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illustration of a tidal disruption event

Editor’s Note: Astrobites is a graduate-student-run organization that digests astrophysical literature for undergraduate students. As part of the partnership between the AAS and astrobites, we occasionally repost astrobites content here at AAS Nova. We hope you enjoy this post from astrobites; the original can be viewed at astrobites.org.

Title: Thermal Electrons in the Radio Afterglow of Relativistic Tidal Disruption Event ZTF22aaajecp/AT 2022cmc
Authors: Lauren Rhodes et al.
First Author’s Institution: McGill University
Status: Published in ApJ

Tidal disruption events (TDEs, see Figure 1), which occur when a star gets a little too close to a supermassive black hole (SMBH) and gets ripped apart, are a hot topic across the electromagnetic spectrum. During a TDE, the star can no longer hold itself together under the gravitational pull of the SMBH. Some bits of the star end up accreting onto the black hole, which can launch a temporary outflow, or, in especially dramatic cases, a relativistic jet.

cartoon of a star orbiting a black hole, getting to close, and being ripped apart

Figure 1: Timeline of events leading to a tidal disruption event. [Chloe Klare]

Aside from being cool transients (as far as spectacular stellar deaths go, they are rivaled only by the supernova), TDEs are valuable to study for a variety of reasons. They likely play a role in galaxy evolution, SMBH growth, and even the life cycles of active galactic nuclei (AGN, in which material is constantly swirling onto the SMBH). Not to mention, they are a great tool for eyeballing the mass of the SMBH responsible for the TDE; if the black hole is any bigger than about 1 billion times the mass of the Sun, its event horizon — the point at which not even light can escape its gravity — extends too far, and a star will disappear across the event horizon before it ever gets ripped apart.

How to Spot a TDE

Usually, TDEs are discovered in the X-ray (after all, not many transients are powerful enough to generate an X-ray flare) or in the optical (thanks to high-cadence, wide-field surveys like the Zwicky Transient Facility and the Legacy Survey of Space and Time). However, radio is a particularly useful regime for TDE searches, especially in dusty host galaxies where we cannot see the optical TDE signatures at all; while dust obscures optical light, the radio is unaffected! There is just one catch: how exactly can we identify a TDE based on only its radio emission?

The radio light in a TDE is generated via synchrotron radiation — which is caused by fast moving electrons in strong magnetic fields — and originates in jets or shocks. Unfortunately, this is also the case in AGN, the primary extragalactic source of variable radio emission, and it can be difficult to distinguish between the two. Additionally, the amount of light we see from synchrotron radiation at a given frequency depends on how energy is distributed among the electrons in the source, which is unknown. Perhaps the simplest case — or at least the one you’ll learn about first in your undergraduate statistical mechanics course — is that the energy is distributed among the electrons thermally (left panel in Figure 2). However, most radio transients associated with black holes are assumed to have non-thermal electron energy distributions, usually where there are exponentially many more low-energy electrons than high-energy electrons (right panel in Figure 2).

cartoon showing thermally distributed and non-thermally distributed electrons

Figure 2: Energy can be distributed among the electrons in a source either thermally (left panel), where most electrons have a medium amount of energy, or non-thermally (right panel), where most electrons have a small amount of energy. Often, extragalactic radio transients are assumed to originate from non-thermal electrons, but today’s article argues why we shouldn’t ignore thermal electrons. [Chloe Klare]

As a further challenge, very few TDEs have had extensive follow-up observations in the radio, so we don’t have strong constraints on how most TDEs should behave, especially in the long term. Luckily, some astronomers are working to change this.

This includes today’s authors, who have focused on one particular TDE, ZTF22aaajecp/AT2022cmc (I’m sure everyone mispronounces her name), or 2022cmc for short. 2022cmc is a special TDE: it is one of only five TDEs suspected to have launched a relativistic jet, and it has the highest redshift (z ~ 1.2) of the five. It was observed first in the optical and then in the X-ray and radio. The X-ray emission was highly variable for 400 days post-TDE, and then disappeared, and the first 100 days of radio emission indicated there was a relativistic outflow. At the time, it was concluded that the jet shut off and the X-ray emission ceased. However, the story doesn’t end there; the authors of today’s article continued to observe 2022cmc in the radio for an additional 900 days at frequencies spanning about 1–100 GHz.

Our authors had two key observing strategies: wide frequency coverage and long duration. Measuring the change in brightness with observing frequency, or the spectral energy distribution (SED), is important for determining which processes are responsible for the radio emission, since thermal electrons and non-thermal electrons will produce different SEDs. On the other hand, measuring the change in brightness over time, or the light curve, is important for determining what is happening at the source, such as whether there is a jet and, if so, how long it lasts. Here, our authors combine light curves at six different frequencies (Figure 3) and SEDs at nine different epochs (Figure 4) to investigate both.

Plot of flux density over time

Figure 3: Light curves spanning six frequencies and 900 days obtained by today’s authors. [Rhodes et al. 2025]

Plot of flux density as a function of frequency

Figure 4: Nine epochs of radio SEDs, which show the peak moving to lower frequencies over time. [Rhodes et al. 2025]

The Findings

Our authors find a couple of interesting results. First, in the time domain, they find the highest-frequency light curves fade with time, while the lower-frequency light curves increase initially, hit peaks at different times (after 300 days at 15.5 GHz, and after 800 days at 1.3 GHz), and then begin to decay. The spectral evolution is even more intriguing; the SED is always peaked, and the peak shifts to lower frequencies over time, which is typical for an expanding emission region. At frequencies below the peak, the SED doesn’t change much. However, the high-frequency side of the SED shows confusing behavior: early on, it has a very steep slope (the amount of light drops off sharply at higher frequencies), but it eventually flattens.

Investigations Begin

Next, our authors consider three possibilities to explain these observations. They first consider synchrotron radiation from only non-thermal electrons in a relativistic jet (Figure 5), which is the canonical model for a gamma-ray burst radio afterglow. Initially, the jet is so fast that all its radio light is relativistically beamed in one direction (like a flashlight), and we can only see the jet if it’s pointed directly at us. Eventually, the jet slows down enough that it is no longer beamed, and light is emitted in all directions (like a light bulb). At this point, we see the light fade over time, which is exactly what happened in the high-frequency light curves. However, there is one glaring problem: this model cannot possibly explain the observed long-lasting steep SED at high frequencies. So, our authors discard this theory.

cartoon showing the jets of a black hole with and without relativistic beaming

Figure 5: The left image shows what a black hole–generated jet looks like in the rest frame of the jet itself. As long as the jet isn’t moving too fast, this is what we see too. However, if the material in the jet is moving near the speed of light, we observe a relativistically beamed jet (right image). [Chloe Klare]

Instead, our authors consider a jetted outflow that has non-thermal and thermal electrons both independently generating synchrotron emission1, giving us the superposition of two radio spectra. This model also doesn’t fit the data well. The peak of the SED moves too slowly, a very dense local environment is required, and, once again, the authors cannot reconcile that steep high-frequency SED.

Lastly, our authors keep the thermal/non-thermal electrons combo and ditch the jet entirely, modeling a spherical outflow. Excitingly, this model best fits the observations, and, most importantly, can explain the mysterious high-frequency behavior. Initially, most of the radio emission originates in the thermal electron population, which produces more light at higher frequencies. As the outflow expands, the non-thermal electrons begin to dominate, and the SED transforms into the classic non-thermal synchrotron shape.

Next Steps

Ideally, our authors want to compare 2022cmc to other TDEs, but few TDEs have such thorough follow-up observations. They speculate that thermal electrons were important in the radio evolution of one of the few such TDEs, Swift J1644, and recommend we revisit its emission models. More broadly, they recommend two future priorities: first, we need extensive radio observations for larger samples of TDEs, especially around 100 GHz, where the thermal electrons contribute most to the SED; secondly, we should stop neglecting thermal electrons not just in TDE models, but in models of any black hole jets, including gamma-ray bursts and X-ray binaries. While this work addresses only one event, one thing is clear. For theorists and observers alike, there is a myriad of exciting work to be done, so it’s no wonder TDEs have garnered so much attention lately.

  1. A convenient property of extragalactic synchrotron sources is that all their electrons radiate independently of one another, even if they are part of the same electron population. This is called incoherent emission. (Galactic sources are another story, but I’ll save that for another time.) ↩︎

Original astrobite edited by Flavia Pascal.

