论文标题
Desarrollo del Software de Interfaz de Usuario para elespectrógrafoGrafoGrafoStronómicoColoresinstalado en el observatorio de la Mayora
Desarrollo del software de interfaz de usuario para el espectrógrafo astronómico COLORES instalado en el observatorio de la Mayora
论文作者
论文摘要
该论文项目源于位于La Mayora的站（Bootes 2）的光谱仪（Bootes 2），属于Burst Observer和Optical Transient Exploring System（Bootes）望远镜的网络。诸如Bootes 2的机器人望远镜具有许多优点，具有在反应时间非常低的情况下进行多种观测值的能力。这使得获得有关天文机构定位和表征的大量数据。使用此工具，现在可以从观测值中提取多种新参数，从而为该站提供更完整，更通用的仪器，以获取更有趣的科学信息。 对于此任务，将执行一系列脚本。特别是两个，一个用于光谱仪的校准，另一个用于图像处理的负荷及其光谱的提取。这将使用Spyder软件（Python）进行，此外，将进行大量测试以验证该软件是否正常运行。一旦进行了这些测试，它将在望远镜的网页中实现。 包括Astropy在内的几个库将用于此目的，其中包括用于处理Python中天文数据的完整软件包和Matplotlib，该软件包允许使用从阵列中包含的数据生成的图形。此外，还将使用几种图像采集技术，例如：过滤，高斯调整和干扰区域的使用。所有这一切，将从望远镜中提取的数据进行优化以实现所需的结果。
This thesis project arises from the need to put into operation the spectrograph (COLORES) of the station (BOOTES 2), located in La Mayora and belonging to the network of Burst Observer and Optical Transient Exploring System (BOOTES) telescopes. A robotic telescope such as the one located at BOOTES 2 has, among its many virtues, the ability to perform a multitude of observations with a very low reaction time. This makes it possible to obtain a large amount of data on the positioning and characterization of astronomical bodies. With this tool in operation, it will now be possible to extract a multitude of new parameters from the observations, providing this station with a more complete and versatile instrument with which to obtain more interesting scientific information. For this task, a series of scripts will be performed. Specifically two, one for the calibration of the spectrograph and another one in charge of the image processing and the extraction of its spectrum. This will be carried out using Spyder software (Python), in which, in addition, numerous tests will be carried out to verify that the software works perfectly. Once these tests have been carried out, it will be implemented in the telescope's Web page for its use. Several libraries will be used for this purpose, including Astropy, which includes a complete package for handling astronomical data in Python, and Matplotlib, which allows the use of graphics generated from data contained in arrays. In addition, several image acquisition techniques will be used, such as: filtering, Gaussian adjustment, and use of regions of interferences. With all this, the data extracted from the telescope will be optimized to achieve the desired results.
