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Published February 2022 | Accepted Version + Published
Journal Article Open

Sensitivity of the Roman Coronagraph Instrument to Exozodiacal Dust

Abstract

Exozodiacal dust, warm debris from comets and asteroids in and near the habitable zone of stellar systems, reveals the physical processes that shape planetary systems. Scattered light from this dust is also a source of background flux which must be overcome by future missions to image Earthlike planets. This study quantifies the sensitivity of the Nancy Grace Roman Space Telescope Coronagraph to light scattered by exozodi, the zodiacal dust around other stars. Using a sample of 149 nearby stars, previously selected for optimum detection of habitable exoplanets by space observatories, we find the maximum number of exozodiacal disks with observable inner habitable zone boundaries is six and the number of observable outer habitable boundaries is 74. One zodi was defined as the visible-light surface brightness of 22 m_V arcsec⁻² around a solar-mass star, approximating the scattered light brightness in visible light at the Earth-equivalent insolation. In the speckle limited case, where the signal-to-noise ratio is limited by speckle temporal stability rather than shot noise, the median 5σ sensitivity to habitable zone exozodi is 12 zodi per resolution element. This estimate is calculated at the inner-working angle of the coronagraph, for the current best estimate performance, neglecting margins on the uncertainty in instrument performance and including a post-processing speckle suppression factor. For an log-norm distribution of exozodi levels with a median exozodi of 3× the solar zodi, we find that the Roman Coronagraph would be able to make 5σ detections of exozodiacal disks in scattered light from 13 systems with a 95% confidence interval spanning 7–20 systems. This sensitivity allows Roman Coronagraph to complement ground-based measurements of exozodiacal thermal emission and constrain dust albedos. Optimized post-processing and detection of extended sources in multiple resolution elements is expected to further improve this unprecedented sensitivity to light scattered by exozodiacal dust.

Additional Information

© 2022. The Author(s). Published by IOP Publishing Ltd on behalf of the Astronomical Society of the Pacific (ASP). Original content from this work may be used under the terms of the Creative Commons Attribution 3.0 licence. Any further distribution of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI. Received 2021 September 16; accepted 2021 December 2; published 2022 February 21. Code to reproduce the figures presented in this study is available on github.com 13 and archived on Zenodo (Douglas & Ashcraft 2021). The authors acknowledge valuable inputs from the JPL and IPAC Roman Coronagraph teams. Thanks to Vanessa Bailey and Steve Ertel for helpful feedback. Portions of this work were supported by the WFIRST Science Investigation team prime award #NNG16PJ24C. Portions of this work were supported by the Arizona Board of Regents Technology Research Initiative Fund (TRIF). J.A.: this work was supported by a NASA Space Technology Graduate Research Opportunity. This research has made use of the SIMBAD database and the VizieR catalog access tool, both operated at CDS, Strasbourg, France. This research has made use of the NASA Exoplanet Archive, which is operated by the California Institute of Technology, under contract with the National Aeronautics and Space Administration under the Exoplanet Exploration Program. Facilities: SIMBAD - , VizieR - , Exoplanet Archive. - Software: This research made use of community-developed core Python packages, including: Astroquery (Ginsburg et al. 2018), Astropy (The Astropy Collaboration et al. 2013), Matplotlib (Hunter 2007), SciPy (Jones et al. 2001), Jupyter and the IPython Interactive Computing architecture (Pérez & Granger 2007; Kluyver et al. 2016). Specific to exoplanet imaging, this research made use of the EXOSIMS exoplanet mission simulation package (Savransky et al. 2017); for photon-counting, EMCCD Detect, 14 based on Nemati (2020); and for post-processing, the dimensionality reduction code for images using vectorized Nonnegative Matrix Factorization (NMF) in Python (Zhu 2016; Ren et al. 2018; Ren 2020).

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Published - Douglas_2022_PASP_134_024402.pdf

Accepted Version - 2112.12804.pdf

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Additional details

Created:
August 22, 2023
Modified:
October 23, 2023