About the author, Chloe Klare:

I’m a PhD student in astronomy and astrophysics at Penn State (with a physics minor, so I get to use my semester spent in QFT for something!). I study active galactic nuclei (in the radio!), and I’m currently looking for baby synchrotron jets in active galactic nuclei.

IC 5332

Editor’s Note: Astrobites is a graduate-student-run organization that digests astrophysical literature for undergraduate students. As part of the partnership between the AAS and astrobites, we occasionally repost astrobites content here at AAS Nova. We hope you enjoy this post from astrobites; the original can be viewed at astrobites.org.

Title: JWST Discovery of Warm Dust in the Circumgalactic Medium of the Makani Galaxy
Authors: Sylvain Veilleux et al.
First Author’s Institution: University of Maryland
Status: Published in ApJ

The Windy Galaxy

Billions of light-years away lies Makani, a record-breaking galaxy discovered in 2019 by researchers at the Keck Observatory atop Maunakea, Hawaiʻi. The galaxy shows evidence of a large merger event, where two galaxies collided to form a larger galaxy. This event triggered starburst activity, or several waves of intense star formation, that changed the makeup of not just Makani, but the region around it.

There are several processes that can create galactic winds. An active supermassive black hole at the center of the galaxy can slingshot particles out of the galaxy at close to the speed of light, or supernovae leftover from previous starburst activity can help to expel material from the galaxy. Makani, whose name in Hawaiian just so happens to mean “wind,” has both factors contributing to its galactic winds: massive amounts of star formation and a very active black hole in its center.

This contributes to some of the strongest galactic winds discovered to date, stretching approximately 100 kiloparsecs (330,000 light-years) beyond the galaxy, roughly ten times the extent of a typical galactic wind. These galactic winds remove gas from the galaxy and help to enrich the circumgalactic medium around the galaxy. There is still much to discover about how galactic winds change the makeup of such galaxies, and what exactly they take with them on their way out.

Earth’s Favorite Carcinogen: Polycyclic Aromatic Hydrocarbons

Polycyclic aromatic hydrocarbons (PAHs, pronounced P-A-Hs or “paws”) are small flat dust grains scattered into every corner of the universe, from the atmosphere of Earth in the form of exhaust and wildfire smoke to the circumgalactic medium (the mostly empty space between galaxies). These PAHs contribute to regulating the temperature of the interstellar medium, but astronomers have long wondered how they migrate across galaxies.

Even though they are smaller than a human hair, PAHs are still easily observable even in very distant galaxies.  These dust grains emit infrared light, and if there are enough PAHs in a region, they are bright enough to be observed with modern telescopes, such as JWST. By combining multiple observations across multiple filters, astronomers can calculate ratios that reveal information about the PAHs’ size, temperature, and charge, allowing reserachers to further discern properties about the regions in which these PAHs reside.

With redshifted galaxies like Makani, the light from PAHs is stretched beyond its usual wavelength, but fortunately for today’s authors, the light was stretched just enough to land known PAH features well within JWST filters, as seen in Figure 1. The authors were then able to use this information to track the distribution of these PAHs across Makani.

JWST spectrum of the galaxy Makani

Figure 1: Makani’s spectrum overlaid on top of the JWST filters. The peaks in the spectrum are PAH features that neatly overlap with JWST’s observing bands. [Veilleux et al. 2025]

PAHs Gone Extragalactic

Using JWST, the authors scrutinized Makani for any signs of PAHs. They found that not only did PAHs exist within the galaxy, these molecules were found up to 30 kpc (~100,000 light-years) outside the galaxy. Makani’s strong galactic winds were ejecting the dust grains from the galaxy over an estimated timescale of a billion years.

Previously, astronomers had not expected to find high quantities of dust grains outside the protection of a galaxy. The journey across a galaxy is long and hot, with temperatures in the millions of degrees. A dust grain would likely not survive the trip, as it would be destroyed by high-energy photons. This suggests that the PAHs were somehow shielded from the hotter parts of the interstellar medium and circumgalactic medium in large enough volumes to make it beyond the edge of Makani.

This answered questions about how galaxies enrich the circumgalactic medium, but it also added several more. Since today’s authors were limited by the sensitivity and range of their instruments, they were unable to confirm if there were PAHs along Makani’s entire wind structure, or just the first 35 kpc (114,000 light-years) of it. They also would like to turn their sights towards the intergalactic medium to see if PAHs could make it even farther beyond the reach of their host galaxy.

Original astrobite edited by Chloe Klare.

About the author, Natalie Price:

As a first-year master’s student at Wesleyan University, I study how stellar winds interact with the local interstellar medium. Outside of the observatory, you can find me dancing, with my nose in a book, or running at non-relativistic speeds.

Messier 83

Editor’s Note: Astrobites is a graduate-student-run organization that digests astrophysical literature for undergraduate students. As part of the partnership between the AAS and astrobites, we occasionally repost astrobites content here at AAS Nova. We hope you enjoy this post from astrobites; the original can be viewed at astrobites.org.

Title: Unbreaking the Universe: MINERVA Measurements of Color Gradients in Massive Quiescent Galaxies Can Help Ease Too-Early Star Formation Tensions
Authors: Sam E. Cutler et al.
First Author’s Institution: Tufts University
Status: Published in ApJL

Universe Breakers

JWST launched in 2021, and one of its key goals was to observe the first galaxies as they formed. Early results from JWST found something surprising: extremely massive galaxies in the early universe that had “quenched,” or stopped making new stars, much faster than was expected. These early results led some to believe that our understanding of how quickly massive galaxies can form and quench was fundamentally wrong.

Before concluding that our understanding of the universe is broken, it’s important to find other reasons why we might see very massive galaxies in the early universe. One theory is that these galaxies are actually less massive than we think. To “weigh” a galaxy, astronomers first measure the amount of light being emitted by that galaxy. If all the light in a galaxy comes from stars (which should be true in the early universe, though active black holes can contribute a lot of light in some galaxies), you can infer the total number of stars by accounting for the average amount of light emitted per star of a certain mass; this is called the “mass-to-light ratio.” Since massive stars emit a lot more light than low-mass stars, and high-mass stars die out faster than low-mass stars, the mass-to-light ratio is higher for older stellar populations. To accurately “weigh” a galaxy, scientists therefore need both a good measurement of the total amount of light in the galaxy and how old its stellar population is. The authors of today’s article suggest that the uncertainty in these measurements might be leading to overestimates of galaxy masses and underestimates of galaxy star formation rates, possibly explaining the existence of the earliest massive quiescent (non-star-forming) galaxies.

The Impact of Color Gradients

Previous works about the massive quiescent galaxies in this study used spectroscopy to determine the galaxies’ masses and star formation rates. These spectra were taken with a “slit,” which introduces a source of error: if the slit is smaller than the image of the galaxy, some of the galaxy’s light will be missed in the spectrum. Astronomers usually correct for this by checking how much of the total light of a galaxy image is covered by the slit and scaling up the spectrum to account for the missing light, but this correction assumes that the spectrum is basically the same across the entire galaxy.

However, this assumption is rarely correct. In the local universe, star-forming spiral galaxies like the Milky Way tend to be made of a central “bulge” surrounded by a “disk” (see Figure 1). The bulge is no longer actively forming new stars, leading to a red-to-blue color gradient as you move out from the center of the galaxy. In astronomy, this is considered a “negative” color gradient. A slit that only covers the galaxy center would lead to an overall overestimate of the stellar mass and underestimate of the star formation rate. If the galaxies instead had a positive color gradient, with more star formation in the center of the galaxy, the mass would be underestimated and the star formation rate would be overestimated. Galaxies with both positive and negative color gradients have been found in the distant universe. By measuring the color gradient for each individual galaxy in their sample, the authors can correct the mass and star formation rate calculations from spectra taken with a slit spectrograph.

