等离子体中非热粒子的能量分配：或库仑对数的再讨论
The energy partitioning of non-thermal particles in a plasma: or the Coulomb logarithm revisited
摘要：
Brown，Preston，and Singleton（BPS）计算了高电离、弱耦合到中等耦合等离子体中带电粒子的阻止本领。在回顾了这个计算背后的主要思想，我们使用BPS导出的福克-普朗克方程来计算穿过等离子体的带电粒子的电子-离子能量分配。这种应用的动机是惯性约束聚变的点火--传递给离子的能量越多，点火的机会就越大，反之亦然。因此，重要的是要尽可能准确地计算电子和离子的部分能量损失，因为这可能对法国的激光兆焦耳（LMJ）设施和美国的国家点火设施（NIF）产生影响。计算穿过等离子体的带电粒子的电子-离子能量分裂的传统方法涉及对阻止本领dE/dx进行积分。然而，当带电粒子减速并被热化到背景等离子体中时，这种计算电子-离子能量分裂的方法就失效了。结果，该方法遭受T/E0阶的系统误差，其中T是等离子体温度，E0是带电粒子的初始能量。例如，在DT融合的情况下，这可能导致高达10%左右的不确定性。这里提出的形式主义是为了解释热化过程，相反，它提供了接近精确的结果。
英文摘要：
The charged particle stopping power in a highly ionized and weakly to moderately coupled plasma has been calculated to leading and next-to-leading order by Brown, Preston, and Singleton (BPS). After reviewing the main ideas behind this calculation, we use a Fokker-Planck equation derived by BPS to compute the electron-ion energy partitioning of a charged particle traversing a plasma. The motivation for this application is ignition for inertial confinement fusion -- more energy delivered to the ions means a better chance of ignition, and conversely. It is therefore important to calculate the fractional energy loss to electrons and ions as accurately as possible, as this could have implications for the Laser Megajoule (LMJ) facility in France and the National Ignition Facility (NIF) in the United States. The traditional method by which one calculates the electron-ion energy splitting of a charged particle traversing a plasma involves integrating the stopping power dE/dx. However, as the charged particle slows down and becomes thermalized into the background plasma, this method of calculating the electron-ion energy splitting breaks down. As a result, the method suffers a systematic error of order T/E0, where T is the plasma temperature and E0 is the initial energy of the charged particle. In the case of DT fusion, for example, this can lead to uncertainties as high as 10% or so. The formalism presented here is designed to account for the thermalization process, and in contrast, it provides results that are near-exact.
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。
