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.
KEYWORDS: Calibration, Coronagraphy, Simulations, Observational astronomy, Data processing, Exoplanets, Equipment, Analog electronics, Space telescopes, Signal processing
The Nancy Grace Roman Space Telescope’s Coronagraph Instrument will for the first time demonstrate active wavefront sensing and control for a space-based coronagraph, and may image the first planet in reflected light. The Community Participation Program has been initiated to engage members of the broader scientific community in the preparation for its planned launch in late 2026/early 2027. Here we will present the on-going work of the Data Reduction and Simulations working group, one of the four working groups within the Community Participation Program. The working group is charged with the development of the data reduction and postprocessing pipeline for the on-sky data and the development of a simulation suite to aid in the preparation and planning of Roman Coronagraph observations.
In preparation for the operational phase of the Nancy Grace Roman Space Telescope, NASA has created the Coronagraph Community Participation Program (CPP) to prepare for and execute Coronagraph Instrument technology demonstration observations. The CPP is composed of 7 small, US-based teams, selected competitively via the Nancy Grace Roman Space Telescope Research and Support Participation Opportunity, members of the Roman Project Team, and international partner teams from ESA, JAXA, CNES, and the Max Planck Institute for Astronomy. The primary goals of the CPP are to prepare simulation tools, target databases, and data reduction software for the execution of the Coronagraph Instrument observation phase. Here, we present the current status of the CPP and its working groups, along with plans for future CPP activities up through Roman’s launch. We also discuss plans to potentially enable future commissioning of currently-unsupported modes.
The Coronagraphic Instrument onboard the Nancy Grace Roman Space Telescope is an important stepping stone towards the characterization of habitable, rocky exoplanets. In a technology demonstration phase conducted during the first 18 months of the mission (expected to launch in late 2026), novel starlight suppression technology may enable direct imaging of a Jupiter analog in reflected light. Here we summarize the current activities of the Observation Planning working group formed as part of the Community Participation Program. This working group is responsible for target selection and observation planning of both science and calibration targets in the technology demonstration phase of the Roman Coronagraph. We will discuss the ongoing efforts to expand target and reference catalogs, and to model astrophysical targets (exoplanets and circumstellar disks) within the Coronagraph’s expected sensitivity. We will also present preparatory observations of high priority targets.
KEYWORDS: Planets, Stars, Exoplanets, Signal to noise ratio, Signal detection, Coronagraphy, Point spread functions, Detection and tracking algorithms, Atmospheric modeling, Surface conduction electron emitter displays
Today, there exists a wide variety of algorithms dedicated to high-contrast imaging, especially for the detection and characterisation of exoplanet signals. These algorithms are tailored to address the very high contrast between the exoplanet signal(s), which can be more than two orders of magnitude fainter than the bright starlight residuals in coronagraphic images. The starlight residuals are inhomogeneously distributed and follow various timescales that depend on the observing conditions and on the target star brightness. Disentangling the exoplanet signals within the starlight residuals is therefore challenging, and new post-processing algorithms are striving to achieve more accurate astrophysical results. The Exoplanet Imaging Data Challenge is a community-wide effort to develop, compare and evaluate algorithms using a set of benchmark high-contrast imaging datasets. After a first phase ran in 2020 and focused on the detection capabilities of existing algorithms, the focus of this ongoing second phase is to compare the characterisation capabilities of state-of-the-art techniques. The characterisation of planetary companions is two-fold: the astrometry (estimated position with respect to the host star) and spectrophotometry (estimated contrast with respect to the host star, as a function of wavelength). The goal of this second phase is to offer a platform for the community to benchmark techniques in a fair, homogeneous and robust way, and to foster collaborations.
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