Exoplanet imaging data challenge, phase 2

<strong>Datasets for the second phase of the Exoplanet Imaging Data Challenge</strong> (https://exoplanet-imaging-challenge.github.io). The second phase of the Exoplanet Imaging Data Challenge is focused on the characterisation of exoplanet signals in high-contrast imaging data. The participants must perform two tasks: provide (1) astrometry of the detected signals, and (2) spectrophotometry of the detected signals. For this phase, we therefore provide with <strong>8</strong> high-contrast data sets, taken with two integral field spectrographs: SPHERE-IFS installed at the Very Large Telescope (VLT, Chile) and GPI installed at the Gemini-South telescope (Chile). Each data set consists of the following files (in <em>.fits</em> format): (a) <em>image_cube_instxx.fits</em>: the coronagraphic multispectral image cube, acquired in pupil-stabilized mode;<br> (b) <em>parallactic_angles_instxx.fits</em>: the corresponding parallactic angle and airmass variation during the observation sequence;<br> (c) <em>wavelength_vect_instxx.fits</em>: the corresponding wavelength vector for each spectral channel;<br> (d) <em>psf_cube_instxx.fits</em>: the non-coronagraphic (point spread function) multispectral image of the target star;<br> (e) <em>first_guess_astrometry_instxx.fits</em>: a first guess position w.r.t the star of the (2 or 3) injected planetary signals. Each data set has 2 to 3 injected planetary signals in various locations.<br> Each data set has very different observing conditions, from very good to very bad. <em>Additional information and ressources can be found on the website and dedicated Github repository.</em> <em>The results of the data challenge must be submitted directly by participants on the EvalAI platform.</em>

**系外行星成像数据挑战赛第二阶段数据集**（https://exoplanet-imaging-challenge.github.io）。
系外行星成像数据挑战赛第二阶段聚焦于高对比度成像数据中的系外行星信号特征表征。参赛选手需完成两项任务：(1) 对探测到的信号开展天体测量，(2) 对探测到的信号进行分光光度测量。
本阶段共提供**8**组高对比度数据集，采集自两台积分场光谱仪（integral field spectrographs）：安装于智利甚大望远镜（Very Large Telescope, VLT）的SPHERE-IFS，以及安装于智利双子南座望远镜的GPI。
每组数据集均采用.fits格式存储，包含以下文件：
(a) `image_cube_instxx.fits`：光瞳稳定模式（pupil-stabilized mode）下采集的日冕多光谱图像立方数据；
(b) `parallactic_angles_instxx.fits`：观测序列中对应的视差角与大气质量变化量；
(c) `wavelength_vect_instxx.fits`：各光谱通道对应的波长矢量；
(d) `psf_cube_instxx.fits`：目标恒星的非日冕点扩散函数（point spread function, PSF）多光谱图像立方数据；
(e) `first_guess_astrometry_instxx.fits`：注入的2或3颗行星信号相对于宿主恒星的初始估计位置。
每组数据集均包含2至3个分布于不同位置的注入行星信号，且各数据集的观测条件差异显著，覆盖极佳至极差的多种观测工况。
更多信息与资源可查阅官网及专属GitHub仓库。参赛选手需通过EvalAI平台直接提交本次数据挑战赛的参赛结果。