将点扩散函数重建推进到下一个层次。适用于SPHERE/ZIMPOL
Pushing Point spread function reconstruction to the next level. Application to SPHERE/ZIMPOL
摘要：
点扩散函数（PSF）重建（PSF-R）是一种成熟的技术，用于从自适应光学（AO）控制回路数据可靠且准确地确定PSF。我们已经成功地应用这种技术，以提高精度的测光和天体测量的观测NGC 6121获得的SPHERE/ZIMPOL，因为它将在即将到来的信。首先，我们介绍了使用我们的PSF-R方法PRIME（Beltramo-Martin et al. 2019）结合光瞳平面和焦平面测量重建PSF的方法，与之前的论文相比，模型和最佳拟合步骤都进行了升级。其次，我们强调，PRIME允许保持PSF拟合残差低于0.2%，超过2小时的观察，仅使用30秒的AO遥测，这可能对未来30-40米级望远镜的PSF-R遥测存储的重要后果。最后，我们部署PRIME在一个更现实的制度，使用微弱的恒星，以确定所需的精度对初始猜测参数，以确保收敛到最优解。
英文摘要：
Point spread function (PSF) reconstruction (PSF-R) is a well established technique to determine reliably and accurately the PSF from Adaptive Optics (AO) control loop data. We have successfully applied this technique to improve the precision on photometry and astrometry to observation of NGC6121 obtained with SPHERE/ZIMPOL as it will be presented in a forthcoming letter. Firstly, we present the methodology we followed to reconstruct the PSF combining pupil-plane and focal-plane measurements using using our PSF-R method PRIME (Beltramo-Martin et al. 2019), with upgrade of both the model and best-fitting steps compared to previous papers. Secondly, we highlight that PRIME allows to maintain the PSF fitting residual below 0.2% over 2 hours of observation and using only 30 s of AO telemetry, which may have important consequences for telemetry storage for PSF-R purpose on future 30-40 m class telescopes. Finally, we deploy PRIME in a more realistic regime using faint stars so as to identify the precision needed on the initial guess parameters to ensure the convergence towards the optimal solution.
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。
