04/21/2026 | Press release | Distributed by Public on 04/22/2026 06:41
Photo Credit: NASA/Ames/Seti Institute/JPL-Caltech
By David Levin
April 21, 2026 • Research
James Cho, Professor of Physics (photo: Mike Lovett)
In the search for life beyond Earth, exoplanets - worlds orbiting distant stars - are the most promising place to look. Before scientists can tell if they might harbor living things, though, they first need to answer a few surprisingly tough questions. What's the weather like? Is it too hot, cold, or violently stormy for life as we know it? Brandeis physicist James Cho has spent 25 years working on this problem. Most recently, he's worked on the European Space Agency's ARIEL mission, which will study more than 500 specific exoplanets in detail when it launches in 2029. We talked to him about how his research could help answer one of humanity's biggest riddles.
Think of it as an inverse problem. You take the observations you make with a telescope and ask: what set of conditions would produce those same observations based on what we know of physics? You put your best guess into a simulation, run it, and see if the output matches what you're seeing on an exoplanet. If it does, you've probably got the right parameters. If not, you adjust.
There are plenty! We barely know how to predict weather here on Earth, and we know a tremendous amount about Earth. With exoplanets, we can only take educated guesses. Many of those planets are in orbital configurations completely unlike anything in our solar system: they may be very close to their stars, incredibly hot, and tidally locked so that one side always faces the star and the other is in permanent darkness. They're so far away that they only look like one or two pixels on an image, so you can't resolve any spatial detail.
If you watch that pixel to see how it changes over time, you'll see useful patterns emerge that tell you a lot about a planet's atmosphere. It's an inverse problem - you take observations from a telescope, and then try to recreate them using an existing model of an atmosphere's physics. You put your best guess into that simulation, run it, and see if the output matches what you're seeing on an exoplanet. If it does, you've probably got the right parameters. If not, you adjust and run it again.
The equations I'm using to do this are pretty well known. They're the same ones we use to forecast weather on Earth, to model ocean currents, and even to design aircraft. They apply to any system where many small things behave collectively as a fluid, which turns out to include an extraordinary range of phenomena, from traffic patterns to the interiors of neutron stars.
The main technique is called the transit method. When a planet passes in front of its star, the star's light dims slightly, and that tells you a planet is there. You can also watch for the secondary eclipse, when the planet starts to pass back behind its star. The difference between those two measurements tells you something about the planet's heat signature, which we measure as infrared light across a range of wavelengths. We also look at the frequencies of light coming from the planet, since different molecules in its atmosphere - like carbon dioxide, methane, and ozone - absorb specific wavelengths of light. Based on the pattern of dips and peaks in light you see on a telescope, you can infer what's in a planet's atmosphere. As all those signals change over time, it tells you something about the planet's weather.
Most of what we know about exoplanet atmospheres comes from telescopes like Hubble and the James Webb Space Telescope, and many of the planets they've found have only been observed once or twice. Ariel is designed to go deep on a focused set of 100 to 150 planets and take repeated measurements. That's critical, because you can only really understand what an atmosphere is doing if you watch it change over time.