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illustration of DART and LICIACube spacecraft

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: High-Speed Boulders and the Debris Field in DART Ejecta
Authors: Tony L. Farnham et al.
First Author’s Institution: University of Maryland
Status: Published in PSJ

The DART Mission: A First Step in Planetary Defense

In a groundbreaking experiment, NASA’s Double Asteroid Redirection Test (DART) became the first mission to intentionally crash a spacecraft into an asteroid to test whether such an impact could change the asteroid’s path. The target was Dimorphos, a small companion orbiting a larger asteroid called Didymos, located about 11 million kilometers from Earth.

Luckily, neither Dimorphos nor Didymos was ever on any sort of collision course with anything (and they’re still not). But by impacting an object orbiting another, the effect of the collision could more easily be measured and so Dimorphos was chosen as the target. You see, the goal wasn’t destruction, but deflection. The scientists wanted to see if a spacecraft could alter an asteroid’s orbit by striking it — and if so, by how much. When DART slammed into Dimorphos at over 22,500 kilometers per hour, it successfully shortened the asteroid’s roughly 12-hour orbit by about 33 minutes. This confirmed that hitting an asteroid with a spacecraft — in this case scientifically called a kinetic impactor — could be a viable method to redirect a potentially hazardous object in space.

But the change in momentum didn’t just come from the spacecraft itself. Much of the momentum transfer came from the plume of debris — called ejecta — that blasted out from the impact site. This debris, spreading out in multiple directions, added to the total push on the asteroid. Understanding how this ejecta moved exactly is key to calculating the full effect of the impact and was one of the primary goals for the DART mission.

With this exact purpose in mind, a small companion spacecraft called LICIACube (Light Italian Cubesat for Imaging of Asteroids), released by DART two weeks before the crash, flew past moments after the collision. It snapped several images of the debris cloud, as seen in Figure 1, as it raced past. It is with a reanalysis of these images that today’s authors have managed to track a number of boulders in the ejected material.

A GIF sequence of images that show the aftermath of the DART spacecraft impact on Dimorphos

Figure 1: Animated sequence of images taken by LICIACube as it flew past Didymos and Dimorphos a few minutes after impact by the DART spacecraft. The image is centered on Didymos with the smaller Dimorphos visible for most of the flyby. Large plumes of ejected material are visible, radiating out from the impact site where a very deep crater likely formed. Video provided by the author and subsequently converted to GIF and slowed for use in this bite. [Farnham et al. 2025]

Boulders, Boulders Everywhere!

You can say that DART really made an impact — pun intended. It kicked up a lot of material as it struck Dimorphos. In some parts the ejecta plumes are dense enough to block sunlight and even cast shadows on Dimorphos. In the images, like the one seen in Figure 2, the authors were able to make out more than 100 boulders, some as big as 3.6 meters in radius. Tracking the boulders allowed them to calculate velocities and their contribution to the momentum budget. Some of the boulders were ejected at speeds up to nearly 200 kilometers per hour and carried almost as much momentum as the DART craft itself.

Boulders detected in the ejecta from Dimorphos

Figure 2: The image shows part of the ejected material from the DART impact on Dimorphos at 2 minutes and 40 seconds after impact. A number of boulders are highlighted as they are tracked through the sequence of images from the LICIACube. The boulders are not uniformly distributed but mostly clustered in two distinct populations, with the South Cluster containing around 70% of the measured objects. [Farnham et al. 2025]

Using the assumption that the objects are somewhat spherical, the authors calculate that the total volume of all 104 boulders that they managed to identify and track amounts to 403 cubic meters of material, which is equivalent to a sphere 4.6 meters in radius. If you use the bulk density of Dimorphos, this suggests that the mass ejected in these objects is around 0.02% of Dimorphos’s total mass. And this is only for the boulders tracked — the study identified more boulder, but LICIACube was not able to track all of them and could only detect sizes down to 0.2 meter!

The authors also found that the boulders are clustered, suggesting that they were ejected in preferred directions. They conclude that this non-uniform distribution likely changed Dimorphos’s orbital plane. Additionally, the momentum imparted by boulder ejection also likely altered the rotational state of the asteroid, making it tumble around in its orbit.

So what happened? Although there are no constraints on their actual points of origin, the authors suggest that a likely scenario might be that the ejected rocks are the shattered pieces of two large boulders that were seen in some of the last images from the DART spacecraft itself. The two boulders on the surface — named Bodhran and Atabaque after their drum-like shapes — were likely struck by the solar panels as seen in Figure 3.

