论文标题
用于虚拟访问自适应光学遥测数据
Towards virtual access of adaptive optics telemetry data
论文作者
论文摘要
目前，最终用户目前无法访问大量的自适应启示（AO）控制环数据和遥测。扩大对这些数据的访问有可能改变许多方面的AO景观，以解决多个用例，例如系统的PSF推导，湍流表征和系统控制的优化。我们解决共享这些数据的最大障碍之一：缺乏标准化，阻碍了访问。我们为AO遥测提出了一个面向对象的Python软件包，该软件包的数据模型从基于灵活的图像传输系统（fits）的强调档案准备就绪的数据交换标准中抽象了用户。它的设计支持来自现有和未来的AO系统的数据，无论是原始格式还是从实际仪器详细信息中抽象出来。我们用来自10m级观测值的Active AO系统的数据来体现其用法，其中两个人目前得到了支持（AOF和KECK），并提供了更多计划。
Large amounts of Adaptive-Optics (AO) control loop data and telemetry are currently inaccessible to end-users. Broadening access to those data has the potential to change the AO landscape on many fronts, addressing several use-cases such as derivation of the system's PSF, turbulence characterisation and optimisation of system control. We address one of the biggest obstacles to sharing these data: the lack of standardisation, which hinders access. We propose an object-oriented Python package for AO telemetry, whose data model abstracts the user from an underlining archive-ready data exchange standard based on the Flexible Image Transport System (FITS). Its design supports data from a wide range of existing and future AO systems, either in raw format or abstracted from actual instrument details. We exemplify its usage with data from active AO systems on 10m-class observatories, of which two are currently supported (AOF and Keck), with plans for more.
