HPIC: The Habitable Worlds Observatory Preliminary Input Catalog
Noah Tuchow, Chris Stark, and Eric Mamajek

TL;DR
The paper presents the HPIC, a comprehensive catalog of approximately 13,000 nearby bright stars, constructed using TESS and Gaia data, to support the Habitable Worlds Observatory's search for Earth-like planets.
Contribution
It introduces an automated pipeline for compiling stellar data and benchmarks its accuracy against existing lists, enhancing target selection for exoplanet imaging missions.
Findings
Stellar properties in HPIC are consistent with previous curated lists.
The catalog effectively predicts mission yields for various telescope sizes.
HPIC is valuable for exoplanet studies and astrophysics of nearby stars.
Abstract
The Habitable Worlds Observatory Preliminary Input Catalog (HPIC) is a list of ~13,000 nearby bright stars that will be potential targets for the Habitable Worlds Observatory (HWO) in its search for Earth-sized planets around Sun-like stars. We construct this target list using the TESS and Gaia DR3 catalogs, and develop an automated pipeline to compile stellar measurements and derived astrophysical properties for all stars. We benchmark the stellar properties in the HPIC relative to those of the manually curated ExEP HWO Precursor Science Stars list and find that, for the 164 best targets for exo-Earth direct imaging, our stellar properties are consistent. We demonstrate the utility of the HPIC by using it as an input for yield calculations to predict the science output of various mission designs including those with larger telescope diameters and those focused on other planet types…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsAstronomical Observations and Instrumentation · Astronomy and Astrophysical Research · Computational Physics and Python Applications
