AI 中文总结
本文提出GPU加速的Kratos-linerad代码，采用两步成像方案处理谱线蒙特卡洛辐射转移，验证了其正确性，GPU并行性提升了速度，可高效合成速度分辨图像。
AI 中文摘要
谱线编码了天体物理气体的速度、温度和化学结构，解释谱线需要在高光学深度下准确、与局部激发一致且足够高效以合成速度分辨图像的辐射转移。本文提出Kratos-linerad，这是一款用于谱线的GPU加速蒙特卡洛辐射转移代码。能级布居可与逃逸光子分布一起迭代至统计平衡，通过恒定内存采样表处理与角度相关的部分频率再分布。该代码采用两步成像方案处理谱线转移：蒙特卡洛过程采样速度分辨的散射发射率，确定性光线追踪过程合成与散射几何解耦的通道图。验证结果重现了逃逸谱的解析标度和成像双峰轮廓，GPU并行性使两个阶段足够快速，可用于……
英文摘要
Spectral lines encode the velocity, the temperature, and the chemical structure of astrophysical gas; interpreting them requires radiative transfer that is accurate at high optical depth, consistent with the local excitation, and efficient enough to synthesize velocity-resolved images. We present Kratos-linerad, a GPU-accelerated Monte Carlo radiative transfer code for spectral lines. The level populations can be iterated to statistical equilibrium together with the escaping photon distribution, treating angle-dependent partial frequency redistribution through constant-memory sampling tables. The code adopts the two-step imaging scheme to line transfer, in which a Monte Carlo pass samples a velocity-resolved scattering emissivity, and a deterministic ray-tracing pass synthesizes channel maps decoupled from the scattering geometry. Validation reproduces the analytic scaling of escaped spectra and the imaging double-peak profiles. GPU parallelism enables both stages sufficiently fast for routine application to astrophysically realistic models.
Comments13 pages, 7 figures, to be submitted
