Astrobites RSS

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: Dynamics of Planetary Rings Under Thermal Forces
Authors: Wen-Han Zhou et al.
First Author’s Institution: The University of Tokyo
Status: Published in ApJL

If you ask anyone what their favourite planet is, the answer you’ll most likely hear is Saturn. Why? Why else than the beautiful and intricate ring system surrounding the gas giant. The other gas and ice giants in our solar system — Jupiter, Uranus, and Neptune — have ring systems themselves but none quite as striking as Saturn’s. Would it surprise you to learn that astronomers’ best models have not yet totally explained why Saturn’s rings look the way they do?

In contrast, it may not surprise you to hear that people have been trying to explain the rings for as long as we have seen them with telescopes. We now know that planetary rings are collections of relatively small particles (think micrometre up to metre sized), most likely having once been the material of a larger body that was disrupted either by collisions or tidal forces. This material, due to the gravity of its local planet, is sculpted into a flat disc where more subtle interactions then lead to substructure forming within the disc such as gaps and ringlets. Many of these substructures are explained by well-understood physics — for example gaps being carved by embedded moonlets or resonances sculpting ring edges — though there remain some outstanding problems in our understanding.

The authors of today’s article set their sights on the problematic inner edge of Saturn’s A ring (Figure 1). They describe some mechanisms — namely the collisions of micrometeoroids within the rings — by which a sharp ring edge can be maintained, but there exists a gap in the understanding of how such an edge can form in the first place. All hope is not lost, though, as today’s authors reintroduce a physical process they call the “eclipse–Yarkovsky” effect, which seems to explain these phenomena.

horizontally sliced Saturn's rings

Figure 1: A horizontally sliced image of Saturn’s rings shows the rich substructure and gaps within the various rings. Saturn, which is not shown here, would be to the left of the image. The authors of today’s article are particularly concerned with the bright and sharp inner (left side) edges of the A and B rings. Click to enlarge. [NASA/JPL/Space Science Institute]

Billions of Rocket-Powered Bumper Cars

The idea behind this process revolves entirely around light. When sunlight hits a particle within a planetary ring, non-absorbed sunlight imparts a little “bump” onto a particle, ever so slightly altering its trajectory. At the same time, some of the sunlight is absorbed into the particle, which heats it up; light is soon re-emitted via thermal radiation, which, again, can slightly change the trajectory of these tiny particles. From a point on the surface of each ring particle (see rightmost side of Figure 2), the photons from this thermal radiation are all emitted in random directions; however, across the whole surface of the particle there is a net force! These tiny particles are spinning, and so the side just near “sunset” is hottest and emitting the most thermal photons. In this way, the pressure from the sunlight plus the thermal radiation of each particle imparts a net torque on the ring itself which changes the angular momentum of the ring.

diagram showing sunlight falling on Saturn and the planet casting a shadow on its rings

Figure 2: Starlight is the main source of light onto the particles that make up a planetary ring (right panel) though reflected light from the planet’s surface hits it too. This light “heats up” the ring and forms an asymmetry as the ring is eclipsed by the planet, which produces a net force. [Zhou et al. 2026]

What we described just then is essentially solar radiation pressure plus the Yarkovsky effect. It turns out that the net force from this process typically averages out to zero as the ring particles orbit around the planet. This assumes, though, that the sunlight is constantly shining on the ring. Stunning imagery of Saturn tells us that this isn’t the case, so what happens when we take into account the shadow cast on the ring from the planet? Today’s authors find that the net effect induces a positive change in angular momentum of the ring particles, which they call the eclipse–Yarkovsky effect.

After today’s authors detailed all of the math involved in this process (and there is a lot), they put it into practice to try to help explain Saturn’s curious rings. Including the eclipse–Yarkovsky effect together with other known effects that drive ring evolution allowed them to reproduce the optical depth profile (how thick the ring looks) of Saturn’s A ring better than ever before (notably the sharp inner edge in Figure 3). On top of this, the effect provides another avenue for moonlet formation in the outer edges of ring systems as the positive torque from the effect drives material out toward and away from the Roche limit.

plot of optical thickness versus radius

Figure 3: The authors try to explain the current structure of Saturn’s A ring by initialising it with a Gaussian profile of optical thickness versus radius (black dot-dashed line) and evolving it for 81 million years under different effects. When viscous effects are included (blue dashed line), the ring spreads out, but it’s only when the eclipse–Yarkovsky (EY) effect is included (red line) that the model closely matches the observed data (grey line). [Zhou et al. 2026]

Undeniably useful for Saturn, the eclipse–Yarkovsky effect may also explain some other conundra in the solar system. Mars may have once had rings, which are thought to have eventually clumped together to form the inner moon Phobos. This idea is problematic, though, in that current models suggest there should still be some residual ring system around Mars even after Phobos formed. Enter the eclipse–Yarkovsky effect: being 100 times stronger for Mars than Saturn (due to its more intense incident sunlight), the effect may have driven out and dispersed that residual ring altogether. While the authors are currently looking into this possibility, the reintroduction of the eclipse–Yarkovsky effect has already shown great promise for our most beautiful ringed planetary neighbour.

Original astrobite edited by Wasi Naqvi.

About the author, Ryan White:

I am a first-year PhD student at Macquarie University in Australia, working mainly on binary/multiple systems with massive stars (Wolf–Rayets in particular!). Outside of study, I’m probably drinking coffee, baking, reading, or going for a run. You can also find me procrastinating on Bluesky @astroryan.bsky.social.

M-dwarf star with starspots

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: A Panchromatic JWST Spectrum of a Giant Starspot on the Fully Convective M Dwarf TOI-3884
Authors: C. A. Murray et al.
First Author’s Institution: University of Colorado Boulder
Status: Published in ApJ

We often picture stars as smooth, glowing spheres, as if they’ve been run through an Instagram filter. But real stars have spots: cooler, darker regions on a star’s surface caused by strong magnetic fields.

Annoyingly, these spots can seriously interfere with how we study exoplanet atmospheres.

How to Probe a Planetary Atmosphere

Planetary atmospheres are often probed through transmission spectroscopy. When a planet transits its star, some starlight passes through the planet’s atmosphere before reaching us. We can distinguish the light that has passed through the planet’s atmosphere by comparing the star’s light in transit versus out of transit. In doing so, we can isolate the atmospheric spectrum and look for absorption features of species like water or oxygen.

Easy, right?

How Starspots Get in the Way

Things get more complicated once we stop thinking of the star as if it’s been smoothed out by an Instagram filter. Starspots are cooler than the surrounding stellar surface, which means they emit a different spectrum. They are also constantly changing: new spots can form, old ones can disappear, and the star’s rotation carries them in and out of view. This changes things.

First of all, your star’s spectrum changes over time, which could mean that the star’s spectrum out of transit is not the same as the star’s spectrum during transit. On the other hand, the planet may transit across a starspot instead of a “normal” stellar region. In this case, the light we measure during the transit is affected by the spot, and it is no longer accurate to directly compare it with the overall stellar light outside the transit.