NGC 2683 with annotations

Figure 1: The spiral galaxy NGC 2683 with its bulge and disk labeled. The inner part of the galaxy (“bulge”) contains older, redder stars; the outer part of the galaxy (“disk”) contains bright blue stars that indicate that star formation is ongoing. Here, the slit spectrograph only covers the galaxy’s bulge, leading to incorrect mass and star formation rate measurements. [ESA/Hubble & NASA (CC BY 4.0) with annotations by Margaret Verrico]

Results

Instead of using spectra, the authors of today’s article use imaging in different filters to measure color gradients for a sample of four galaxies in the early universe that had previously been found to be extremely massive and no longer forming stars. They use medium-band filters, or filters that let in only a small part of a galaxy’s spectrum, to produce a spectral energy distribution at each radius. This spectral energy distribution is less informative than a spectrum (think a handprint versus a fingerprint), but it’s detailed enough to model the likely stellar population at each radius to determine whether the galaxies have positive, negative, or no color gradients, allowing for better corrections to the properties measured from the galaxies’ centers. They also model the stellar population from the central part of the galaxy that would normally be covered by a slit, as well as from the actual spectrum, to test whether any differences in their results come from their choice of modeling techniques.

The authors find that three of the four galaxies have a negative color gradient in at least some areas. The fourth galaxy has a relatively flat color gradient, though this measurement is less certain due to the object’s redshift. When the authors plot the galaxies’ colors on a diagnostic diagram that separates red and old galaxies from young and blue galaxies, they find that three of the four galaxies have centers that appear red and old but outskirts that appear young and blue (Figure 2). This means previous measurements of the mass may have been overestimated, and previous measurements of the star formation rate may have been underestimated.

color-color diagram for the galaxies studied

Figure 2: The location of each of the four galaxies on a color–color diagram that separates red galaxies (above/to the left of the dashed lines) from blue galaxies (below/to the right of the dashed lines). The open markers indicate the galaxy color as measured from the center of the galaxy; the filled-in markers show the color at different radii from the galaxy center. For all but one galaxy, the color at several radii is bluer than at the center, indicating that the galaxy might have younger stars at least at some radii. [Adapted from Cutler et al. 2026]

Next, the authors model the stellar ages across the galaxies using spectral energy distribution modeling. This technique compares the measured spectral energy distribution to libraries of stellar spectra, rules about how different dust or chemical composition impact galaxy appearance, and observational effects to predict the actual stellar makeup of a galaxy. In this case, the authors can’t know for sure whether the redder colors at galaxy centers come from an older stellar population, more dust, or changes in the chemical composition (the so-called “dust–age–metallicity degeneracy”). To account for this, the authors try modeling the stellar population two ways: once by assuming all change in color comes from a change in stellar age, and again by allowing the dust and chemical composition of the galaxy to change with radius. They find that if only the stellar age varies across the galaxy, age gradients in the galaxy stellar population can bring the estimated galaxy masses and star formation rates back toward agreement with models of galaxy evolution in the early universe, though not all the way. However, allowing dust and chemical composition to change across the face of the galaxy lead to higher stellar masses and less star formation, meaning the mystery may not yet be solved.

Is the Universe Broken?

To determine whether these galaxies still count as “universe breakers,” the authors use a cosmological model to predict the largest expected galaxy mass in the observed area at different periods in cosmic time. The previous results had less than a 0.3% chance of occurring under current cosmological models; with their updated numbers and stellar population models, the authors find that the observed galaxies sometimes have more than a 5% chance of occurring, though there is still tension. They point out that their analysis ignores processes that could help galaxies grow and quench in the early universe, like galaxy mergers; still, the existence of these massive galaxies with such low star formation rates remains a puzzle.

Original astrobite edited by Ansh Gupta.

About the author, Margaret Verrico:

I am a fourth-year graduate student at the University of Illinois Urbana-Champaign. I study the connection between supermassive black hole transients and their host galaxies. I am also an avid knitter and reader, and I am passionate about opening up STEM opportunities for people of all backgrounds.

NGC 1068

Editor’s Note: Astrobites is a graduate-student-run organization that digests astrophysical literature for undergraduate students. As part of the partnership between the AAS and astrobites, we occasionally repost astrobites content here at AAS Nova. We hope you enjoy this post from astrobites; the original can be viewed at astrobites.org.

Title: Geometry, Not Calorimetry, Drives the Radio–Infrared–γ Ray Correlation
Authors: T. A. Porter, I. V. Moskalenko, and G. Jóhannesson
First Author’s Institution: Stanford University
Status: Published in ApJ

Galaxies emit light not only in the visible band, but also across other wavelengths via different physical mechanisms. Finding correlations between emissions at different wavelengths is a powerful tool for astrophysicists to explore the underlying mechanisms of galaxy formation. One of the most famous examples is the infrared–radio continuum correlation, which holds across several orders of magnitude in luminosity.

The typical explanation for this correlation is that both infrared light and radio synchrotron emission share the same energetic origin: star formation. Young stars emit ultraviolet radiation, which is absorbed by interstellar dust and re-radiated in the infrared. When these stars end their lives in core-collapse supernovae, the resulting shock waves accelerate cosmic-ray electrons, which then interact with the magnetic field to produce synchrotron emission.

For this correlation to hold, cosmic-ray electrons must radiate away all their energy within the galaxy, unable to escape and carry away some of their energy. Otherwise, the amount of radio emission would depend on how quickly cosmic rays escape and would no longer correlate with the infrared emission. This assumption is called the “electron calorimeter” model, which assumes that electrons lose all their energy due to radiation without escaping the galaxy. However, observations show that the infrared–radio correlation persists even in low-density galaxies where cosmic rays can easily escape, suggesting that the calorimeter model may not be the full story. To reconcile this, previous studies proposed “conspiracy-like” scenarios in which cosmic-ray injection, transport, magnetic-field amplification, and gas density are all coupled in a finely self-regulating way to maintain the correlation across diverse galactic environments — a somewhat awkward explanation that requires multiple unrelated physical processes to conveniently work together.

With the increased sensitivity of the Fermi Large Area Telescope, high-energy gamma-ray (or γ-ray) detections add new information to this picture. A galaxy’s γ-ray emission is produced by two different sources: cosmic-ray protons interacting with the interstellar medium gas, and cosmic-ray electrons inverse-Compton scattering off of nearby starlight or photons from the cosmic microwave background. Since both processes involve cosmic rays, the total γ-ray emission should also reflect the amount of star formation and therefore correlate with infrared and radio emission.

Because all three wavelengths trace different pieces of the same cosmic-ray population, studying them together reveals how the galaxy’s total cosmic-ray energy budget is distributed across its multi-wavelength emission.

The infrared–radio correlation has been established not only at the scale of entire galaxies, but also locally, down to patches roughly 100 parsecs across. Think of it like the relationship between a city’s electricity consumption and its population: we have long known they track each other city-wide, but it turns out the same relationship holds block by block. The infrared–radio correlation works the same way: zoom into any 100-pc region within a galaxy, and the correlation is still there. Unfortunately, the resolution of γ-ray observations is still stuck at around the kiloparsec scale. It is therefore unclear whether the local infrared–radio correlation reflects a genuine local physical coupling, one that would extend to γ-rays if we had sufficient resolution, or whether it is simply a spatial average of the emission, smoothed out by insufficient resolution. The answer determines whether radio and γ-ray emission can be used as reliable tracers of star formation, or whether they are just smeared out by cosmic-ray propagation over kiloparsec scales.

In this study, the authors numerically model galactic cosmic-ray transport, building a suite of physically motivated three-dimensional models of the Milky Way. They consider two variants for each of the four key inputs: 1) the cosmic-ray source distribution, 2) the interstellar gas, 3) the amount of starlight within the galaxy (the interstellar radiation field), and 4) the galactic magnetic field. Crucially, every model is normalized to reproduce the locally observed cosmic-ray data to within 5%, so that any differences in the predicted emission come purely from the large-scale geometry of each input, rather than from variations in the total cosmic-ray budget.

After evolving cosmic-ray transport for these realistic models, the authors then compute synthetic observations at radio, infrared, and γ-ray bands from various viewing inclinations to investigate how the underlying galactic model and the viewing angle affect the correlations between these emissions.

