用多光谱同步辐射图像层析重建TCV中的逃逸分布函数
Tomographic reconstruction of the runaway distribution function in TCV using multispectral synchrotron images
摘要：
利用三种不同波长间隔的滤波相机图像研究了静止TCV失控放电中观测到的同步辐射。通过层析SART程序的高动量，这些相对论粒子的空间和动量分布的高俯仰角的一部分被重建。实验估计的分布是重要的验证和完善的形成，衰变和运输模型的基础失控避免和缓解策略设计。使用测试分布，它表明，反演程序提供的估计准确到百分之几十的区域中的相空间贡献最多的同步加速器图像。我们发现，结合图像过滤周围的不同部分的发射光谱扩大了探测部分的动量空间，减少重建误差。接下来，SART算法被用来获得在选定的TCV放电的时空失控动量分布的信息。的动量分布被发现放松对雪崩式指数衰减的配置文件。异常高的螺距角和径向轮廓增加的边缘被发现的最强烈的发射粒子的分布。由环形磁场波纹引起的俯仰角散射与这幅图是一致的。另一种解释是高频不稳定性的存在与在等离子体边缘形成的逃逸壳相结合。
英文摘要：
Synchrotron radiation observed in a quiescent TCV runaway discharge is studied using filtered camera images targeting three distinct wavelength intervals. Through the tomographic SART procedure the high momentum, high pitch angle part of the spatial and momentum distribution of these relativistic particles is reconstructed. Experimental estimates of the distribution are important for verification and refinement of formation-, decay- and transport-models underlying runaway avoidance and mitigation strategy design. Using a test distribution it is demonstrated that the inversion procedure provides estimates accurate to within a few tens of percent in the region of phase-space contributing most to the synchrotron image. We find that combining images filtered around different parts of the emission spectrum widens the probed part of momentum-space and reduces reconstruction errors. Next, the SART algorithm is used to obtain information on the spatiotemporal runaway momentum distribution in a selected TCV discharge. The momentum distribution is found to relax towards an avalanche-like exponentially decaying profile. Anomalously high pitch angles and a radial profile increasing towards the edge are found for the most strongly emitting particles in the distribution. Pitch angle scattering by toroidal magnetic field ripple is consistent with this picture. An alternative explanation is the presence of high frequency instabilities in combination with the formation of a runaway shell at the edge of the plasma.
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。
