hard-rod gas, by comparing with numerical simulations and finding excellent agreement.

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