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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. 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., Comment: 36 pages, 27 figures. Proceedings of SPIE "Astronomical Telescopes and Instrumentation" 2020

This document summarizes how far the Nancy Grace Roman Space Telescope Coronagraph Instrument (Roman CGI) will go toward demonstrating high-contrast imaging and spectroscopic requirements for potential future exoplanet direct imaging missions, illustrated by the HabEx and LUVOIR concepts. The assessment is made for two levels of assumed CGI performance: (i) current best estimate (CBE) as of August 2020, based on laboratory results and realistic end-to-end simulations with JPL-standard Model Uncertainty Factors (MUFs); (ii) CGI design specifications inherited from Phase B requirements. We find that the predicted performance (CBE) of many CGI subsystems compares favorably with the needs of future missions, despite providing more modest point source detection limits than future missions. This is essentially due to the challenging pupil of the Roman Space Telescope; this pupil pushes the coronagraph masks sensitivities to misalignments to be commensurate with future missions. In particular, CGI will demonstrate active low-order wavefront control and photon counting capabilities at levels of performance either higher than, or comparable to, the needs of future missions., Comment: 10 pages, 3 tables. Revised version v2: added some co-authors

AIMS: We aim to evaluate the near-infrared colors of brown dwarfs as observed with four major infrared imaging space observatories: the Hubble Space Telescope (HST), the James Webb Space Telescope (JWST), the Euclid mission, and the WFIRST telescope. METHODS: We used the SPLAT SPEX/ISPEX spectroscopic library to map out the colors of the M-, L-, and T-type dwarfs. We have identified which color-color combination is optimal for identifying broad type and which single color is optimal to then identify the subtype (e.g., T0-9). We evaluated each observatory separately as well as the narrow-field (HST and JWST) and wide-field (Euclid and WFIRST) combinations. RESULTS: The Euclid filters perform poorly typing brown dwarfs and WFIRST performs only marginally better, despite a wider selection of filters. WFIRST's W146 and F062 combined with Euclid's Y-band discriminates somewhat better between broad brown dwarf categories. However, subtyping with any combination of Euclid and WFIRST observations remains uncertain due to the lack of medium or narrow-band filters. We argue that a medium band added to the WFIRST filter selection would greatly improve its ability to preselect brown dwarfs its imaging surveys. CONCLUSIONS: The HST filters used in high-redshift searches are close to optimal to identify broad stellar type. However, the addition of F127M to the commonly used broad filter sets would allow for unambiguous subtyping. An improvement over HST is one of two broad and medium filter combinations on JWST: pairing F140M with either F150W or F162M discriminates very well between subtypes., Comment: Accepted for publication in A&A

We present the results of a study to optimize the principal component analysis (PCA) algorithm for planet detection, a new algorithm complementing ADI and LOCI for increasing the contrast achievable next to a bright star. The stellar PSF is constructed by removing linear combinations of principal components, allowing the flux from an extrasolar planet to shine through. The number of principal components used determines how well the stellar PSF is globally modelled. Using more principal components may decrease the number of speckles in the final image, but also increases the background noise. We apply PCA to Fomalhaut VLT NaCo images acquired at 4.05 micron with an apodized phase plate. We do not detect any companions, with a model dependent upper mass limit of 13-18 M_Jup from 4-10 AU. PCA achieves greater sensitivity than the LOCI algorithm for the Fomalhaut coronagraphic data by up to 1 magnitude. We make several adaptations to the PCA code and determine which of these prove the most effective at maximizing the signal-to-noise from a planet very close to its parent star. We demonstrate that optimizing the number of principal components used in PCA proves most effective for pulling out a planet signal., Comment: Accepted for publication in ApJ, 7 pages, 9 figures