Surprisingly, inclination plays the most important role — more so than the cosmic-ray source distribution, the radiation field, or the magnetic field. Figure 1 shows the correlation plots between the radio and γ-ray emission (left two columns) and between infrared and γ-ray emission (right two columns) when viewing the galaxy face-on (i.e., viewing the galaxy from directly above the disk). Different colors represent γ-ray emission components from different physical mechanisms, with orange showing the total γ-ray emission. For both sets of correlation plots, starting from the upper-left panel, each panel modifies one physical input and recomputes the emission. Although there is some variation, one can see that the γ-ray emission correlates with both the radio and the infrared emission over several orders of magnitude, regardless of the underlying input model.

plots of radio and infrared flux versus gamma-ray intensity

Figure 1: Radio (left two columns) and infrared (right two columns) vs. γ-ray correlation plots for a galaxy viewed face-on from 50 kpc. Each panel modifies one input — the cosmic-ray source distribution, gas, radiation field within the galaxy, or magnetic field — relative to a baseline model. Colors indicate γ-ray production mechanisms (green: proton–gas; black: inverse-Compton; orange: total). Across all variations, both the radio–γ-ray and infrared–γ-ray correlations remain quasi-linear over several orders of magnitude, showing that the correlations are robust to the choice of underlying galactic model. [Adapted from Porter et al. 2026]

In contrast, Figure 2 shows the correlation plot between radio and γ-ray emission (upper panels) and between infrared and γ-ray emission (lower panels) when viewing the galaxy edge-on (viewing the disk from the side). The radio–γ-ray correlation is preserved, while the infrared–γ-ray correlation is no longer observed. This is because, at this inclination, geometric projection separates the emission components. Infrared-emitting dust and γ-ray emission from cosmic ray–interstellar medium interactions are confined to the disk, while synchrotron radio emission and γ-ray emission from inverse-Compton scattering extend to larger distances above and below the disk. As a result, in an edge-on view, a sight line passing through the disk sees strong infrared emission, while a sight line that misses the disk sees zero infrared but still some γ-ray emission, breaking the infrared–γ-ray correlation. On the other hand, because radio emission is more extended than infrared emission, sight lines that miss the disk can still see both radio and γ-ray emission together, preserving the radio–γ-ray correlation.
relationships between infrared, radio, and gamma-ray flux for two types of galaxy models

Figure 2: Correlation plots for two galaxy models viewed edge-on from 50 kpc — simple axisymmetric (left) and complex with spiral arms (right). Top: radio vs. γ-ray; bottom: infrared vs. γ-ray. Colors indicate γ-ray production mechanisms (green: proton–gas; black: inverse-Compton; orange: total). The infrared–γ-ray correlation breaks down, while the radio–γ-ray correlation is broadened but partially preserved. [Porter et al. 2026]

However, there is one situation where the edge-on correlation comes back: when the observer is far enough away that the image becomes too blurry to resolve the galaxy’s internal structure. Figure 3 shows the same galaxy model viewed from 500 kpc, roughly the distance to Messier 31, our nearest large neighbor. At this distance, a single pixel in the image covers about 1 kpc, large enough for everything along the line of sight. The messy, broken-up pattern seen in the closer 50 kpc edge-on view (lower-right panel of Fig. 2) disappears, and a tight, nearly linear correlation comes back. This explains why nearly all distant, unresolved galaxies show tight radio–infrared–γ-ray correlations: the tightness is simply what you get when you blur everything together, not evidence that cosmic rays are actually losing all their energy locally inside those galaxies.
relationships between infrared, radio, and gamma-ray flux for simulated galaxies viewed from 500 kiloparsecs

Figure 3: Correlation plots from a complex galaxy model viewed from 500 kpc, at three different inclinations (face-on, 45°, edge-on). Top row: radio vs. γ-ray; bottom row: infrared vs. γ-ray. Colors indicate different γ-ray production mechanisms (green: proton–gas; black: inverse-Compton; orange: total). At this distance, the blurring effect of large pixels restores a tight correlation even in the edge-on view. [Porter et al. 2026]

Now we have a consistent picture of the radio–infrared–γ-ray correlation: the authors conclude that this correlation is not a direct signature of cosmic-ray calorimetry, but a geometric projection effect. In face-on systems, a single sight line integrates emission from both the disk and off-disk regions, naturally producing a linear correlation, even when cosmic rays do not lose all their energy locally to radiation (i.e., local calorimetry is absent). In edge-on systems, the correlation breaks down because geometric stratification separates the different emission components. The practical implication is significant: for unresolved galaxies, the tightness of the global correlation alone cannot be used as evidence for cosmic-ray calorimetry, and the physically meaningful information about cosmic-ray transport and escape efficiency is encoded in the scatter around the mean trend, not in the correlation itself.

Original astrobite edited by Kelsie Taylor.

About the author, Sandy Chiu:

I’m a PhD candidate at the University of Michigan, Ann Arbor. I’m interested in numerical simulations of cosmic rays feedback in galaxies and their comparison with observation.

Arp 142

Editor’s Note: Astrobites is a graduate-student-run organization that digests astrophysical literature for undergraduate students. As part of the partnership between the AAS and astrobites, we occasionally repost astrobites content here at AAS Nova. We hope you enjoy this post from astrobites; the original can be viewed at astrobites.org.

Title: The JWST EXCELS Survey: Insights into the Nature of Quenching at Cosmic Noon
Authors: Maya Skarbinski et al.
First Author’s Institution: Johns Hopkins University
Status: Published in ApJ

How to Quench a Galaxy

Look at an image of the sky taken with a sufficiently sensitive telescope, and you’ll quickly notice that galaxies tend to cluster into two main types: blue spiral galaxies, which have flat disk shapes with a central bulge, and red elliptical galaxies, which look like spherical or elliptical balls of red stars. Blue spiral galaxies can form tens to hundreds of stars every year, while elliptical galaxies have completely stopped forming stars, meaning that some process has to transform star-forming spirals into non-star-forming, or “quiescent,” elliptical galaxies. To form the current population of massive elliptical galaxies, this process had to be common about 2–3 billion years after the Big Bang at “cosmic noon,” the period when star formation in the universe peaked. The processes that “quench” star formation in massive galaxies are still being studied, and one of the best ways to study them is to find galaxies that recently quenched and look for clues about the processes that quenched them.

Post-starburst galaxies are galaxies that have rapidly quenched after a short burst of star formation. Because these galaxies quenched so quickly and so recently, it’s often possible to find signs of whatever quenched them, like the signatures of past galaxy mergers, feedback from supermassive black hole accretion, or the shutoff of gas flowing into the galaxy. Rapid quenching is pretty uncommon now, but it was a much more common way for galaxies to quench at cosmic noon. Understanding post-starburst galaxies at cosmic noon is therefore critical for understanding the formation of massive elliptical galaxies in the local universe.

The Quest for Quenched Galaxies

Today’s article uses data from the JWST Early eXtragalactic Continuum and Emission Line Survey (EXCELS) to identify post-starburst galaxies at cosmic noon and try to determine why they quenched. EXCELS is a spectroscopic survey, so the authors get a spectrum for every galaxy. The spectrum encodes information about the galaxy’s stellar population, including the mass of stars in the galaxy, the number of stars forming every year, and the history of star formation throughout the galaxy’s life.

The authors use a technique called principal component analysis to further divide the sample into young and old post-starbursts. Principal component analysis is a machine-learning technique that learns the most important features of a data set. This technique is used for “dimension reduction,” or reducing the number of data points needed to learn something about the object. A typical spectrum has hundreds or even thousands of data points, which means performing data analysis on a spectrum can be very computationally expensive. Principal component analysis takes these thousands of data points and learns broad patterns that correlate with each other. These patterns are called “supercolors” in the context of spectral data, and they encode things like the overall shape and color of the spectrum as well as the spectral shape around key features (see Figure 1 for a visualization). Since the overall shape, color, and emission/absorption line features of a spectrum come from the galaxy’s stellar population, this method can be used to identify galaxies with lots of star formation a billion years ago but very little star formation today — in other words, post-starburst galaxies.

demonstration of principal component analysis for spectra of different types of galaxies

Figure 1: An example of principal component analysis for sample star-forming (SF), quiescent (Qu), and post-starburst (PSB) galaxy spectra (left-hand side). Principal component analysis simplifies a many-dimensional data set (for example, spectra) into fewer dimensions. In this case, Super-Color 1 measures the overall color of the spectrum (shown on the left-hand side as the slope of the spectra, marked with red lines), while Super-Color 2 measures the shape of the spectrum around 4,000 angstroms (orange box). The authors use principal component analysis to identify post-starburst galaxies for further analysis (right-hand side). [Adapted from Skarbinski et al. 2026]

The authors apply principal component analysis to the galaxies in their sample and find that 11 of the galaxies in their sample are classified as post-starburst, 9 are quiescent, and 4 still have some star formation. To further analyze the stellar populations of the post-starbursts in their sample, the authors use a program called Bagpipes to fit the galaxies’ spectra. Bagpipes is a spectral energy distribution fitting software, which means that it takes the observed spectrum of a real galaxy and tries to match it to a library of different stellar spectra. By measuring the relative contribution of different kinds of stars (which all have different lifetimes), Bagpipes can compute the likely history of star formation in the galaxy (e.g., when the star formation rate peaked) as well as the present-day properties of the galaxy (things like the mass in stars versus dust and the current star formation rate). The authors use the galaxies’ star formation histories to try to find clues as to how they quenched.