DART impact site and possible trajectories for the ejected boulders.

Figure 3: The right side of the figure shows the impact site for the DART spacecraft just before it hit the surface. The outline of the craft is superimposed on top with the main bus of the craft and with two extended solar panels. Also shown are the authors’ estimated paths for the 104 boulders tracked. They may be the remains of two surface rocks that were shattered upon impact. To the left is the radius distribution for the boulders that were tracked in the study. [Farnham et al. 2025]

The shallow angles and high ejection speeds are consistent with this scenario. Regardless of how they were ejected, though, it is clear that a significant amount of momentum can be found in the debris and that this process plays an important part in understanding how a kinetic impactor can deflect asteroids.

The European Space Agency’s Hera mission, now en route and arriving in 2026, aims to carry out an in-depth post-impact analysis. It could determine if Dimorphos is tumbling in its slightly modified orbit and help assess the momentum transfer from the impact debris. All this will contribute to a better understanding of just how much the impact changed the asteroid’s orbit and how much more momentum came from the ejected material than was contributed by the DART spacecraft to Dimorphos. These data will be key to refining asteroid deflection strategies in the case that we might need them in the future. After all, the dinosaurs didn’t have any, and look where it got them!

Original astrobite edited by Chloe Klare.

About the author, Kasper Zoellner:

I have a Master of Science in astronomy and I am currently working towards a PhD in physics and educational science. My greatest passion is the search for exoplanets and how stellar variability may influence the possibility of life. I am also interested in science outreach, education and discussing what sci-fi novel to read next!

Messier 82

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: Stars Born in the Wind: M82’s Outflow and Halo Star Formation
Authors: Vaishnav V. Rao et al.
First Author’s Institution: University of Michigan
Status: Published in ApJ

Outflows and Star Formation

Some galaxies, known as starburst galaxies, form stars at exceptionally high rates. High star formation rates mean, you guessed it, lots of new stars! The most massive stars live comparatively short lives and can die in a brilliant cosmic explosion known as a supernova. So, when you have a starburst galaxy, you get lots of young stars, a fraction of which produce supernovae. While these stellar explosions occur on relatively small scales, they can collectively drive galactic-scale expulsions of gas and dust known as outflows.

Outflows expel gas laden with metals out of the galaxy, playing a pivotal role in the evolution of galaxies. They can also drive additional star formation in the areas surrounding the galaxy, which is exactly what today’s authors are interested in. Messier 82 (M82), a quintessential local starburst galaxy, is the focus of today’s article (see Figure 1). M82’s proximity makes its spectacular outflows a prime testing ground for studying the impact of outflows on a galaxy and its surroundings.

starburst galaxy Messier 82

Figure 1: An image of the local starburst galaxy M82, taken by the Subaru Telescope. The Hubble Space Telescope field encompassing the Southern Arcs is highlighted as a green box. [Rao et al. 2025]

The Southern Arcs of M82

The main focus of today’s article are arc-like groups of stars called the Southern Arcs that are located near M82’s southern outflow. Using photometry from the Hubble Space Telescope, today’s authors derive star formation histories for the Southern Arcs, with the goal of understanding the impact that M82’s outflows have had on star formation in its halo. Figure 1 shows the Southern Arcs region of M82 highlighted in green alongside an image of M82.

Star Formation Histories

If you’ve ever taken an astronomy class, you’re probably familiar with the Hertzsprung–Russell (HR) diagram. HR diagrams are one of the most powerful tools available to astronomers, as they encode a ton of information regarding populations of stars and their formation. In practice, astronomers can construct HR diagrams using resolved stellar populations. That is, if you can resolve individual stars in a galaxy, you can construct a color–magnitude diagram, which is essentially the HR diagram you may be familiar with, but uses observed properties as a proxy for temperature (color) and luminosity (magnitude).