Ultimately, absorption features that we thought were from the planetary atmosphere could actually be coming from starspot contamination instead.

Starspot Models: Our Solution?

To deal with this, astronomers build starspot models, where they vary the spots in terms of the following:

  • The surface covering fraction: this parameter tells us how much of the stellar surface is covered in spots
  • The temperature contrast: this parameter tells us how much cooler (in ratio) the spot is compared to the rest of the stellar surface, and by proxy how much dimmer

These models are promising, but how do we know that we have chosen the right parameters?

A Unique Laboratory: TOI-3884

The TOI-3884 system is a unique laboratory for testing our starspot models. As seen in Figure 1, it has very convenient starspot geometry, with a large starspot located close to its pole. On top of that, we observe this star almost completely pole-on, which means that we always see this starspot, no matter how much the star rotates. To top this all off, the star hosts a close-in planet, which orbits the star from pole to pole.

Illustration of the TOI-3884 system

Figure 1: Illustration of the TOI-3884 system. The pole (and rotation axis) of the star is indicated with a black “x,” indicating that we see the star almost pole-on. The polar starspot is indicated in grey, and the transiting planet TOI-3884b is indicated in black. Different dates are shown, illustrating how the system evolves over the span of a few weeks. [Adapted from Mori et al. 2025]

The planet transits the star, and as it does so, it always passes over the polar starspot. This gives us a rare opportunity to probe the spectrum of a starspot. Similar to how we can use normal in/out of transit observations to probe a planetary atmosphere, we can now compare the observations during/after a “starspot transit” to probe the starspot region. Today’s authors do exactly this using six different transit observations from JWST.

So… How Good Are Our Models?

From the JWST observations, the authors extract a starspot spectrum for the first time. Figure 2 shows this as the spot contrast (how much dimmer the spot is than the surrounding stellar surface) plotted across different wavelengths. To see how well our models are doing, they compare this observed spectrum to two commonly used starspot models. The difference between the data and the models (the residual) is plotted in the lower panel.

spectrum of TOI-3884’s starspot.

Figure 2: The spectrum of TOI-3884’s starspot. The y-axis in the upper panel, the spot contrast, indicates how much dimmer the starspot is compared to the “normal” stellar surface. Different observations taken with JWST are indicated in different colored crosses, and other previous observations are overplotted in various other shapes. Model starspot spectra are shown in dashed or dotted black lines. The residuals between the model spectra and the JWST observations are shown in the bottom panel. [Adapted from Murray et al. 2026]

At wavelengths longer than about 1 micron, in the near-infrared regime, things look good! The residuals stay small, meaning the models do a solid job reproducing the observations. But move left into shorter wavelengths, in the optical regime, and the agreement quickly falls apart. The residuals grow, and it becomes clear that the models are missing something.

There’s still work to be done before we can confidently probe planetary atmospheres at optical wavelengths without worrying about stellar contamination, and this observed starspot spectrum provides a unique benchmark to test future starspot models. For now, the near-infrared remains a safer and more reliable window for planet atmosphere studies.

Original astrobite edited by Natalie Price.

About the author, Elise Koo:

I’m a PhD student at the University of Amsterdam, working to detect magnetic interactions between stars and their planets using radio and spectroscopic observations. Outside of research, I like to try out a variety of sports.

Earth in visible and near-infrared light

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: Retrieving the Red Edge on Earth-Like Planets with Heterogeneous Clouds and Surfaces
Authors: Zachary Burr et al.
First Author’s Institution: Jet Propulsion Laboratory; ETH Zurich
Status: Published in ApJ

In the next 25 years, astronomers could find signs of life on other planets with the launch of the Habitable Worlds Observatory. Atmospheric signs of life, known as atmospheric biosignatures, are how astronomers currently search for life on other planets. Figure 1 shows examples of atmospheric biosignatures with pictures of each chemical’s origin on Earth. Before E.T. can phone home, though, we have to understand what chemicals make up a planet’s atmosphere. To do this, astronomers can use spectroscopy to observe a planet’s atmosphere in different wavelengths and measure the types and quantities of chemicals present.

biosignatures in Earth's atmosphere

Figure 1: Atmospheric biosignatures present in Earth’s atmosphere. More abundant biosignatures include oxygen and ozone (byproducts of photosynthesis in plants and bacteria) and nitrous oxide (byproduct of bacteria that don’t need oxygen to survive). Less abundant biosignatures include isoprene (released from the breakdown of leaves that have fallen from trees) and sulfur gases (byproducts of cyanobacteria). [Kaz Gary]

There are many ways to observe the spectrum of a planet, but the one you’re probably most familiar with is transmission spectroscopy. You can learn more about transmission spectroscopy of exoplanet atmospheres and how to model transmission spectra with these bites: 1, 2, 3. However, all of the current techniques for exoplanet spectroscopy (including transmission spectroscopy) measure the star’s light and how the planet affects the star’s light. This means it’s heavily dependent on how we model the star’s light to indirectly observe the planet’s light. The only way to take the spectrum of a planet directly is with direct imaging: the technique that the future Habitable Worlds Observatory will use to find signs of life in planetary spectra.

But are atmospheric biosignatures the only way to tell if life exists on other planets? Short answer: absolutely not. Let’s take Earth as an example. If we imagine Earth as a directly imaged exoplanet and take spectra of the light it reflects, you’ll find that around near-infrared wavelengths (~700 nanometers or just past the red part of the visible light spectrum), the light reflected off of Earth increases sharply. This sharp increase is called the vegetation red edge and is caused by plant and ocean life on Earth’s surface as shown in Figure 2. This is made possible because chlorophyll (the thing that makes plants green) absorbs nearly all visible light but reflects near-infrared light. The vegetation red edge is an example of a surface biosignature. In today’s article, the authors determine if the vegetation red edge will be visible in spectra of Earth-like exoplanets!

Spectra of different sources of the vegetation red edge

Figure 2: Spectra of different sources of the vegetation red edge on Earth. The vegetation red edge is highlighted in gray where the spectra rapidly increase and then level off beyond the visible light part of the spectrum. Each color represents a different source with pictures of each source on the right-hand side of the plot. [O’Malley-James and Kaltenegger 2019]

Snapshots

Planets rotate; that’s how we have morning, noon, and night in 24 hours guaranteed. This means that different parts of the surface will be visible at different times when we take spectra. Sometimes, we may see more ocean than land, other times not. To determine if the vegetation red edge would be visible at all points in Earth’s day, the authors simulated nine different spectra of modern-day Earth representing nine snapshots of Earth’s rotation. Additionally, they also simulated a time-averaged spectrum that shows an entire Earth day in one snapshot without the time variability. These spectra are shown in Figure 3.