How Quickly Do Post-Starbursts Quench?

First, the authors measure something called a “quenching timescale,” which they define as the length of time between when the galaxy’s star formation rate peaked and when it fell low enough that the galaxy was quenched. The quenching timescale depends on which process shut down star formation in the galaxy — feedback from black hole accretion or star formation should cause fast quenching, while galaxies that are starved of gas from the intergalactic medium should quench more slowly. The authors find that 15 of their galaxies quenched in under 500 million years, 6 took between 500 million and 1 billion years, and 3 took longer than 1 billion years to quench. The galaxies that had the highest peak star formation rates quenched the fastest, suggesting that feedback from star formation could have played a role in quenching these galaxies.

plots showing possible evolutionary tracks for two example galaxies

Figure 2: Possible evolutionary tracks in supercolor for two example galaxies as they quench. The galaxy in the top panel quenches quickly and has post-starburst supercolors for about a billion years, while the galaxy in the bottom panel quenches without ever going through the post-starburst phase. The authors use these tracks to determine how important the post-starburst phase is for quenching massive galaxies. [Skarbinski et al. 2026]

Next, the authors measure how important the post-starburst phase is to form massive quiescent galaxies. Not all galaxies that quench go through a post-starburst phase; some objects, especially those that quench slowly, will transition directly from star forming to quiescent. The authors use the star formation histories from their spectral energy distribution fits to predict how the galaxies’ supercolors changed after their star formation peaked (Figure 2) and find that six of the nine quiescent galaxies went through a post-starburst phase in the past, while the other three did not. For the objects that went through a post-starburst phase, the median time spent as a post-starburst was around 600 million years.The authors can use this measured “visibility timescale” to constrain whether the post-starburst phase is important for forming massive quiescent galaxies. If the fraction of post-starburst galaxies in a sample is high, that can be for two reasons: either a larger fraction of galaxies will eventually go through a post-starburst phase, or the post-starburst phase is very long, making it easy to find post-starburst galaxies. Using the measured timescale of 600 million years and combining with results from another article, the authors find that 40% of quiescent galaxies likely went through a post-starburst phase; for the more massive end of the sample, this fraction increases to around 73% due to the shorter visibility timescale. This suggests that the post-starburst phase is very important for forming the kind of massive quiescent galaxies we see in the local universe.

While the post-starburst phase is important, the different quenching timescales present across the sample suggest that multiple pathways existed to quench galaxies at cosmic noon, similar to what has been found in less-distant galaxies and at cosmic noon in other samples. This is also supported by the fact that four of the five galaxies with sufficient data show evidence of an actively accreting supermassive black hole that may help shut down star formation in many (but perhaps not all) massive galaxies. While the precise processes that quench massive galaxies are still uncertain, one thing is clear: JWST EXCELS at solving the mystery!

Original astrobite edited by Anavi Uppal.

About the author, Margaret Verrico:

I am a fourth-year graduate student at the University of Illinois Urbana-Champaign. I study the connection between supermassive black hole transients and their host galaxies. I am also an avid knitter and reader, and I am passionate about opening up STEM opportunities for people of all backgrounds.

Messier 17

Editor’s Note: Astrobites is a graduate-student-run organization that digests astrophysical literature for undergraduate students. As part of the partnership between the AAS and astrobites, we occasionally repost astrobites content here at AAS Nova. We hope you enjoy this post from astrobites; the original can be viewed at astrobites.org.

Title: The Rhythm of the ISM: Tracing the Timescales of Gas Evolution and Star Formation Across Galactic Environments
Authors: Zuzanna Kocjan and Vadim A. Semenov
First Author’s Institution: University of Maryland
Status: Published in ApJ

The Connection Between Gas and Star Formation in Galaxies

Stars are born in the interstellar medium (ISM) when cold, dense clouds of gas become unstable and collapse under gravity. Despite their plentiful reservoirs of gas, galaxies convert only a small fraction of this material into stars, making star formation a surprisingly inefficient process. A key factor behind this inefficiency is stellar feedback: radiation, stellar winds, and supernova explosions from young stars can inject energy and momentum into the surrounding gas, heating, stirring, and dispersing it. In this way, stellar feedback shapes future star formation across scales ranging from individual regions in the ISM to whole galaxies.

An important tool astronomers use to study star formation is the Kennicutt–Schmidt relation, which links the amount of gas in a galaxy to the rate at which stars form. More specifically, it relates the gas surface density, Σgas, to the star formation rate surface density, ΣSFR. (For more on this relation, see this Astrobites article on a classic research article.) However, this law is underpinned by a crucial ingredient: timescales. In particular, the pace of star formation depends both on how quickly galactic gas is cycled into star-forming material and on how rapidly those regions convert gas into stars once they form. Today’s article investigates the physical origin of star-formation scaling relations behind the Kennicutt–Schmidt law by building on a simple theoretical framework for the ISM.

Consider a Kettle of Boiling Water…

In a given region of a galaxy, the ISM consists of gas in either an actively star-forming state or an inert, non-star-forming state, depending on whether it is dense and unstable enough to collapse (as illustrated in Figure 1). The transition of non-star-forming gas into the star-forming state occurs on the supply timescale, τ+. Conversely, the dispersal of star-forming gas back into a non-star-forming state is characterized by the removal timescale, τ–. As a helpful analogy, the authors compare this process to water boiling in a kettle: the ISM is continuously “boiling,” with gas moving between active and inactive states. Meanwhile, the total gas reservoir gradually decreases, analogous to water slowly evaporating as the kettle boils. The gas depletion time, τ*, therefore represents the timescale over which the available gas would be exhausted by star formation.

Schematic of the gas cycling framework

Figure 1: Schematic of the gas cycling framework used in the authors’ theoretical model for how gas is converted into stars, which takes into account a supply, removal, and depletion timescale. [Adapted from Kocjan and Semenov 2026]

Building on this picture of gas cycling, the authors turn to simulated galaxies, where the motion and evolution of the gas can be followed directly. By tracking how gas flows through the ISM in the simulations, they derive the three characteristic timescales above — τ+, τ–, and τ* — that describe how gas is supplied to, removed from, and ultimately consumed by star formation. The goal is to connect the small-scale physics of the ISM to the large-scale star formation efficiencies and scaling relations observed across galaxies.