Today’s authors use the color–magnitude diagrams of the Southern Arc to derive star formation histories for the region. Star formation histories describe the star formation rate as a function of time, providing an insight into when and how stellar populations formed. To derive the Southern Arc star formation histories, the authors use the MATCH color–magnitude diagram fitting code, which determines the combination of stellar populations that reproduce the observed color–magnitude diagram, accounting for observational biases along the way. Figure 2 shows the star formation histories obtained using three different stellar evolution models. The authors find that about 85% of the stellar mass in the Southern Arc field formed sometime between 70 and 150 million years ago before star formation slowed down. About 30 million years ago, star formation picked up again, producing the rest of the stellar mass in the Southern Arc field.

star formation history and cumulative star formation history of the Southern Arc region

Figure 2: The star formation history (left) and cumulative star formation history (right) of the Southern Arc region. Different stellar evolutionary models are marked in different colors. The star formation history shows the star formation rate as a function of time, while the cumulative star formation history shows the buildup of the stellar mass as a fraction of the total mass observed now. [Rao et al. 2025]

So, What’s the Deal with the Southern Arcs?

The authors explore two mechanisms that could explain the star formation histories. In the first scenario, M82’s outflows trigger star formation when impacting the cooler circumgalactic gas. When the outflow shocks collide with the cooler gas, it causes it to collapse and form stars. In the second scenario, star formation is occurring within the outflows themselves. Figure 3 is a schematic of the two proposed mechanisms.

schematic outlining the two possible mechanisms for the formation of the Southern Arcs

Figure 3: A schematic outlining the two possible mechanisms for the formation of the Southern Arcs. The left panel shows the scenario in which shocks produced by the outflow collide with gas in the circumgalactic medium, triggering star formation. The right panel shows the scenario in which star formation is triggered within the outflow itself. [Rao et al. 2025]

The authors emphasize that distinguishing between the two scenarios requires further observations, specifically to determine metallicities of the stars in the Southern Arcs. If the two distinct stellar populations have different metallicities, it is more likely that the stars formed within the outflow in multiple gas clouds. If the populations have similar metallicities, it hints that the outflow shock triggered star formation, leading to similar stellar populations. So, as the age-old saying goes, “further data are needed” to better understand the origin of the Southern Arcs!

Original astrobite edited by Jessie Thwaites.

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!

Illustration of stellar-mass black holes embedded within the accretion disk of a supermassive 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: Tracing the Light: Identification for the Optical Counterpart Candidates of Binary Black Holes During O3
Authors: Lei He et al.
First Author’s Institution: University of Science and Technology of China
Status: Published in ApJ

Since the first detection of gravitational waves about a decade ago, gravitational wave science has been the gift that keeps on giving (for example, check out GW231123, announced earlier this year). It is also a field where more questions with unknown answers just keep coming. A key question at the forefront of gravitational wave science is about formation channels: how does the population of black holes seen through the LIGO–Virgo–KAGRA (LVK) detectors form? The two most popular of these formation channels are the “isolated binary” channel, wherein two stars of a binary stellar system each form black holes that then merge, and the “dynamical” formation channel, wherein two stars in a dense stellar cluster (usually a nuclear star cluster) become black holes and merge just through chance and the denseness of the environment they are in.

More recently, a third channel has been gaining popularity: the active galactic nucleus (AGN) disk channel. An AGN disk is a large disk of hot gas that surrounds a supermassive black hole in the center of a galaxy. The disk helps address two potential issues with stellar-mass binary black hole mergers that could pose a problem for the other two formation channels: delay time and mass. The delay time is the time between when the binary system forms and when the two black holes merge. By putting the system into the denser gaseous environment of an AGN disk, the orbits of the black holes decay faster, allowing the merger to happen on a quicker timescale. Regarding mass, the LVK detectors have detected mergers with masses above what would be expected from stellar-mass black holes alone, the so-called “lite” intermediate-mass black holes. One potential avenue through which these “lite” intermediate-mass black holes may form is in the gaseous disks of AGNs, where they can accrete material and gain mass before merging.

One potential astronomical benefit of a binary black hole merger happening inside the gaseous disk of an AGN is that the merger could disturb this disk and spark a flare of light. If we could spot such a flare and tie it to a gravitational wave event, we would then have both gravitational wave and electromagnetic observations of the same event. Prior research has suggested that some AGN flares detected by the Zwicky Transient Facility (ZTF) might be linked to binary black hole mergers observed during LIGO–Virgo’s third observing run. Today’s authors revisit this possibility by using additional years of data from ZTF combined with the public data through the third observing run.

The authors re-analyzed seven candidate flare–gravitational wave pairs originally flagged during the third observing run (see Figure 1). They examined each AGN’s long-term light curve from data from ZTF, looking for repeated flaring that might indicate a variable AGN rather than a one-time merger-driven flare. Using a Bayesian framework and an approach called Gaussian processes, they calculated the probability that each optical flare was physically connected to a specific gravitational wave event, considering both the spatial and temporal alignment of each of the two signals. Their framework allowed them to calculate a value they dub pflare, which is the probability that a given flare is indeed a genuine flare rather than a characteristic of the variability intrinsic to the AGN itself.