Spectra of a directly imaged modern-day Earth at nine different times in its rotation

Figure 3: Spectra of a directly imaged modern-day Earth at nine different times in its rotation. The y-axis is the ratio of the planet’s signal to the star’s signal and the x-axis is wavelength in microns. Each color represents a time in UTC and the black curve represents the time-averaged spectrum. [Burr et al. 2026]

The authors then run retrieval models on all nine spectra to see if the vegetation red edge would be detectable in each spectrum, including the time-averaged one. Retrieval models take into account characteristics of the planet that would affect how light moves through its atmosphere, such as the atmospheric chemicals present and the surface gravity. They then use this information to generate possible spectral models that could fit the data. The best-fit model allows astronomers to infer what the atmosphere is made of and properties of the planet such as surface gravity. Because we are looking at Earth in visible light, much of the light from the planet is reflected. Typically, models of Earth-like planets in visible wavelengths only include atmospheric albedo: the measure of how reflective a planet’s atmosphere is. However, surface biosignatures can also be reflective as shown by the vegetation red edge. The authors use this to their advantage and introduce a surface albedo into their model that changes with the amount of desert, vegetation, and ocean visible on Earth’s surface at that time. They then further divide the nine spectra into three different types based upon the visible surface: majority land; 50% land, 50% ocean; and majority ocean. Check out the article online to see a cool animation of the Earth rotating and how the spectrum looks different at each time!

Arr! There Be… Vegetables?

After running the models, the authors were able to detect a sharp increase in the surface albedo value in every spectrum, including the time-averaged one. This result is shown in Figure 4. The authors take this result one step further in order to validate that the vegetation red edge is actually a result of surface variation of vegetation. They re-run models on each of their spectra but instead include a constant surface albedo instead of a time-varying one. This resulted in incorrectly measured radii, chemicals, and surface gravity in nearly all of the models. Without the vegetation red edge and surface features, the models could not accurately determine if life was present on Earth.

Retrieved surface albedos for the nine time-varying spectra

Figure 4: Retrieved surface albedos for the nine time-varying spectra. The surface albedo is broken down into three different values (a₁, a₂, a₃). Each of these values represents a change in the surface albedo at different wavelengths (i.e., how reflective the surface is at three different wavelengths). The nine spectra were broken down by the amount of surface that was visible at that time and color-coded for each category. The time-averaged spectrum is shown in gray. Each category of spectra was able to retrieve an increase in reflected light from the surface at vegetation red edge wavelengths. The spectra that had the majority land visible have the biggest increase in the surface albedo. This makes sense since the amount of visible vegetation is the largest with majority-land planets. [Burr et al. 2026]

For the first time (to the author’s knowledge), the vegetation red edge has been shown to be a promising and observable biosignature in Earth-like atmospheres. This study has also laid the groundwork for future work on other surface biosignatures and their potential impact on spectra of habitable planets. Confirming signs of life in multiple different ways, both on the surface and in the atmosphere, will finally allow astronomers to say we are not alone in the universe. In fact, life likes to live on the (red) edge!

Original astrobite edited by Madison VanWyngarden.

About the author, Kaz Gary:

I am a fourth-year PhD candidate at The Ohio State University with a passion for planets. My current work focuses on modeling exoplanet observations for the Habitable Worlds Observatory and understanding planetary atmospheres. Outside of research, I help develop planetarium shows and love all forms of science communication. In my free time, I enjoy playing tabletop RPGs, painting, watching terrible reality TV, and hanging out with my pet hedgehog.

NGC 4151

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: Shocks, Winds, and a Torus: The Large Binocular Telescope Interferometer (LBTI) Resolves the Active Nucleus of NGC 4151
Authors: Jacob W. Isbell et al.
First Author’s Institution: University of Arizona
Status: Published in ApJ

At the centre of nearly every galaxy lies a supermassive black hole that dominates this innermost region. Not only is there this millions-of-solar-masses dark beast, but usually too a whole bunch of stuff — stars, gas, dust, and more — which is often quite bright! When there is plenty of this material quite close to the black hole, we believe physics takes control to flatten it into a family of disk and toroidal structures in what we call the unified model of active galactic nuclei (AGNs; see Figure 1).

schematic of the unified model of active galactic nuclei

Figure 1: The unified model of AGNs asserts that there is an inner accretion disk, surrounded by a dusty torus that cohabitates with clouds moving at different velocities (the so-called broad and narrow line regions), and sometimes even relativistic jets extending from the accretion disk to galactic scales; you can read more about AGN structure in this Astrobites guide. [Emma Alexander; CC BY 4.0]

When astronomers look at different active galaxies (read: galaxies with active supermassive black holes at their core), we see a range of phenomenologies related to their brightness, spectra, morphologies, and more. The unified model of AGNs seeks to explain these different AGN appearances simultaneously by positing that they all have the same physical structure, and we are just viewing them from different angles, hence seeing different features.

The cores of AGNs are often imaged at the smallest scales (e.g., their accretion disks, viewed with interferometers like the Very Large Telescope Interferometer) and the largest scales (e.g., their relativistic jets, viewed with radio interferometers), but comparatively less effort has gone to directly observing the predicted dusty tori in the mid-infrared. That is exactly what today’s authors set out to do using the Large Binocular Telescope Interferometer (LBTI) — a pair of 8.4-metre-aperture mirrors separated by just over 14 metres and combined to simulate a telescope effectively 29 metres wide. This lets astronomers take direct images at a much higher resolution than a smaller-aperture telescope, and hence directly peer into the region around AGNs where this dusty torus should lie.

Today’s authors turn the LBTI towards NGC 4151, a medium-luminosity AGN. With the large effective aperture of the LBTI, they were able to resolve scales in the AGN region as small as 4.4–9.1 pc, about 14–30 light-years depending on the wavelength (see Figure 2), in the mid-infrared. These observations revealed warm dust emission in a complex structure around the central supermassive black hole. The authors note a central bar at all wavelengths, with a significant extension of cool dust arcing to the west (right in the image) and warmer dust localised to the centre (as evident by 3.7- and 4.8-micron emission only nearest to the supermassive black hole and its accretion disk).

deconvolved images of the AGN core of NGC 4151

Figure 2: The deconvolved images of the AGN core of NGC 4151 show a very bright central source (the innermost region around the supermassive black hole), as well as some complex surrounding structure particularly at long wavelengths. The interpreted morphology is described in Figure 3. These images are deconvolved, meaning that known optical effects are corrected for on the raw data to produce a sharper image. [Adapted from Isbell et al. 2026]

To explain the observed morphology in Figure 1, the authors compare three different interpretations based on this new high-resolution imagery together with the results of previous studies looking at other scales and the spectrum of the AGN core. Each interpretation is illustrated and briefed in Figure 3.

illustration of the different regions surrounding NGC 4151's black hole and potential interpretations for the observed morphology

Figure 3: Three interpretations of the observed morphology are presented by the authors. The left panel illustrates the different regions surrounding the supermassive black hole (together with the results of other studies cited in the article). The right panel shows the suggested interpretations explaining the morphology. [Isbell et al. 2026]

The first interpretation is in keeping with the unified model of AGNs: a geometrically and optically thick torus of dust surrounds the inner region. In this interpretation, the surface of the dusty torus re-radiates light from the accretion disk to produce most of the mid-infrared emission. Additional mid-infrared emission could come from localised concentrations of gas or interactions between the outflow and the jet. The authors immediately disfavour this explanation, as other studies have shown bright ionised emission at the location of the would-be torus, which is not expected if an optically thick torus were to be present. Hence, these new observations somewhat challenge the one “flavour” of the unified model of AGNs.