The Timescales of the Interstellar Medium

To explore how gas and star formation are connected across different galactic environments, the authors analyze three simulated systems: a dwarf galaxy, a Milky Way–like galaxy, and a gas-rich starburst galaxy, as shown in Figure 2. Despite spanning very different physical regimes, the galaxies exhibit remarkably similar trends in the fraction of gas actively forming stars as a function of Σgas​. This suggests that the amount of star-forming gas is governed primarily by local interstellar conditions, since regions with higher gas surface densities tend to contain denser, more strongly self-gravitating gas.

galaxy simulations and star-forming gas fraction

Figure 2: Using simulations (left to right) of an isolated intermediate-mass dwarf galaxy, Milky Way–like galaxy, and gas-rich galaxy, the authors measure the star-forming gas fraction versus the gas surface density (right). [Adapted from Kocjan and Semenov 2026]

To further understand this trend, this study then applies the authors’ theoretical framework to determine the timescales of ISM gas cycling on the scales of individual star-forming regions. These include the timescales for the formation, dispersal, and local depletion of star-forming gas as described above: τ+, τ−, and τ∗, which also exhibit strong correlations with the gas surface density (see Figure 3). Specifically, the timescale for supplying gas into the star-forming state is linked to the rate at which turbulence redistributes material through the galactic disk. The depletion timescale, over which star-forming gas is turned into stars, decreases at higher Σgas​, since denser regions more efficiently collapse and form stars. By contrast, the removal timescale is comparatively short, reflecting how quickly feedback and changes in local equilibrium can disrupt star-forming clouds. In this way, the “boiling kettle” framework is able to capture the major processes driving small-scale gas evolution.
Scaling relations between the supply, depletion, and removal times

Figure 3: Scaling relations between the supply (left), depletion (middle), and removal (right) times in kiloparsec-scale regions of the simulated galaxies (shown in different colors). Based on the measurements from the simulations, the authors introduce a parameterized model for the gas cycling framework, as defined in the equations. [Adapted from Kocjan and Semenov 2026]

The cycling of gas through different phases of the ISM offers a useful framework for understanding how galaxies form stars. In the relatively well-ordered systems studied here, this balance can be described in simple terms; however, it is likely to become more complex in extreme environments where additional physical processes — such as those operating in the early stages of galaxy formation — play a significant role. Even so, these results highlight how key galactic properties can emerge naturally from the interplay between galaxy-scale dynamics, ISM turbulence, and the state of star-forming gas.

Original astrobite edited by Jayde Willingham.

About the author, Shalini Kurinchi-Vendhan:

After studying astrophysics and literature at Caltech, I moved onto a Fulbright Fellowship in Heidelberg, Germany. I’m passionate about using computer simulations to explore supermassive black holes and galaxy evolution — but I also love poetry and traveling.

Mars from Mars Global Surveyor

Editor’s Note: Astrobites is a graduate-student-run organization that digests astrophysical literature for undergraduate students. As part of the partnership between the AAS and astrobites, we occasionally repost astrobites content here at AAS Nova. We hope you enjoy this post from astrobites; the original can be viewed at astrobites.org.

Title: Mars as an Exoplanet: Lessons from a Planet at the Edge of Habitability
Authors: Stephen R. Kane et al.
First Author’s Institution: University of California, Riverside
Status: Published in PSJ

Mars in the Upside Down

If you’re a fan of Stranger Things like me, you’ll know of the Upside Down: a mirror world similar to our own, but with very different rules. Imagine Mars in the Upside Down, where it is no longer our next-door neighbor but a planet hundreds of light-years away. An astronomer on this Upside Down Earth would be looking at a distant speck with a transit signal barely distinguishable from noise. In this world, Mars would no longer be familiar but completely foreign, with unknown properties. Kane et al. suggest that treating Mars as if it were a stranger is a useful way to think about exoplanet science today.

JWST is hunting for atmospheres on small rocky planets around other stars. However, only a select few Mars-like exoplanets have been discovered (Figure 1). This is because sub-Earth planets are small and hard to detect, testing the bounds of current technology. The ones that have been discovered, such as TRAPPIST-1h and Kepler-138b, were detected due to favorable geometry. They happen to orbit very close to a low-mass star or sit in resonant multi-planet systems, which amplify the signal we are looking for. True Mars analogs with low flux and moderate orbital periods remain out of reach. This is precisely what makes Mars itself so important scientifically — it is the only planet of this type we can study up close.

Plot of planetary radius versus planet mass, with symbols colored by incident stellar flux.

Figure 1: A plot of confirmed exoplanets by mass and radius. Most confirmed exoplanets are larger and more massive than Earth. Mars-like planets (dots in the blue box) are rare in confirmed exoplanet detections. [Kane et al. 2026]

Getting to Know Mars, Getting to Know All About Mars

We know a lot about Mars in comparison to other planets thanks to rovers (such as Curiosity and Perseverance), atmospheric orbiters (such as Mars Atmosphere and Volatile EvolutioN and the Mars Orbiter Mission), and other science missions (Figure 2). We know it once had water features with neutral pH and favorable chemistry for life from sedimentary evidence at the Gale and Jezero craters. We know its atmosphere is 95% CO2 with a surface pressure less than 1% of Earth’s. We know it once had an active magnetic dynamo, but the dynamo died out about 4 billion years ago, leading to solar wind steadily stripping away Mars’s atmosphere over time.

Diagram showing Earth and Mars to scale

Figure 2: Earth and Mars to scale, showing their internal structures and atmospheres. Despite being neighbors, Mars is dramatically smaller with a thin CO2 atmosphere, similar to the planets JWST is struggling to characterize. [Kane et al. 2026]

But in the Upside Down, we would know none of this since Mars would be so distant. With current technology, this Upside Down Mars would be essentially undetectable using transit signals, radial velocity measurements, and spectrographs.

Beyond Our Backyard

JWST is currently studying the small rocky TRAPPIST-1 planets and is finding little evidence of atmospheres. The authors of today’s article explore the idea that these exoplanets are similar to Mars and perhaps are undergoing processes that strip away their atmospheres and create optimal conditions for life only for short durations. Using Mars as a blueprint, the authors show how we can better understand exoplanet processes, including volatile delivery and loss, photochemistry, climate evolution, obliquity forcing, planetary architecture, and intrinsic magnetism. For example, measurements of noble gases directly fingerprint Mars’s atmospheric escape process, and the authors argue these give us a calibration framework for interpreting future exoplanet spectra.

The upcoming Nancy Grace Roman Space Telescope’s microlensing survey will start revealing how common true Mars analogs actually are throughout the galaxy, while the future Habitable Worlds Observatory will attempt direct imaging of nearby candidates with unprecedented precision. Together, these missions will tell us whether Mars-like outcomes (brief habitability, catastrophic atmospheric loss, barren surfaces, etc.) are the default fate for small rocky planets. Interpreting that data will require the exact framework this article builds: one grounded in the only Mars analog we can study in detail.

Original astrobite edited by Sandy Chiu.

About the author, Ben Sherwin:

I am a physics PhD student and a National Science Foundation Graduate Research Fellow at Stanford University, working with Josh Frieman. I am interested in theoretical and observational cosmology, specifically in cross-correlations between the cosmic microwave background and tracers of large-scale structure.

side-by-side images of Venus's surface today and an imagining of what its surface might have looked like in the past

Editor’s Note: Astrobites is a graduate-student-run organization that digests astrophysical literature for undergraduate students. As part of the partnership between the AAS and astrobites, we occasionally repost astrobites content here at AAS Nova. We hope you enjoy this post from astrobites; the original can be viewed at astrobites.org.

Title: Carbon Cycle Imbalances on Arid Terrestrial Planets with Implications for Venus
Authors: Haskelle T. White-Gianella and Joshua Krissansen-Totton
Authors’ Institution: University of Washington
Status: Published in PSJ

The Carbon-Cycle Thermostat

When discussing the habitability of planets, we usually focus on the habitable zone, the region around a star where a planet can host a temperature suitable for supporting liquid water on its surface. Yet, being in the right place doesn’t necessarily guarantee that a planet will be habitable.

A planet also needs the right atmospheric composition to sustain the necessary temperatures for hosting liquid water. A key mechanism found on Earth for maintaining this composition is the geologic carbon cycle, which acts as a built-in climate control system. This cycle begins with volcanic eruptions releasing carbon dioxide (CO2), which then dissolves in rainwater and forms a weak acid that weathers rocks on continents. The weathering products wash into oceans, where they form carbonate rocks, locking carbon away. Eventually, plate tectonics recycles some of that carbon back to volcanoes. The weathering process works faster when the planet is warmer, thus regulating the amount of CO2 and stabilizing the climate over long periods of time (but it should be noted that it can take up to a few hundred thousand years to rebalance this slow carbon cycle through the weathering process).

An important caveat is that the weathering process requires sufficient liquid water on the planet’s surface, so what happens in the case for planets with shallower oceans? Low-mass M dwarfs, the most common type of star found in the galaxy, are expected to host less-massive disks and therefore lower water inventories for forming planets. If more “dry” planets are indeed a more likely outcome of planet formation, we’d want to know how their arid conditions influence their long-term evolution and habitability.

