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arXiv · 2512.07620

Determining the Detectability of H2O with Photometric Observations using Bayesian Analysis for Remote Biosignature Identification on exoEarths (BARBIE)

Natasha Latouf·Chris Stark·Avi Mandell·Vincent Kofman
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Abstract

We examine the detectability of water (H2O) in the reflected-light spectrum of an Earth-like exoplanet assuming a photometric observational approach rather than spectroscopic. By quantifying the detectability as a function of normalized exposure time, resolving power (R), and amount of spectral points, we can constrain whether spectroscopy or photometry is the more efficient observing procedure to detect H2O at varying abundances by measuring the broad 0.94 microns absorption feature using the Habitable Worlds Observatory (HWO). We simulate low-resolution spectroscopy (R = 10, 20, 30, presented as photometric bandwidth fraction 10%, 5%, 3% herein) as a proxy for narrow-band photometric observations, and constrain the wavelength range from 0.85 - 1.05 microns, to narrow focus on the 0.9 microns feature. We then constrain the number of spectral points to 2 or 3 points at each bandwidth fraction to investigate the impact of spectral point placement on detectability. Additionally, we take the signal-to-noise ratios (SNRs) for strong H2O detection and calculate the resultant exoplanet yields assuming photometric observation and compare to the yields from higher-resolution spectroscopic observations under different noise instances, characterization wavelength, noise floors, and aperture sizes. We find that H2O is strongly detectable at all bandwidth fractions depending on the spectral point placement, requiring a minimum of 3 spectral points, at a variety of normalized exposure time depending on the abundance of H2O. We also find that the detector noise is the main driver in determining whether photometry or spectroscopy results in higher yields. Photometry is the preferred observational method in high-noise cases, while spectroscopy is preferred in low-noise scenarios.

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Natasha Latouf, Chris Stark, Avi Mandell, Vincent Kofman. 2025-12-08. Determining the Detectability of H2O with Photometric Observations using Bayesian Analysis for Remote Biosignature Identification on exoEarths (BARBIE). https://arxiv.org/abs/2512.07620

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