Wavelength Requirements for Life Detection via Reflected Light Spectroscopy of Rocky Exoplanets

The paper investigates the wavelength requirements for the Habitable Worlds Observatory (HWO) to detect life on rocky exoplanets via reflected light spectroscopy. The authors argue that merely detecting biosignature gases like oxygen (O2) and methane (CH4) is insufficient; the telescope must also characterize the broader physicochemical context to rule out false positives and false negatives. Through simulated retrievals using the rfast radiative transfer model and emcee MCMC sampling, they systematically explore the necessary short and long wavelength cutoffs.

The study considers Earth-through-time scenarios (Phanerozoic, Proterozoic with high and low CH4, Archean with high and low CH4) and five false positive scenarios (low non-condensable inventory, waterworld, photochemical, reduced mantle degassing, and hydrothermal methane). They find that broad wavelength coverage from 0.26 µm to 1.7 µm is necessary. Specifically, the short wavelength cutoff of 0.26 µm is driven by the need to detect O3 via the Hartley band (0.2-0.32 µm) for weakly oxygenated Proterozoic-like atmospheres, where O2 and CH4 may be undetectable. The long wavelength cutoff of 1.7 µm is driven by the need to constrain carbon-bearing species (CO2, CO, CH4) to rule out false positives, particularly CO-rich atmospheres that could mimic methane biosignatures. They also require signal-to-noise ratios (SNR) of 20-40 across this range (assuming R=7 UV, R=140 VIS, R=70 NIR).

Key results include: biogenic CH4 is detectable regardless of long wavelength cutoff due to features at 0.8-1.0 µm, but CO2 constraints require at least 1.5 µm, and CO upper limits require at least 1.6 µm. For false positives, wavelength coverage to at least 1.6 µm with SNR 40 is needed to constrain CO in photochemical false positives, and SNR 20-40 is needed for low non-condensable false positives to constrain total pressure. The authors recommend a 1.7 µm cutoff as a safer choice than 1.6 µm because it provides a buffer for lower SNR (10) observations. They conclude that these requirements imply a large aperture (>8 m) is likely necessary to achieve high SNR out to 1.7 µm for the majority of HWO targets.

Based on this paper, I can improve AI systems in the following specific ways:

• What it can do: Automatically classify retrieved atmospheric posteriors as detections, upper limits, or non-constraints using the paper's analytic function fitting approach (Gaussian, flat, upward-sloping, and combined functions)

• Specific capability: Given a 1D marginalized posterior distribution for a gas mixing ratio, the AI can determine whether the gas is detected, constrained as an upper limit, or unconstrained, and extract quantitative uncertainties (16%, 50%, 84% percentiles)

• What it can do: Simulate the impact of different wavelength cutoffs (shortwave: 0.2-0.415 μm; longwave: 1.0-2.0 μm) and signal-to-noise ratios (10, 20, 40) on biosignature detection and false positive discrimination

• Specific capability: Given a proposed telescope design (wavelength range, resolution, SNR), predict which Earth-through-time scenarios (Phanerozoic, Proterozoic high/low CH4, Archean high/low CH4) and false positive scenarios (photochemical, waterworld, low non-condensable, reduced mantle degassing, hydrothermal methane) can be correctly identified

• What it can do: Automatically evaluate whether a detected biosignature (O2, O3, CH4) can be confidently attributed to life or whether a known false positive scenario remains plausible

• Specific capability: Given retrieved abundances of CO2, CO, CH4, O2, O3, H2O, and total pressure, the AI can:

• Rule out photochemical O2 false positives if CO upper limit < 10%

• Rule out reduced mantle CH4 degassing if CO2 is constrained and CO upper limit < 10%

• Identify low non-condensable false positives if total pressure is constrained to < 0.2 bar

• Flag waterworld false positives if land fraction upper limit is < 10%

• What it can do: Automatically configure and run rfast retrievals for different atmospheric compositions representing different epochs of Earth's history

• Specific capability: Given a target epoch (e.g., Proterozoic low CH4), the AI can:

• Set appropriate prior ranges for gas partial pressures (10-12 to 10 7 Pa for trace species)

• Configure MCMC parameters (200 walkers, 200,000 steps, burn-in of 100,000-150,000, thinning of 100)

• Determine which wavelength range and SNR are needed for confident biosignature detection

• What it can do: Determine the minimum wavelength coverage needed to achieve a specified biosignature detection confidence

• Specific capability: Given a target scenario (e.g., Proterozoic Earth with 0.1% PAL O2), the AI can:

• Recommend a shortwave cutoff (0.26 μm for O3 detection via Hartley band)

• Recommend a longwave cutoff (1.7 μm for CO/CO2 constraints to rule out false positives)

• Identify the minimum SNR needed (20-40) for each wavelength region

• What it can do: Assign a quantitative confidence score to a biosignature detection based on the completeness of contextual information

• Specific capability: Given retrieved atmospheric parameters, the AI can:

• Score confidence as high if O3 is detected in UV, CH4 is detected, CO2 is constrained, and CO upper limit < 10%

• Score confidence as moderate if O2 is detected but CO2/CO are unconstrained

• Score confidence as low if only O2 is detected without contextual gases, as this could be a false positive

• What it can do: Adjust biosignature detection strategies based on stellar spectral energy distribution

• Specific capability: Given a target star type (F, G, K, or M), the AI can:

• Adjust expected photochemical false positive likelihood (lower for F/G/K, higher for M)

• Modify wavelength requirements (e.g., M-dwarf targets may need different UV coverage)

• Account for pre-main sequence H escape false positives (more relevant for M-dwarfs)

• What it can do: Generate graduated observation strategies for HWO targets

• Specific capability: Given a target list, the AI can:

• Prioritize targets for low-SNR, restricted-wavelength reconnaissance

• Recommend which targets warrant high-SNR (20-40) follow-up across 0.26-1.7 μm

• Estimate integration times needed to achieve required SNR at each wavelength

Searching for signs of life is a primary goal of the Habitable Worlds Observatory (HWO). However, merely detecting oxygen, methane, or other widely discussed biosignatures is insufficient evidence for a biosphere. In parallel with biosignature detection, exoplanet life detection additionally requires characterization of the broader physicochemical context to evaluate planetary habitability and the plausibility that life could produce a particular biosignature in a given environment. Life detection further requires that we can confidently rule out photochemical or geological phenomena that can mimic life (i.e. "false positives"). Evaluating false positive scenarios may require different observatory specifications than biosignature detection surveys. Here, we explore the coronagraph requirements for assessing habitability and ruling out known false positive (and false negative) scenarios for oxygen and methane, the two most widely discussed biosignatures for Earth-like exoplanets. We find that broad wavelength coverage ranging from the near UV (0.26 mu m) and extending into the near infrared (1.7 mu m), is necessary for contextualizing biosignatures with HWO. The short wavelength cutoff is driven by the need to identify Proterozoic-like biospheres via O 3, whereas the long wavelength cutoff is driven by the need to contextualize O 2 and CH 4 biosignatures via constraints on C-bearing atmospheric species. The ability to obtain spectra with signal-to-noise ratios of 20-40 across this 0.26-1.7 mu m range (assuming R=7 UV, R=140 VIS, and R=70 NIR) is also required. Without sufficiently broad wavelength coverage, we risk being unprepared to interpret biosignature detections and may ultimately be ill-equipped to confirm the detection of an Earth-like biosphere, which is a driving motivation of HWO..