Creating Carbon-Tracking Models

The authors built a model that tracks how water and CO2 move between a planet’s interior, oceans, and atmosphere over 4.5 billion years. The model notably includes the following:

  • A sophisticated weathering model that accounts for how runoff can limit rock weathering, improving upon previous models that only included a temperature dependence on weathering
  • Wind-driven evaporation limits that influence the amount of water evaporation in addition to sunlight-driven evaporation
  • Multiple deep water cycle parameterizations that explore how water moves between the interior and the surface

The model tests for four initial surface water inventories (0.1%, 1%, 10%, and 100% of Earth’s oceans) and then simulates how the surface water, atmosphere, and climate evolve over time.

A Critical Water Threshold

The models reveal that planets require at least 20–50% of Earth’s ocean mass to maintain a balanced carbon cycle. Below this threshold, the carbon cycle becomes unbalanced, leading to devastating consequences for habitability (Figure 1).

two plots of final surface temperature as a function of initial surface water mass

Figure 1: Final surface temperature after simulating 4.5 billion years of evolution as a function of initial water inventory for Earth-like planets. Each dot represents a model run with different assumptions (total carbon inventory, temperature dependence of weathering, soil age, etc.). The yellow region shows where most simulations result in uninhabitable surface temperatures from an unbalanced carbon cycle, and the cyan region shows where most simulations result in habitable surface temperatures and a balanced carbon cycle. The left and right plots show the results for two different parameterizations of the deep water cycle implemented in the model. [White-Gianella & Krissansen-Totton 2026]

For the more arid planets, models reveal a concerning runaway process. Limited surface water reduces precipitation and slows rock weathering. Weathering cannot keep up with volcanic CO2 release, causing CO2 buildup and warming of the atmosphere. The cycle repeats, driving runaway warming until all water evaporates.

Important Implications (Within and Outside Our Solar System)

Looking within the solar system, the results offer an explanation for how a potentially habitable Venus could have transitioned into its current inhospitable state. If Venus had formed with an initial water inventory below this critical threshold of 20–50% of Earth’s ocean mass, then its carbon cycle would have become unbalanced, creating the CO2 inferno seen on Venus today.

In future exoplanet studies, telescopes like the Habitable Worlds Observatory might detect ocean glint (specular reflection from liquid water) or measure land fraction from light curves. Finding a planet in the habitable zone but with limited ocean coverage would likely be bad news, as the planet could be quietly losing its grip on habitability. Astronomers may want to be more careful when looking at seemingly promising planets within their habitable zones.

Original astrobite edited by Natalie Price.

About the author, Jared Bull:

I am a 2nd-year PhD student at Johns Hopkins University. I study brown-dwarf variability and am interested in using time-series observations to uncover dynamic processes within their atmospheres. In my free time I like to read, cook, and do astrophotography.

distant starburst galaxies

Editor’s Note: Astrobites is a graduate-student-run organization that digests astrophysical literature for undergraduate students. As part of the partnership between the AAS and astrobites, we occasionally repost astrobites content here at AAS Nova. We hope you enjoy this post from astrobites; the original can be viewed at astrobites.org.

Title: MAGAZ3NE: Confirming Dust Deficiency and Quiescent Nature of Ultramassive Galaxies at 3 < z < 4 with ALMA Observations
Authors: Wenjun Chang et al.
First Author’s Institution: University of California, Riverside
Status: Published in ApJ

Distant galaxies offer a unique window into how stars, gas, and dust evolve over cosmic time. Tracing this evolution requires understanding not only how galaxies form, but also how and when they stop forming stars, a process known as quenching. Understanding how, when, and why galaxies quench is a fundamental question in astrophysics, and one that requires observations of star-forming, quenching, and fully quenched galaxies alike. Unfortunately, one complication is that identifying truly quenched galaxies is challenging: galaxies that appear “dead” may instead be actively forming stars, hidden behind a thick veil of dust.

In today’s article, the authors use observations from the Atacama Large Millimetre/submillimetre Array (ALMA) to investigate five ultramassive galaxies at redshifts, z, between 3 and 4, and ask a deceptively simple question: are these massive red galaxies genuinely quenched, or are they secretly forming stars behind the scenes?

Meet the Suspects: Ultramassive Galaxies at the Edge of Cosmic Noon

The five galaxies in this study are drawn from the Massive Ancient Galaxies at z > 3 NEar-infrared (MAGAZ3NE) survey, which targets some of the most massive galaxies known at early cosmic times. All five have stellar masses exceeding 100 billion solar masses and have been confirmed at z > 3. At these redshifts, we are observing the galaxies as they were when the universe was less than 2 billion years old. This is just before an epoch known as cosmic noon, when star formation across the universe reached its peak.

These galaxies also benefit from extensive multiwavelength observations from a range of observatories, including the ground-based Visible and Infrared Survey Telescope for Astronomy and the Spitzer Space Telescope. By combining imaging across wavelengths from the ultraviolet to the near-infrared, astronomers can measure the “colours” of galaxies and use these colours to infer the galaxies’ star-forming activity.

Galaxies that have quenched their star formation are dominated by older stellar populations, which makes them appear red (hence why they are often referred to as “red and dead” galaxies). However, dust can redden galaxies in a similar way by absorbing blue light and re-emitting it at longer wavelengths — meaning that a dusty, star-forming galaxy can easily masquerade as a quenched one. To uncover any hidden star formation, the authors turn to ALMA to search for far-infrared dust emission. The sample of galaxies investigated with ALMA is shown in Figure 1.

UVJ color–color diagram

Figure 1: UVJ colour–colour diagram, which uses galaxy colours in the ultraviolet (U), visible (V), and near-infrared (J) to identify quenched galaxies. The five ultramassive galaxies (UMGs) studied here (filled cyan circles) lie firmly in the quenched region (QG), consistent with a lack of ongoing star formation. Crosses indicate galaxies undetected in ALMA dust emission, while other massive galaxies at similar redshifts are shown in grey for comparison. [Chang et al. 2026]

ALMA on the Scene

ALMA observes light at sub-millimetre wavelengths, which at these redshifts traces emission from star-forming regions that are obscured by dust. Of the five ultramassive galaxies in this sample, only one is detected with ALMA. Even when the remaining four galaxies are stacked together, no dust emission is recovered, indicating that if any dust is present, it must be extremely faint.

To better quantify what these ALMA non-detections imply, the authors perform spectral energy distribution fitting (see a recent overview bite on spectral energy distribution fitting) using the Code Investigating GALaxy Emission, or CIGALE, a code that enforces energy balance between absorbed starlight and dust emission to estimate physical properties such as a galaxy’s star formation rate and dust content. With the ALMA constraints included, all five galaxies are found to lie more than 10 times below the star-forming main sequence. Even the single ALMA-detected galaxy remains formally quenched, showing only weak residual star formation.

In other words, these galaxies really are dead (or at least extremely dormant).

Extremely Dust-Poor Galaxies

The spectral energy distribution fitting also allows the authors to measure how much dust these galaxies contain relative to their stellar mass. This ratio provides a simple but powerful way to assess how much interstellar material remains in a galaxy — and therefore how much fuel is left for future star formation.

Three of the five ultramassive galaxies have ratios of Mdust/Mstar < 10-4 (Figure 2), placing them among the most dust-poor quenched galaxies confirmed at z > 3. The lone galaxy detected by ALMA contains slightly more dust, with Mdust/Mstar = 10-3, but even this is far below what would be expected for an actively star-forming galaxy. For comparison, typical star-forming galaxies at similar stellar masses host more than 100 times more dust.

Plot of dust-to-stellar mass ratio versus redshift

Figure 2: The ratio of dust mass to stellar mass versus redshift for massive quenched galaxies (QGs). This quantity measures how dust rich a galaxy is compared to its stellar mass. The ultramassive galaxies in this study (cyan pentagons) fall well below the dust content expected for star-forming galaxies (solid blue line), highlighting their extreme dust deficiency. [Adapted from Chang et al. 2026]

These results raise important questions about how galaxies can become ultramassive, quenched, and nearly dust-free within the first two billion years of cosmic history.