The second interpretation aligns with a different version of the unified model: one in which a geometrically thin disk replaces a thick torus around the AGN core. Provided the disk is optically thin too, the authors favour this approach as it is consistent with the geometry of ionised emission that worked against the first interpretation. While other studies suggest that this thin disk should be optically thick, this morphology is at least better aligned with what we see in other AGNs.

The third interpretation suggests that the emission comes from only the radiation pressure–driven wind emanating from the AGN core. The authors disfavour this explanation, citing previous radiative transfer simulations that show that the flux should fall off with distance from the core too quickly to be consistent with the observations.

No matter the interpretation, these LBTI observations are an important glimpse into the future of mid-infrared AGN studies that will be done with 30-metre-class telescopes (such as the European Southern Observatory’s Extremely Large Telescope). This article, together with the group’s similar study on NGC 1068, is challenging and refining an accepted view of AGN morphology — the consequences of which apply to galaxies near and far — and poses new questions perfect for sophisticated hydrodynamic and radiative simulations.

Original astrobite edited by Margaret Verrico.

About the author, Ryan White:

I am a first-year PhD student at Macquarie University in Australia, working mainly on binary/multiple systems with massive stars (Wolf–Rayets in particular!). Outside of study, I’m probably drinking coffee, baking, reading, or going for a run. You can also find me procrastinating on Bluesky @astroryan.bsky.social.

illustration of an exoplanet and exomoon around a star

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: A Deep Search for Exomoons Around WISE 0855 with JWST
Authors: Mikayla J. Wilson et al.
First Author’s Institution: University of California, Santa Cruz
Status: Published in AJ

The “Moon”-umental Question

The solar system hosts hundreds of moons, ranging from volcanic worlds like Io around Jupiter, to icy objects like Enceladus around Saturn, to captured objects like Neptune’s retrograde moon Triton. Moons are essential to our model of how the solar system formed and also offer some of the best chances we have for finding life beyond Earth.

Astronomers also expect exomoons, or moons orbiting planets outside the solar system, to be abundant around other giant exoplanets. But how common are exomoons? How do they compare to the moons in our solar system?

In order to begin answering those questions, we must first detect an exomoon, which has proved difficult despite decades of searching by astronomers. Fortunately, JWST presents a new opportunity to uncover the exomoon population by looking at lonely free-floating planets as they drift through space.

Why Free-Floating Planets?

One proposed method for searching for exomoons is by looking for their transits in front of their host planets, characterized by the dips in brightness of the planet as the moon passes in front, blocking the planet’s light. Looking for exomoon transits around planets orbiting stars is quite difficult, as the bright starlight can easily drown out the small signals of exomoon transits. Free-floating planets solve this issue by removing the star entirely, increasing our sensitivity to such detections. (See this bite for a good review.)

The authors of today’s article directed the exomoon hunt towards the free-floating WISE J085510.83-071442.5 (or WISE 0855). It has the prestige of being the coldest known brown dwarf (250–285K) while also sitting at a relatively low mass (3–10 Jupiter masses). Notably, it is also one of our closest neighbors at a distance of only 7.4 light-years, making it ideal for high-precision observations despite its faintness. Even though brown dwarfs are technically distinct from planets, the authors opt to refer to companions around WISE 0855 as moons given WISE 0855’s “planetary-mass” status. (It’s complicated…)

Repurposing JWST Data… for Moons!

The JWST observations used in this study contain 11 hours of near-infrared (2.87–5.27 microns) time-series spectra originally intended to study water clouds and weather on WISE 0855. Time-series brightness monitoring can also be used for transit searches, which the authors take advantage of.

One complication is that WISE 0855 is variable, meaning its intrinsic brightness changes over time. Variability is likely driven by clouds and other dynamic processes within its atmosphere. So how do the authors distinguish between a passing moon and a turbulent atmosphere? The key idea is that variability is wavelength dependent, meaning that the brightness of WISE 0855 will fluctuate differently depending on the observed wavelength. In contrast, transits are “gray,” meaning that the same amount of light is blocked at all wavelengths, producing a consistent feature across the entire spectrum.

Finding Moons with Statistics!

The authors apply this idea and pick out two wavelength regions of WISE 0855’s spectrum that contain two distinct variability patterns, which should both contain an identical moon transit signal (if present). They then generate a light curve (how brightness changes over time) for these two regions (see Fig. 1).

WISE 0855 light curves

Figure 1: (A) Light curves from two selected wavelength regions of WISE 0855’s spectrum with injected transit signals. Also plotted is the best-fit Gaussian processes + transit model for the two light curves. (B) Light curve data after subtracting the Gaussian processes portion of the best-fit model, revealing the example injected transit signals. [Wilson et al. 2025]

To appropriately model the variability, the authors employ Gaussian processes, a flexible tool that can model complex, quasi-periodic signals like atmospheric variability. They compare fits from two types of models:

  • Gaussian processes–only model: Assumes that all observed variability is intrinsic to the planet itself
  • Gaussian processes + transit model: Includes a simple trapezoidal exomoon transit signal that is simultaneously fit in both light curves

Using Bayesian evidence (a measure of how well each model explains the data), they determined which model was favored. So, what do they find?

The Bad News and the Good News

Based on Bayesian evidence, the authors conclude that there are no statistically significant detections of exomoons in the data. The results suggest very weak evidence for a ~0.53-Earth-radius moon at a wide separation from WISE 0855 — an unlikely scenario given that transit probability decreases at greater separations (and therefore longer orbital periods).

Yet, the study goes further: What kinds of moons is JWST able to detect, if any? To answer this, the authors performed injection and recovery tests, where they injected artificial transit signals of varying depths (exomoon sizes) into the data and tested how well their models were able to recover them (results shown in Fig. 2). They find that JWST is capable of detecting 96% of transits with depths ≥0.5%, equivalent to a Titan-like moon. Smaller Io-like moons were also detectable more than half of the time. This means that if a Titan analog had actually transited during these observations, we would almost certainly have seen it!

plot of successful detections of injected transit signals

Figure 2: Results showing the number of successful detections for the transit injection and recovery tests. Fifty transit injections are done for transit depths of 1%, 0.5%, 0.4%, 0.3%, 0.2%, and 0.1%. The transit depths represent different exomoon sizes, with the shaded regions representing Io-like and Titan-like moons. [Wilson et al. 2025]

JWST will continue to gather more time-series data of free-floating planets, brown dwarfs, and directly imaged exoplanets, each providing a new opportunity to help us better understand the moon population outside of our solar system. We’re still waiting for the first confirmed exomoon, but when that transit finally happens, we know that JWST will be ready.

Original astrobite edited by Kelsie Taylor.

