In this communication, we report on the results of the second phase of the Exoplanet Imaging Data Challenge started in 2019. This second phase focuses on the characterization of point sources (exoplanet signals) within multispectral high-contrast images from ground-based telescopes. We collected eight data sets from two high-contrast integral field spectrographs (namely Gemini-S/GPI and VLT/SPHERE-IFS) that we calibrated homogeneously and in which we injected a handful of synthetic planetary signals (ground truth) to be characterized by the data challenge participants. The tasks of the participants consist of (1) extracting the precise astrometry of each injected planetary signals, and (2) extracting the precise spectro-photometry of each injected planetary signal. Additionally, the participants may provide the 1-sigma uncertainties on their estimation for further analyses. When available, the participants can also provide the posterior distribution used to estimate the position/spectrum and uncertainties. The data are permanently available on a Zenodo repository and the participants can submit their results through the EvalAI platform. The EvalAI submission platform opened on April 2022 and closed on the 31st of May 2024. In total, we received 4 valid submissions for the astrometry estimation and 4 valid submissions for the spectrophotometry (each submission, corresponding to one pipeline, has been submitted by a unique participant). In this communication, we present an analysis and interpretation of the results.
The Exoplanet Imaging Data Challenge is a community-wide effort meant to offer a platform for a fair and common comparison of image processing methods designed for exoplanet direct detection. For this purpose, it gathers on a dedicated repository (Zenodo), data from several high-contrast ground-based instruments worldwide in which we injected synthetic planetary signals. The data challenge is hosted on the CodaLab competition platform, where participants can upload their results. The specifications of the data challenge are published on our website https://exoplanet-imaging-challenge.github.io/. The first phase, launched on the 1st of September 2019 and closed on the 1st of October 2020, consisted in detecting point sources in two types of common data-set in the field of high-contrast imaging: data taken in pupil-tracking mode at one wavelength (subchallenge 1, also referred to as ADI) and multispectral data taken in pupil-tracking mode (subchallenge 2, also referred to as ADI+mSDI). In this paper, we describe the approach, organisational lessons-learnt and current limitations of the data challenge, as well as preliminary results of the participants’ submissions for this first phase. In the future, we plan to provide permanent access to the standard library of data sets and metrics, in order to guide the validation and support the publications of innovative image processing algorithms dedicated to high-contrast imaging of planetary systems.
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