The Raymond and Beverly Sackler School of Physics and Astronomy, Tel Aviv University, Tel Aviv 69978, Israel.
Phys Rev Lett. 2019 Oct 25;123(17):178102. doi: 10.1103/PhysRevLett.123.178102.
Entropy and free-energy estimation are key in thermodynamic characterization of simulated systems ranging from spin models through polymers, colloids, protein structure, and drug design. Current techniques suffer from being model specific, requiring abundant computation resources and simulation at conditions far from the studied realization. Here, we present a universal scheme to calculate entropy using lossless-compression algorithms and validate it on simulated systems of increasing complexity. Our results show accurate entropy values compared to benchmark calculations while being computationally effective. In molecular-dynamics simulations of protein folding, we exhibit unmatched detection capability of the folded states by measuring previously undetectable entropy fluctuations along the simulation timeline. Such entropy evaluation opens a new window onto the dynamics of complex systems and allows efficient free-energy calculations.
熵和自由能估计是模拟系统热力学特性分析的关键，这些系统的范围从自旋模型到聚合物、胶体、蛋白质结构和药物设计。当前的技术存在模型特异性的问题，需要大量的计算资源，并在远离研究实现的条件下进行模拟。在这里，我们提出了一种使用无损压缩算法计算熵的通用方案，并在越来越复杂的模拟系统上对其进行了验证。我们的结果与基准计算相比显示出准确的熵值，同时具有计算效率。在蛋白质折叠的分子动力学模拟中，我们通过测量模拟时间线上以前无法检测到的熵波动，展示了对折叠状态的无与伦比的检测能力。这种熵评估为复杂系统的动力学打开了一个新窗口，并允许进行有效的自由能计算。