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.

galaxy cluster MACS J1149.5+2223

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: Metal-Poor Star-Forming Clumps in Cosmic Noon Galaxies: Evidence for Gas Inflow and Chemical Dilution Using JWST NIRISS
Authors: Vicente Estrada-Carpenter et al.
First Author’s Institution: Arizona State University
Status: Published in ApJ

If you want to reconstruct a galaxy’s life story, one of the best “fossil records” is its metallicity. In astronomy this refers to the abundance of elements heavier than helium, which are made in stars and returned to a galaxy’s gas through winds and supernovae. Over time, more star formation usually means more metals mixed into the gas.

Now zoom to Cosmic Noon (roughly when the universe was most actively forming stars). Many galaxies in this epoch look “clumpy”; their star formation is concentrated in several bright knots scattered across the disk. The big question is where those clumps come from. Do they form from the galaxy’s own gas via internal disk instabilities, or do they light up when fresh, metal-poor gas flows in and both fuels star formation and dilutes the local metallicity?

The authors try to answer that question with JWST by measuring the metallicity of each clump relative to its immediate surroundings, rather than comparing clumps to a single galaxy-wide number (which can be misleading if the galaxy has a metallicity gradient).

They use JWST/Near Infrared Imager and Slitless Spectrograph (NIRISS) slitless grism spectroscopy from the CAnadian NIRISS Unbiased Cluster Survey (CANUCS) to study 20 lensed galaxies at redshift 0.6 < z < 1.35. (Lensing effectively acts like a zoom lens, helping to resolve smaller structures.) They focus on emission lines that trace star-forming gas, especially Hα (a star formation tracer) and sulfur lines [SII] and [SIII] (needed for their metallicity method).

Slitless spectra come with a headache: because there is no slit, different parts of a galaxy can overlap in the dispersed image. To make reliable emission-line maps from slitless data, the authors use a forward-modeling code called Sleuth, which allows the continuum to vary across the galaxy.

The authors identify clumps using the Hα map together with rest-frame ultraviolet imaging because these tracers are sensitive to star formation on different timescales: Hα highlights gas ionized by the youngest massive stars, while ultraviolet light traces young stellar light over longer periods. As a result a clump can be bright in one and not the other, especially if dust is involved.

To estimate gas-phase metallicity, they use the “strong-line” method, which infers metallicity from ratios of bright emission lines calibrated using models and empirical samples. Their main diagnostic is S23 = ([SIII] + [SII]) / Hα. Because some line ratios also depend on the ionization state (how strongly the gas is being ionized by young stars), they also use the sulfur ratio S32 = [SIII]/[SII] as a check and iterate to a self-consistent solution.

So, Are Clumps Really Chemically Different from Their Surroundings?

For each clump, the authors measure the metallicity inside the clump and compare it to an annulus just outside the clump (masking neighboring clumps to avoid mixing). When they plot “clump metallicity” versus “local disk metallicity,” most points fall below the 1-to-1 line, meaning the clumps are more metal poor than their surroundings (Figure 1). The mean offset is about 0.1 dex, which corresponds to roughly 20% dilution in the clump gas.

plot of gas-phase metallicity in star-forming clumps compared against metallicity of nearby disk regions

Figure 1: Each point compares a star-forming clump’s gas-phase metallicity to the metallicity of the nearby disk region immediately surrounding it. If clumps and disks had the same metallicity, they would lie on the dashed 1-to-1 line. Instead, most clumps sit below it, showing a typical ∼0.1 dex metallicity deficit, consistent with local chemical dilution. (The solid red line shows a best-fit linear trend to the clump measurement.) [Adapted from Estrada-Carpenter et al. 2025]

An extra wrinkle is that the galaxy medians hint at two populations: some galaxies have clumps with small offsets (near the 1-to-1 line), while others show larger offsets. The authors suggest this could mean two formation pathways, one dominated by internal gas reservoirs (smaller offsets) and another where inflow of metal-poor gas plays a bigger role (larger offsets). They are careful, though, as the sample is still small.

If inflow is really the driver, you should expect a link: the more strongly a clump is forming stars relative to its surroundings, the more diluted its metallicity should be. That is exactly what the authors find. The clumps that are most boosted in star formation are also the most metal diluted.

The article also emphasizes that clumps are not chemically uniform blobs. In at least one detailed example, the peaks in Hα (highest star formation) coincide with local minima in metallicity along a cut through the galaxy (Figure 2), suggesting internal star formation rate and metallicity gradients that reinforce the same story, intense star formation goes hand in hand with lower metallicity in the clump regions.

galaxy image showing spatial variation of H alpha and metallicity

Figure 2: Example galaxy from this study illustrating the clump-scale link between star formation and metallicity. The color image shows the galaxy with a rectangular strip marking the region used for a 1D cut. In the bottom panel, the turquoise line shows the Hα flux (a tracer of recent star formation), while the white line shows the metallicity along the same cut. Peaks in Hα flux line up with local dips in metallicity, showing that the brightest star-forming clumps are also the most chemically diluted compared to nearby regions. [Adapted from Estrada-Carpenter et al. 2025]

Are These Clumps Really “In Situ,” or Could They Be Small Satellites?

A reasonable alternative is that some clumps are actually small companion galaxies projected onto the disk. These could also look metal poor, because low-mass galaxies tend to be low metallicity. The authors look for evidence using face-on systems and find that more massive clumps tend to sit closer to galaxy centers, which is consistent with in-situ clumps that form in the disk and migrate inward, though it does not rule out satellites. They argue that kinematics from JWST/NIRSpec IFU will be needed for a definitive separation.

Why This Matters

Gas inflow, star formation, and feedback, together known as the baryon cycle, are key drivers of how galaxies grow. What this article adds is a spatially resolved view that compares each clump to its local environment, showing that regions of elevated star formation also tend to be locally metal poor. That pairing is hard to explain as a simple metallicity gradient or a galaxy-wide averaging effect, and it is exactly what you would expect if at least some clumps are being fueled by relatively metal-poor inflows. In short, these clumps may be snapshots of galaxies refueling in real time.

Original astrobite edited by Ryan White.

About the author, Niloofar Sharei:

I’m an astronomy PhD candidate at UC Riverside studying how galaxies grow through star-forming clumps. I track how these clumps emerge, evolve, and sometimes survive long enough to reshape their galaxies. When I’m not thinking about cosmic blobs, I’m reading, hiking, or listening to Bach.

illustration of stars in the early universe

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: Hunting for the First Explosions at the High-Redshift Frontier
Authors: Junehyoung Jeon et al.
First Author’s Institution: The University of Texas at Austin
Status: Published in ApJ

Back in the 1920s, astronomers discovered that we live within just one of many, many galaxies in the big, wide universe. Since then, we’ve been racing to search for the most distant galaxy that can be observed — in other words, searching for the oldest starlight we can see, since the light from these distant sources has been travelling towards us for most of the age of the universe. (Remember: more distant = higher redshift = longer lookback time.)

This race to the redshift frontier has had a pretty eventful history (see a great overview video here), which became even more eventful with the launch of JWST. JWST rapidly smashed the previous redshift (z) record of z = 10.6 by discovering a galaxy at z = 13.2, and then it broke its own record twice more. The current title holder sits at z = 14.4, observed less than 300 million years after the Big Bang.

