A strong diffusive ion mode in dense ionized matter predicted by Langevin dynamics.
A strong diffusive ion mode in dense ionized matter predicted by Langevin dynamics.
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DOI：
10.1038/ncomms14125
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发表时间：
2017-01-30
影响因子：
16.6
通讯作者：
Gregori G
中科院分区：
文献类型：
--
作者：
Mabey P;Richardson S;White TG;Fletcher LB;Glenzer SH;Hartley NJ;Vorberger J;Gericke DO;Gregori G
行星、棕矮星和中子星壳的状态和演化是由致密物质和压缩物质的性质决定的。然而，由于建立强耦合等离子体模型的固有困难，目前对输运系数的预测存在着数量级的差异。集体模是一个突出的特征，其光谱可以作为验证致密物质理论预测的重要工具。随着自由电子激光技术的最新进展，具有足够小带宽的X射线已经成为可能，这使得研究稠密物质中的低频离子模成为可能。在这里，我们给出了这些离子模的数值预测，并展示了如果朗之万动力学包含耗散过程，它们的强度和色散的显著变化。值得注意的是，在零频率附近出现了一个强扩散模，这在标准模拟中是不存在的，或者是弱得多的。我们的结果对解释稠密等离子体中的输运系数有深远的影响。由于电子和离子之间的强相互作用，研究稠密等离子体的性质是具有挑战性的，而使用静态恒温器的数值方法克服了这一困难。通过在模型中考虑耗散过程，作者预言在低能时会出现强扩散离子模。
The state and evolution of planets, brown dwarfs and neutron star crusts is determined by the properties of dense and compressed matter. Due to the inherent difficulties in modelling strongly coupled plasmas, however, current predictions of transport coefficients differ by orders of magnitude. Collective modes are a prominent feature, whose spectra may serve as an important tool to validate theoretical predictions for dense matter. With recent advances in free electron laser technology, X-rays with small enough bandwidth have become available, allowing the investigation of the low-frequency ion modes in dense matter. Here, we present numerical predictions for these ion modes and demonstrate significant changes to their strength and dispersion if dissipative processes are included by Langevin dynamics. Notably, a strong diffusive mode around zero frequency arises, which is not present, or much weaker, in standard simulations. Our results have profound consequences in the interpretation of transport coefficients in dense plasmas. Studying the properties of dense plasmas is challenging due to strong interactions between electrons and ions, and numerical methods overcome this difficulty using a static thermostat. Here the authors predict a strong diffusive ion mode at low energy by including dissipative processes in the model.