For now, ALMA has delivered a clear answer to the question of “dead or in disguise?”: at least some candidate ultramassive galaxies in the early universe really are quenched, and they are strikingly dust poor. By ruling out the dusty impostor scenario, this study shows that deep ALMA observations can cleanly distinguish genuinely quenched galaxies from dusty star-forming ones, even at the highest stellar masses and earliest cosmic times. How these galaxies lost their dust remains an open question, but one thing is clear: by the time cosmic noon arrived, some galaxies had already finished forming stars and quietly faded into dormancy.

Original astrobite edited by Viviana Cáceres.

About the author, Lucie Rowland:

I’m a fourth (and final!) year PhD student at Leiden Observatory in the Netherlands, studying massive, star forming galaxies in the early universe with ALMA and JWST. It’s a really exciting time to be interested in astronomy, so I hope to make groundbreaking new research more accessible!

disk of hot gas swirling around a black hole

Editor’s Note: Astrobites is a graduate-student-run organization that digests astrophysical literature for undergraduate students. As part of the partnership between the AAS and astrobites, we occasionally repost astrobites content here at AAS Nova. We hope you enjoy this post from astrobites; the original can be viewed at astrobites.org.

Title: The Wandering Supermassive Black Hole Powering the Off-Nuclear Tidal Disruption Event AT2024tvd
Authors: M. Guolo et al.
First Author’s Institution: Johns Hopkins University
Status: Published in ApJL

A Star Gets Eaten in the Wrong Neighborhood

We find supermassive black holes at the centers of most large galaxies. They end up there because of how galaxies form: as matter collapses and merges over time, material sinks to the gravitational center, and the black hole settles in.

So, what happens when we catch a star being ripped apart by a supermassive black hole that is not at the center of its galaxy?

That is exactly the puzzle posed by AT2024tvd, a tidal disruption event (TDE) spotted roughly 2,600 light-years from the center of a massive galaxy located 600 million light-years away from us (see Figure 1).

AT2024tvd from Hubble and JWST

Figure 1: A color image of AT2024tvd from the Hubble Space Telescope and JWST. The yellow dot inside the square marks the galaxy’s center, while the TDE is the white dot, which is visibly offset to the upper left, about 2,600 light-years away. [Adapted from Guolo et al. 2026]

We see TDEs when a black hole tears apart a star that gets too close to it. It happens because the black hole’s gravity pulls harder on the near side of the star than the far side, stretching the star until it comes apart. The stellar debris then forms a hot accretion disk, a ring of material swirling around the black hole that spirals inward and releases a burst of electromagnetic energy across many wavelengths — from visible light to X-rays. These events are valuable to astronomers because they briefly light up black holes that would otherwise be invisible, giving us a rare window to measure their properties. Since supermassive black holes live at galactic centers, that is also where we expect TDEs to happen, which makes a TDE found away from a galactic center rare and puzzling. The galactic center is often called the nucleus of a galaxy, so astronomers refer to these displaced events as “off-nuclear” TDEs. AT2024tvd is only the third known off-nuclear TDE, and this research article makes a strong case that it is the most remarkable one yet.

Measuring Mass Using Light

To figure out the mass of the black hole responsible for AT2024tvd, the authors needed to get creative. You cannot weigh a black hole directly, so astronomers have to work backward from what they can see. The key idea is that a black hole’s mass controls how its accretion disk behaves. A more massive black hole produces a larger, cooler disk, while a less massive one produces a smaller, hotter disk. By measuring how bright the disk is at different wavelengths and how hot it gets, you can figure out how massive the black hole must be.

The authors did this by modeling the light the event produced across many wavelengths. They combined data from several telescopes: the Zwicky Transient Facility, the Neil Gehrels Swift Observatory, Pan-STARRS, and two rounds of high-quality X-ray data from XMM-Newton. TDE light curves go through different phases. The early flare in visible and ultraviolet light is bright but complicated, and the physical processes behind it are not fully understood. But after a few hundred days, TDEs settle into a quieter “plateau phase,” where the ultraviolet and visible light come directly from the accretion disk. At this stage, the emission follows well-understood physics, and astronomers can model it reliably.

The authors used a model called kerrSED, which describes the spectral energy distribution (SED) of a spinning black hole’s accretion disk (kerr). It accounts for the disk’s temperature, its physical size, the black hole’s spin (how fast it rotates), and the angle at which we are viewing the system. It also accounts for a process called Comptonization, where hot electrons near the black hole boost lower-energy photons (particles of light) up to X-ray energies. By fitting this model to the observed light at multiple wavelengths simultaneously, the authors could pin down the disk properties and extract the black hole mass. The result was a clean fit: the disk model alone could explain all the observed light during the plateau phase, with nothing significant left over (see Figure 2).

brightness evolution of AT2024tvd

Figure 2: The brightness of AT2024tvd measured across a wide range of wavelengths, after correcting for absorption and the galaxy’s motion. The symbols show individual measurements from different telescopes, while the shaded contours represent the best-fit disk model and its uncertainty. Left: The early X-ray data, which is well explained by emission from the hot inner accretion disk. Right: The later data covering both visible/ultraviolet light and X-rays, all consistently explained by the same disk model. [Adapted from Guolo et al. 2026]

Not an Intermediate, but a Supermassive Black Hole

From their fit, the authors found a black hole mass of about one million solar masses. Black holes above about 100,000 solar masses are considered supermassive, while those below that threshold but above about 100 solar masses are called intermediate-mass black holes. So, this puts AT2024tvd in the supermassive category. This matters because the two previously known off-nuclear TDEs, called 3XMM J2150-05 and EP240222a, were both powered by intermediate-mass black holes. Those black holes were found inside small, dense collections of stars called ultra-compact dwarf galaxies that were orbiting larger host galaxies.

AT2024tvd is different. When the authors looked at deep images of the location where the TDE happened, they found no star cluster or small galaxy there. Whatever group of stars once surrounded this black hole has been almost entirely pulled apart by the gravity of the much larger parent galaxy. The ratio of the black hole’s mass to the mass of any remaining stars around it is extreme: greater than 3%, which is far above what we normally see. This is the signature of a “wandering” supermassive black hole, one that was brought in during a past galaxy merger and has been slowly sinking toward the center of its new host ever since, losing its surrounding stars along the way.

The authors compared AT2024tvd to other TDEs using established relationships between accretion disk properties and black hole mass (Figure 3). In terms of its disk temperature, luminosity, and inferred mass, AT2024tvd behaves like a typical nuclear TDE powered by a supermassive black hole. However, when placed on the black hole mass versus host stellar mass relation, it stands out as a strong outlier. The black hole mass is far too large for the small amount of surrounding stellar mass detected at its location.

plot of black hole mass versus host galaxy mass

Figure 3: AT2024tvd (yellow star) plotted on the relationship between black hole mass and host galaxy stellar mass. Red squares show nearby galaxies with dynamically measured black hole masses plotted against galaxy bulge stellar mass, while blue squares show the relation using total galaxy stellar mass. Purple points and green diamonds represent nuclear TDE host galaxies with black hole masses inferred from different TDE modeling techniques. Yellow diamonds mark the two previously known off-nuclear TDEs. AT2024tvd stands out as a clear outlier, with a very high black hole mass compared to the upper limit on any surrounding stellar mass. [Guolo et al. 2026]

The Big Picture

This discovery matters for several reasons. It shows that off-nuclear TDEs are not limited to intermediate-mass black holes sitting in small satellite galaxies. Some are powered by fully supermassive black holes that have been displaced from their original galactic centers. It also shows that TDE modeling, when done carefully during the plateau phase of the light curve (when the emission is dominated by well-understood accretion disk physics), can provide reliable black hole masses on its own, without assuming any relationship between the black hole and its host galaxy. This is particularly important for wandering black holes, where those relationships do not apply.

Looking ahead, upcoming surveys like Vera C. Rubin Observatory’s Legacy Survey of Space and Time are expected to find many more off-nuclear TDEs. Combined with X-ray follow-up from telescopes like XMM-Newton, these events could become our main tool for mapping out the population of displaced black holes in the nearby universe. One disrupted star at a time, we are starting to find black holes that theory told us should exist but that had, until now, stayed hidden.

Original astrobite edited by Kelsie Taylor and Veronika Dornan.

About the author, Serat Saad:

Serat is a first-year PhD student in astronomy at The Ohio State University. His research is on stellar and galactic dynamics, where he uses observational data to understand gravity. He also has interests in active galactic nuclei and tidal disruption events.

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