Several galaxy candidates (to date unconfirmed) have now even been proposed at z ~ 25–32 (e.g., Capotauro), only 100 million years after the Big Bang! If real, these sources would pose a serious challenge to our understanding of the formation of the first galaxies, as galaxies shouldn’t really be observable at such early times. In today’s article, the authors put forward an intriguing alternative: what if some of these ultra-high-redshift candidates aren’t galaxies at all, but transient explosions from the universe’s first stars?

The First Stars and Their Explosive Endings

The earliest generation of stars (Population III; see my previous bite on these here) formed from pristine hydrogen and helium gas. Without metals to cool the gas efficiently, theory predicts that these stars were extremely massive, often exceeding 100 solar masses. While such stars would be short-lived, their deaths could be spectacular.

Population III stars of sufficient mass are predicted to end their lives as hyper-energetic pair-instability supernovae (PISNe). This is a long-winded name for a rapid, intensely hot explosion that leaves no remnant behind — not even a trace of the pre-existing star. Whilst nothing would remain of the star, the light emitted in that explosion could be bright enough to masquerade as a high-redshift galaxy candidate in current JWST surveys, but only if three key conditions are met:

  1. JWST must observe a sufficiently overdense region, where lots of Population III stars can form very early.
  2. A PISN must occur while JWST is “watching.”
  3. The explosion must be bright enough to rise above JWST’s detection limits.

Simulating a (Biased) Universe

To address the likelihood of these conditions having already been met by existing JWST observations, the authors turn to cosmological simulations. Rather than simulating an “average” patch of the universe, they focus on an extremely overdense region (Fig. 1). This creates a rare but important environment where structures collapse earlier than usual. These regions are exactly where large numbers of Population III stars are expected to form at the highest redshifts.

projection of the gas density in the simulated overdense region at z = 30.4

Figure 1: A projection of the gas density in the simulated overdense region at z = 30.4. The densest structures stand out clearly, tracing the locations where the first stars are able to form. Black dots mark newly formed groups of stars, while the most massive dark matter halo in the region is highlighted with an orange circle. The figure illustrates that in such an unusually dense patch of the early universe, star formation can already be underway just 100 million years after the Big Bang, creating the conditions needed for early Population III stars and their explosive deaths. [Adapted from Jeon et al. 2026]

In their simulations, star formation begins as early as z ~ 30–40 (within the first hundred million years after the Big Bang), producing Population III stars and, by extension, potential PISNe very shortly afterwards. While such overdense regions are rare, the authors show that the total area already surveyed by JWST (including large surveys such as CEERS, JADES, PRIMER, and COSMOS-Web) is large enough that it is plausible JWST has already observed at least one such region.

Catching a Cosmic Explosion in the Act

So, we can tick off condition #1: it’s possible that a sufficiently overdense region has already been observed by JWST. Next up, how lucky do we have to be to catch an explosion in the act (condition #2), so to speak? For this condition, cosmic time dilation actually works in our favour. A PISN explosion at z > 20 that lasts only months in its own rest frame can last for decades in the observed frame. (This whole time-being-relative thing sounds wacky because it is — please join me, Neil deGrasse Tyson, and countless others in struggling to imagine this.)

But would any such explosion be bright enough (condition #3)? Using theoretical PISN spectra, the authors show that these explosions could reach observed magnitudes of ~28–29 at z ~ 30 — right at the depth of current JWST deep surveys (Fig. 2). In fact, the predicted brightness and colours are somewhat comparable to those of some proposed z ~ 30 candidates (Fig. 3), raising the possibility that these objects could be PISNe rather than galaxies.

plot of predicted PISN brightness

Figure 2: This plot compares the predicted brightness of PISNe originating from different types of extremely massive stars to the depth reached by existing JWST surveys, showing that these explosions could remain detectable for ~20 years at peak brightness in the observed frame. [Jeon et al. 2026]

Theoretical PISNe spectra compared to a proposed z = 32 source

Figure 3: A comparison of theoretical PISNe spectra with the observed photometry of one proposed z ≈ 32 source (Capotauro). The coloured curves show model spectra for PISNe originating from extremely massive stars, at different stages of the explosion, while the data points represent the observed brightness of the high-redshift candidate across multiple JWST filters. [Jeon et al. 2026]

So… Are We Seeing the First Stars Die?

It’s not time to throw a party just yet. The authors note there are several caveats and uncertainties. The nature of Population III stars is still highly uncertain, JWST does not continuously monitor the same patch of sky, and identifying a PISN at such high redshift would be extremely challenging. Thanks to time dilation, these explosions would fade very slowly, making them hard to distinguish from steady sources using photometry alone. Alternatively, there are other plausible explanations for these ultra-high-redshift candidates: lower-redshift interlopers (a rather infamous example is CEERS-93316), local brown dwarfs, or even nearby exoplanets.

Still, the idea is exciting. If JWST were to detect a genuine PISN at z > 20, it would represent a direct glimpse of the very first stars, pushing observational astronomy into truly uncharted territory. For now, the most distant explosions in the universe may already be hiding in JWST images; we just have to learn how to recognise them.

Original astrobite edited by Nathalie Korhonen Cuestas.

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!

Population III stars

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: GLIMPSE: An Ultrafaint ≃105 M⊙ Pop III Galaxy Candidate and First Constraints on the Pop III UV Luminosity Function at z ≃ 6–7
Authors: Seiji Fujimoto et al.
First Author’s Institution: University of Toronto; The University of Texas at Austin
Status: Published in ApJ

You, me, your laptop, my $8 matcha, and just about everything else on Earth was forged in the fiery bellies of dying stars. Generations of stars had to live and die before the universe became enriched with any elements heavier than helium (what astronomers call “metals”). The first stars to undergo this cosmic cycle are known as Population III (Pop III) stars. Though their existence has been hypothesized since the 1960s, astronomers have failed to observe these distant metal-free stars or the faint, low-mass galaxies that host them.

The first Pop III stars likely formed around 100 million years after the Big Bang in pristine pockets of hydrogen gas. Although these are too distant for us to observe, we expect that as the universe started to become metal enriched, there were still existing pockets of gas introverted enough to survive unpolluted and form metal-free Pop III stars up to a redshift of z ~ 6–7 (when the universe was around 900 million years old)!

JWST is the perfect instrument to search for these systems. You can read other astrobites on the search for possible Pop III systems with JWST here and here. The authors of today’s article seek to develop the most efficient way of using JWST’s Near-Infrared Camera (NIRCam) to find the galaxies hosting Pop III stars. Using their selection method on existing NIRCam data, the authors identified one promising Pop III galaxy candidate.

I’m Not Like Other Galaxies

In order to find a Pop III galaxy, we need to take a look at galaxies’ spectral energy distributions (SEDs). These are graphs that show the energy emitted by a galaxy at different wavelengths of light. Pop III galaxies are expected to have SEDs that differ from your everyday, metal-enriched galaxy. NIRCam will be especially sensitive to three key spectral features that show up in the SEDs of Pop III galaxies: an absent [O III] line (light emitted by doubly ionized oxygen atoms), a strong H-alpha line (light emitted when a hydrogen atom transitions from its third to its second energy level), and a significant Balmer jump (light absorbed to ionize electrons in the second energy level of a hydrogen atom). To identify these key SED characteristics, the authors use SED fitting and color–color diagrams to execute an efficient Pop III search with NIRCam.

