基于几何预采样的无序系统电子停止的高效从头计算：对液态水的应用
Efficient ab initio calculation of electronic stopping in disordered systems via geometry pre-sampling: application to liquid water
摘要：
快速离子$S_e(v)$的电子停止曲线的知识，特别是在布拉格峰附近，是重要的理解辐射损伤。然而，在实验上，确定轻离子的这种特征是非常具有挑战性的，特别是在无序系统中，例如液态水和生物组织。实时含时密度泛函理论（rt-TDDFT）的最新发展使$S_e(v)$沿纳米尺度轨道的计算成为可能。然而，获得可以与观测值进行比较的有意义的统计平均$S_e(v)$仍然是一个挑战。在这项工作中，利用探测到的弹丸和从弹丸到目标中的原子的距离的局部电子结构之间的相关性，我们设计了一个轨迹预采样方案，选择，几何，一个小的一组短的轨迹，以加速通过rt-TDDFT计算的平均$S_e(v)$的收敛。对于液态水中的质子，我们首先计算从质子到最近的氧原子$ϕ_R(r_{p{\rightarrow}O})$的距离的参考概率分布函数（PDF），其轨迹的长度与实验采样的长度相似。然后，顺序地选择短轨迹，使得累积的PDF以越来越高的精度再现$ϕ_R(r_{p{\rightarrow}O})$。使用这些预先采样的轨迹，我们证明了平均$S_e(v_p)$收敛在整个速度范围内，少于八个轨迹，而其他平均方法使用随机和均匀分布的轨迹需要大约十倍的计算工作量。这使我们能够比较$S_e(v_p)$曲线的实验数据，并评估广泛使用的经验表的基础上布拉格规则。
英文摘要：
Knowledge of the electronic stopping curve for swift ions, $S_e(v)$, particularly around the Bragg peak, is important for understanding radiation damage. Experimentally, however, the determination of such feature for light ions is very challenging, especially in disordered systems such as liquid water and biological tissue. Recent developments in real-time time-dependent density functional theory (rt-TDDFT) have enabled the calculation of $S_e(v)$ along nm-sized trajectories. However, it is still a challenge to obtain a meaningful statistically averaged $S_e(v)$ that can be compared to observations. In this work, taking advantage of the correlation between the local electronic structure probed by the projectile and the distance from the projectile to the atoms in the target, we devise a trajectory pre-sampling scheme to select, geometrically, a small set of short trajectories to accelerate the convergence of the averaged $S_e(v)$ computed via rt-TDDFT. For protons in liquid water, we first calculate the reference probability distribution function (PDF) for the distance from the proton to the closest oxygen atom, $ϕ_R(r_{p{\rightarrow}O})$, for a trajectory of a length similar to those sampled experimentally. Then, short trajectories are sequentially selected so that the accumulated PDF reproduces $ϕ_R(r_{p{\rightarrow}O})$ to increasingly high accuracy. Using these pre-sampled trajectories, we demonstrate that the averaged $S_e(v_p)$ converges in the whole velocity range with less than eight trajectories, while other averaging methods using randomly and uniformly distributed trajectories require approximately ten times the computational effort. This allows us to compare the $S_e(v_p)$ curve to experimental data, and assess widely used empirical tables based on Bragg's rule.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
