论文标题
下轨火箭有效载荷的大型反射光栅原型的性能测试
Performance Testing of a Large-Format Reflection Grating Prototype for a Suborbital Rocket Payload
论文作者
论文摘要
板上的软X射线光栅光谱仪板上的平面光栅火箭实验(OGRE)希望在通过亚轨道下火箭发射时实现天体物理物体的最高分辨率软X射线光谱。对于光谱仪的成功而言,最重要的是$> 250 $的反射光栅的性能,散装了其反射光栅组件。为了测试当前的光栅制造能力,在宾夕法尼亚州立大学的材料研究所通过电子束光刻来制造了有效载荷的光栅原型,随后在Max Planck外皮物理学泛滥的Panter X射线测试设施的Max Planck Institute进行了测试。通过马尔可夫链蒙特卡洛(MCMC)采样对产生数据的贝叶斯建模表明,光栅在94%的置信度下实现了$ r_ {g}(λ/δλ)> 4500 $的OGRE单颗粒分辨率要求。由此产生的$ r_g $后验概率分布表明,该置信度水平可能是保守的估计,因为仅对有限的$ r_g参数空间进行了采样,并且该模型无法将$ r_g $的上限限制为小于Infinity。对系统的RayTrace仿真发现,观察到的数据可以通过$ r_g = \ infty $的光栅执行来复制。因此,假设可以通过系统的有限测量限制而不是$ r_g $的有限限制来解释所获得的$ r_g $后验概率分布的行为。讨论了这些结果的含义以及对测试设置的改进。
The soft X-ray grating spectrometer on board the Off-plane Grating Rocket Experiment (OGRE) hopes to achieve the highest resolution soft X-ray spectrum of an astrophysical object when it is launched via suborbital rocket. Paramount to the success of the spectrometer are the performance of the $>250$ reflection gratings populating its reflection grating assembly. To test current grating fabrication capabilities, a grating prototype for the payload was fabricated via electron-beam lithography at The Pennsylvania State University's Materials Research Institute and was subsequently tested for performance at Max Planck Institute for Extraterrestrial Physics' PANTER X-ray Test Facility. Bayesian modeling of the resulting data via Markov chain Monte Carlo (MCMC) sampling indicated that the grating achieved the OGRE single-grating resolution requirement of $R_{g}(λ/Δλ)>4500$ at the 94% confidence level. The resulting $R_g$ posterior probability distribution suggests that this confidence level is likely a conservative estimate though, since only a finite $R_g$ parameter space was sampled and the model could not constrain the upper bound of $R_g$ to less than infinity. Raytrace simulations of the system found that the observed data can be reproduced with a grating performing at $R_g=\infty$. It is therefore postulated that the behavior of the obtained $R_g$ posterior probability distribution can be explained by a finite measurement limit of the system and not a finite limit on $R_g$. Implications of these results and improvements to the test setup are discussed.