The first selection method involves SED fitting. Astronomers create template SEDs that represent different types of galaxies and then compare these templates to the observed SEDs to see which one matches best. In this work, the authors use metal-rich galaxy templates and Pop III templates to fit the galaxies observed with NIRCam. They then calculate the chi-squared χ2 (a statistical measure of best fit) between the data and all the SED templates. A galaxy is selected as a Pop III candidate if the Pop III model provides a good fit (χ2 < 10) to the photometry and is significantly better than any metal-rich model. It’s kind of like looking for Cinderella by making every woman in the kingdom try on the glass slipper.

A color-color diagram showing how Pop III models lie in a different parameter space than metal-rich galaxies.

Figure 1: Color–color diagram for selecting Pop III galaxies where the x and y-axes show the different NIRCam filters being subtracted. The cyan symbols are different Pop III models while the other colored dots are different metal-rich galaxy models. [Adapted from Fujimoto et al. 2025]

A color–color diagram plots the difference in magnitude between two filters on each axis. NIRCam filters are specially chosen to emphasize the SED characteristics above. When these filters are chosen, Pop III galaxies occupy a distinct region of this diagram as compared to metal-rich galaxies. For example, subtracting the F356W filter from the F277W filter is sensitive to the presence of the [O III] line and the Balmer jump. Figure 1 demonstrates how this color selection separates Pop III galaxies from typical galaxies.

O Pop III, Pop III, Wherefore Art Thou?

The authors apply their fresh new selection criteria to publicly available NIRCam data from large surveys. And (drum roll please) the slipper fits! The Pop III galaxy candidate GLIMPSE-16043 is an ultra-faint galaxy at z = 6.5. It was imaged in the GLIMPSE survey, which uses the technique of gravitational lensing to observe faint and distant galaxies.

The GLIMPSE survey targeted a massive galaxy cluster, Abell S1063. The cluster bends the light from distant galaxies and, like a giant lens, magnifies faraway objects, providing some of the deepest JWST imaging to date. The Pop III candidate passes both tests: it resides in the Pop III region of the color–color diagram, and its SED is best fit by a Pop III model, not a metal-rich galaxy model (see Figure 2). Next, spectroscopic follow-up is needed to ensure that this galaxy is truly metal free and not just extremely metal poor.

The spectral energy distribution of a Pop III galaxy candidate. This plot shows that the JWST data is best fit by a Pop III model rather than a metal-rich galaxy.

Figure 2: SED of GLIMPSE-16043 with the best-fit Pop III template (blue) and best-fit metal-enriched template (gray). The top panel is the galaxy imaged in different filters from NIRCam and the Hubble Space Telescope. [Fujimoto et al. 2025]

The authors conclude that our best shot at identifying additional Pop III galaxy candidates is using NIRCam to image large numbers of gravitationally lensed clusters. Without magnification from gravitational lensing, it may be impossible to see these ultra-faint Pop III galaxies. Once candidates have been identified, they can be followed up with deep spectroscopy to confirm their redshift and their lack of metals. Who knows? With these new methods, we may soon get a glimpse of the universe’s very first stars.

Original astrobite edited by Chris Layden and Margaret Verrico.

About the author, Madison VanWyngarden:

I am a first-year PhD student in astronomy and NSF Graduate Research Fellow at the University of Arizona. I study galaxy formation and evolution in the distant universe and am particularly interested in dusty star-forming galaxies. In my free time, I love reading, hiking, and baking bread!

galaxy transitioning from star forming to quiescent

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: Searching Within Galaxies for the Earliest Signs of Quenching With Spatially Resolved Star Formation Histories in UVCANDELS
Authors: Charlotte Olsen et al.
First Author’s Institution: New York City College of Technology
Status: Published in ApJ

How and Why Do Galaxies Stop Forming Stars?

Galaxies serve as important laboratories for many subfields of astrophysics. As such, astrophysicists are interested in the full galactic life cycle, from how galaxies are born to the end of their formation. Whereas young galaxies in the distant universe are actively forming stars, many nearby galaxies are much quieter, with little or no ongoing star formation. Astronomers like to describe these galaxies as “red and dead” because their stars are older and therefore appear redder in color. The process by which galaxies shut down their star formation is known as quenching, and it causes galaxies to become quiescent. Understanding the origin of quiescent galaxies is a fundamental question in galaxy evolution. Studying this process is challenging, however, because star formation is intertwined with many other factors that shape galaxies, including their environments and supermassive black holes.

Star formation occurs on scales that are much smaller and over timescales much shorter than the global properties and overall lifetime of a galaxy. By observing star formation on these smaller scales over time, astronomers can gain a clearer picture of how star formation ceases in a galaxy, and they can determine whether this process is driven from the inside out — starting with the supermassive black hole in the galactic center — or from the outside in, influenced by environmental effects. In today’s article, the authors use the Cosmic Assembly Near-Infrared Deep Extragalactic Legacy Survey with high-resolution ultraviolet coverage (UVCANDELS) to examine eight “golden” galaxies, shown in Figure 1. They then reconstruct the star formation histories within small regions of each galaxy to detect the “earliest signs of quenching.”

galaxy sample from Olsen et al.

Figure 1: Images of the eight galaxies in the “Golden Sample” of galaxies studied in this work (right). These galaxies were chosen because of their clear detection, and they show a range of edge-on to face-on views as well as shapes. The authors divided each galaxy into small, resolved regions in which they measured the star formation (example shown on left). [Adapted from Olsen et al. 2026]

Characterizing the Star Formation Histories

To trace a galaxy’s star formation over cosmic time, today’s authors model its integrated light — which encodes the many episodes of past star formation — using spectral energy distribution (SED) fitting. By comparing a galaxy’s light across many wavelengths to computer models, SED fitting can estimate the ages of its stars and when they formed. This approach allows astronomers to study how a galaxy’s star formation rate evolves as a function of its stellar mass, known as the SFR – Mstellar relation. Note that the article considers the star formation rate and stellar mass in individual regions of each galaxy, so it analyzes these properties as surface densities, ΣSFR and ΣMstellar, instead of the total values.

