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Astronomers Warn of Risk of Misinterpreting JWST Planetary Signals

Refining current models is essential for unearthing accurate details of exoplanet properties — and signs of life — in data from new telescope, team says.

n this conceptual image, the James Webb telescope captures light from around a newly-discovered planet (on left). However, when scientists analyze this data, limitations in opacity models could produce planetary predictions that are off by an order of magnitude (represented by 3 possible planets on the right).
Credit: Jose-Luis Olivares, MIT. James Webb icon courtesy of NASA.

Cambridge, MA– Astronomers are harnessing NASA's newest space telescope, JWST, to decode the atmospheres of nearby worlds. The properties of these planetary atmospheres could give clues to how a planet formed and whether it harbors signs of life.

But a new study in Nature Astronomy, led by the Center for Astrophysics | Harvard & Smithsonian and MIT, suggests that the tools astronomers typically use to decode planetary signals may not be good enough to accurately interpret the new telescope's data. Specifically, opacity models — the tools that model how light interacts with matter as a function of the matter’s properties — may need significant refining in order to match the precision of Webb’s data, the researchers say.

"Taking proper account of opacity model limitations and making efforts to eliminate them is essential in the era of JWST," says Iouli Gordon, an astrophysicist and study co-author based at the Center for Astrophysics.

If these models are not refined? The researchers predict that properties of planetary atmospheres, such as their temperature, pressure, and elemental composition, could be off by an order of magnitude.

"There is a scientifically significant difference between a compound like water being present at 5 percent versus 25 percent, which current models cannot differentiate,” says corresponding author Julien de Wit, an assistant professor in MIT’s Department of Earth, Atmospheric, and Planetary Sciences (EAPS).

Leveling up

Opacity is a measure of how easily photons pass through a material. Photons of certain wavelengths can pass straight through a material, be absorbed, or be reflected back out depending on whether and how they interact with certain molecules within a material. This interaction also depends on a material’s temperature and pressure.

An opacity model works on the basis of various assumptions about how light interacts with matter. Astronomers use opacity models to derive certain properties of a material, given the spectrum of light that the material emits. In the context of planets, an opacity model can decode the type and abundance of chemicals in a planet’s atmosphere, based on the light from the planet that a telescope captures.

The team says that the current state-of-the-art opacity model, which they liken to the classical language translation tool, the Rosetta Stone, has done a decent job of decoding spectral data captured by instruments such as those on the Hubble Space Telescope.

"So far, this 'Rosetta Stone' has been doing OK," de Wit says. "But now that we're going to the next level with Webb's precision, our translation process will prevent us from catching important subtleties, such as those making the difference between a planet being habitable or not."

Light, perturbed

The team makes this point in their study, in which they put the most commonly used opacity model to the test. The scientists looked to see what atmospheric properties the model would derive if it were tweaked to assume certain limitations in our understanding of how light and matter interact. The researchers created eight such "perturbed" models. They then fed each model, including the real version, "synthetic spectra" — patterns of light that were simulated by the group and similar to the precision that the JWST would see.

They found that, based on the same light spectra, each perturbed model produced wide-ranging predictions for the properties of a planet's atmosphere. Based on their analysis, the team concludes that, if existing opacity models are applied to light spectra taken by the Webb telescope, they will hit an “accuracy wall.” That is, they won't be sensitive enough to tell whether a planet has an atmospheric temperature of 300 Kelvin or 600 Kelvin, or whether a certain gas takes up 5 percent or 25 percent of an atmospheric layer.

The team also found that every model also produced a "good fit" with the data, meaning, even though a perturbed model produced a chemical composition that the researchers knew to be incorrect, it also generated a light spectrum from that chemical composition that was close enough to, or "fit" with the original spectrum.

"We found that there are enough parameters to tweak, even with a wrong model, to still get a good fit, meaning you wouldn’t know that your model is wrong and what it’s telling you is wrong," de Wit explains.

He and his colleagues raise some ideas for how to improve existing opacity models, including the need for more laboratory measurements and theoretical calculations to refine the models’ assumptions of how light and various molecules interact, as well as collaborations across disciplines, and in particular, between astronomy and spectroscopy.

"In order to reliably interpret spectra from the diverse exoplanetary atmospheres, we need an extensive campaign for new accurate measurements and calculations of relevant molecular spectroscopic parameters," Gordon says. "These parameters will need to be implemented promptly into reference spectroscopic databases and consequently models used by astronomers."

Robert Hargreaves, a study co-author and scientist at the Center for Astrophysics, adds, "As we enter a new era of exoplanet research, JWST and future missions will provide unprecedented high-quality observations of exoplanet atmospheres. It is therefore necessary that we have appropriate spectroscopic data and models to accurately infer fundamental characteristics of these new worlds."

Additional co-authors are Prajwal Niraula (first author) of MIT; Clara Sousa Silva of Bard College; and Roman Kochanov who was a postdoctoral associate at the Center for Astrophysics from 2014-2018 and in 2020 during the time of the study.


A version of this article was originally published on the MIT New Office website.

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