Using SED fitting, the authors determine the expected star formation rate and stellar mass of the regions from 250 million to 1 billion years before the time of observation. Figure 2 shows the line of best fit for the SFR – Mstellar relation of the regions for each galaxy, before and at the time of observation. The SFR – Mstellar relations are very similar across the sample 1 billion years before the observations; however, by the time of observation, the overall star formation rates have decreased slightly, indicating that the galaxies are beginning to quench. They also exhibit increased variation suggesting that each galaxy is quenching in a different way.

best-fit SFR – M stellar relation

Figure 2: The best-fit SFR – Mstellar relation of the regions for each galaxy, represented by the different colored lines, 1 billion years (1 Gyr) before and at the time of observation (left and right panels, respectively). At 1 billion years before the observation, the galaxies appear to have the same relation, but their variation at the time of observation suggests that the galaxies have begun quenching in different ways. [Olsen et al. 2026]

To further probe how these galaxies are starting to quench, the authors also measure the specific star formation rate (sSFR) of the regions as a function of their distance from the center of the galaxy. The sSFR can be thought of as the rate of new star formation relative to the amount of existing stellar mass: SFR /Mstellar. Figure 3 shows three examples from the galaxies studied in this work. Once again, the star formation rates of the regions decrease over the course of 1 billion years. However, the regions where the star formation rate has declined most rapidly differ from galaxy to galaxy — ranging from the central regions to the mid-disk to the outskirts — as each galaxy is undergoing a different quenching mechanism.

specific star formation rate of the regions as a function of their distance from the center of the galaxy

Figure 3: The specific star formation rate of the regions as a function of their distance from the center for three of the galaxies in the sample. Overall, the star formation rate decreases from 1 billion years before the observation (red) to the time of observation (blue). However, the regions where the star formation decreases most significantly (indicated with the yellow boxes) vary from galaxy to galaxy. [Olsen et al. 2026]

Detecting the Earliest Signs of Quenching

It should be noted that all of the galaxies in this study are still forming stars. However, they are on the verge of having their star formation suppressed, offering valuable insight into how quenching begins and how diverse the process can be. New telescopes are pushing the boundaries of what we can observe. On one hand, JWST can capture galaxies at exceptionally high resolution; on the other, the Vera C. Rubin Observatory and the Nancy Grace Roman Space Telescope will deliver vast datasets containing billions of galaxies. Future investigations leveraging these facilities could reveal more about the physical processes that quench galaxies on small scales, shedding light on the mechanisms that drive galaxy evolution.

Original astrobite edited by Catherine Slaughter.

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.

X-ray dot

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 X-Ray Dot: Exotic Dust or a Late-Stage Little Red Dot?
Authors: Raphael E. Hviding et al.
First Author’s Institution: Max Planck Institute for Astronomy
Status: Published in ApJL

What Are Little Red Dots?

One of the most intriguing results produced by JWST was the serendipitous discovery of a new class of object: “little red dots” (LRDs). These objects started popping up everywhere in our early universe observations. Surprisingly, they look like compact (little) red dots in imaging data (astronomers are an incredibly creative bunch). The number of LRDs we observe drops drastically at redshifts less than about z = 4 (about 12 billion years ago), implying that LRDs are likely evolving into something else entirely. The luminous, compact nature of LRDs, paired with their disappearance from the cosmic stage, has continuously puzzled astronomers in recent years.

At least part of the LRD population has routinely been explained as a new class of active galactic nuclei (AGN). AGN are the central engines of many galaxies — luminous regions powered by actively accreting supermassive black holes. Recent evidence has increasingly pointed towards LRDs being a new class of AGN: black hole stars, or black holes surrounded by dense cocoons of gas. Naturally, this raises questions surrounding the placement of LRDs in our understanding of supermassive black hole and galaxy evolution across cosmic time.

A hallmark of typical AGNs is their X-ray brightness. X-rays are one of the most energetic types of electromagnetic radiation, and they are primarily produced by the most extreme astrophysical situations (think neutron star mergers). One of the key challenges in explaining the nature of LRDs has been their lack of X-ray emission. Their lack of emission in this regime is a piece of evidence pointing towards a black hole star scenario — dense gas can block the X-rays being produced by the black hole. However, the lack of LRDs in the present-day universe implies that they likely shed their cocoons at some point. Catching an LRD in the act of shedding its cocoon would thus provide an important piece of evidence surrounding their nature and evolution. Thankfully, today’s authors may have done exactly that! They report the discovery of what they call the “X-ray dot” (XRD): an LRD-like object that is also X-ray luminous at a redshift of approximately z = 3.28.

New JWST Observations of the XRD

While archival observations of the XRD with the Hubble Space Telescope, the Canada France Hawaii Telescope, the Spitzer Space Telescope, and the Chandra X-ray Observatory existed, new spectral data from JWST were needed to study the system in depth. Spectral data have a huge advantage over photometric observations when it comes to modeling the system. With a good quality spectrum, astronomers can use sophisticated modeling tools to try and pin down the physical nature of the emission we’re observing, and thus understand its intrinsic nature.

Figure 1 showcases the archival data from Hubble, Spitzer, and Chandra, along with the XRD’s spectrum from JWST (black curve, bottom panel). Photometric observations of the source indicate that it is incredibly compact (radius ≲ 250 pc, about 100 times more compact than the Milky Way) and shows similarities to LRD spectra, but with some key differences. (An example LRD spectrum is shown as the red curve in Figure 1.) The impressive X-ray luminosity of the XRD — typical of standard AGNs — is another key difference between it and standard LRDs.

A figure showing image cutouts from HST, Spitzer, and Chandra, of the XRD. The bottom panels also shows its spectrum alongside a typical LRD spectrum.

Figure 1: Top: Image cutouts from various Hubble, Spitzer, and Chandra observations of the XRD. Bottom: The spectrum of the XRD (black) shown alongside a similar LRD spectrum (red) and two quasar spectra (blue and purple), one of which has been reddened due to the presence of dust (purple). [Hviding et al. 2026]

So…What’s the Deal with the XRD?

To understand the nature of the XRD, the authors fit a variety of models describing a wide range of physical systems to the available data. Surprisingly, their best-fit models indicate that if the XRD is simply a typical AGN heavily obscured by astrophysical dust, its dust properties are drastically different from those of typical galaxies and AGN. Instead, trying to explain the system as an AGN embedded in a cocoon of gas (the black hole star model) provides better results (more aligned with observed LRDs), but it still isn’t perfect.

Notably, the emission in the ultraviolet-to-optical regime of the electromagnetic spectrum differs greatly from that of LRDs. In LRDs, this emission is indicative of a single dense gas component around the supermassive black hole, while in the XRD the authors find evidence suggestive of a patchier, less uniform distribution of gas. However, in order for this explanation to match the data, physical conditions of the model must be finely tuned, suggesting that this model may need to be refined further. These factors seem to suggest that the XRD is poorly understood in the context of our current paradigm of models describing AGNs and LRDs. The potentially patchy nature of the XRD’s gas envelope could suggest that this object is an LRD in the process of shedding its outer envelope, evolving into a typical AGN.

Regardless of its true nature, the XRD opens up new doors in our understanding of AGNs and LRDs. It provides an exciting glimpse at AGN evolution in action — a transitional fossil for early universe black holes. With a new piece of the puzzle slotted into our picture of AGN evolution, it’s only a matter of time before astronomers fully contextualize the stubbornly enigmatic LRDs.

Original astrobite edited by Ansh R. Gupta.

About the author, Drew Lapeer:

Drew is a first-year PhD student at the University of Massachusetts Amherst. They are broadly interested in the evolution of galaxies, with a focus on the impact of cosmic feedback on the galactic ecosystem. In their free time, they enjoy reading, rock climbing, hiking, and baking!

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