Sky localization of the seven AGN systems analyzed in this work

Figure 1: Sky localization of the seven AGN systems analyzed in this work. Red stars represent the locations of the AGNs with suspected flares, and colored lines represent the nine potential gravitational wave events that may be associated with each AGN flare. The white/black background represents the density of the distribution of AGNs in the Million Quasar Catalog. [He et al. 2025]

After analyzing the updated data, only two of the original seven flare candidates remained consistent with being merger-driven events, as the two associated AGNs showed no additional flares for three years after the initial brightening, suggesting that their activity was not just normal AGN variability.

The authors take this result one step further. One primary application of combining gravitational wave and electromagnetic signals is an independent measurement of the Hubble constant. The most straightforward way to measure the Hubble constant is to measure both the recessional velocity and the distance to a single source. Multi-messenger astronomy provides a straightforward approach to this, as the redshift can be determined from electromagnetic observations and the distance from gravitational wave observations. (GW170817 is a notable example of this.)

The authors show how this could be applied to their data using flares. They use the two most promising flare–gravitational wave associations to derive a new estimate of the Hubble constant. By combining the distance inferred from the gravitational wave signal with the redshift of the AGN host galaxy, they obtained a value of the Hubble constant of about 72 kilometers per second per megaparsec (roughly the peak of the green dotted curve on the bottom of Figure 2). This result is consistent with other measurements of the Hubble constant, which are the local distance-ladder measurements from supernovae and the cosmic microwave background estimates from Planck (the two measurements that are often cited as being in tension). The uncertainty from the author’s analysis is still quite large, but it provides a proof of concept. When they included the well-known GW170817 neutron star merger, they obtained a result that is slightly more informative and slightly greater than the result from GW170817 alone.

plot showing constraints on the Hubble constant from multiple methods

Figure 2: Constraints on the Hubble constant using multiple methods. For both figures, the x-axis represents the inferred value of the Hubble constant, and the y-axis represents the posterior probability of that value using hierarchical Bayesian analyses (for gravitational wave analyses). The vertical orange bands represent the measured value of the Hubble constant with five standard deviations of certainty using the “distance ladder” method as reported by the SH0ES collaboration. The vertical blue bands represent the measured value of the Hubble constant with five standard deviations of certainty by using measurements of the cosmic microwave background with the Planck spacecraft. The dotted black curve (both left and right) represents the posterior distribution of the Hubble constant as measured by the LVK collaboration from the first binary neutron star multi-messenger source, GW170817 (which peaks directly between the other two measurements). The purple and red curves (left) represent the posterior distributions of the two confident AGN/binary black hole pairs in this work, the green curve (right) represents the combined posterior distribution of the two confident AGN/binary black hole pairs in this work, and the solid purple curve (bottom) represents the combined posterior distribution of the two confident AGN/binary black hole pairs with GW170817. [He et al. 2025]

What makes this work so exciting is that it showcases a method for identifying black hole binaries in AGN disks, and once identified, turning the joint observation of the merger and AGN disk into a new astronomical and cosmological tool! If we can confidently identify a handful of these events, they can be used both to understand binary black hole formation channels and to independently measure cosmological distances, thereby expanding our understanding of the universe. With upcoming surveys like the Vera Rubin Observatory’s Legacy Survey of Space and Time, which will monitor vast numbers of AGNs with greater cadence and depth, the prospects for finding more such events are strong.

Original astrobite edited by Amaya Sinha.

About the author, William Smith:

Bill is a graduate student in the astrophysics program at Vanderbilt University. He studies gravitational wave populations with a focus on how these populations can help inform cosmology as part of the LIGO Scientific Collaboration. Outside of astrophysics, he also enjoys swimming semi-competitively, music and dancing, cooking, and making the academy a better place for people to live and work.

Illustration of a binary system containing two white dwarfs

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 Evolution of Hypervelocity Supernova Survivors and the Outcomes of Interacting Double White Dwarf Binaries
Author: Ken J. Shen
Author’s Institution: University of California, Berkeley
Status: Published in ApJ

Even stars get kicked around sometimes. When a white dwarf — a dense stellar corpse that’s run out of its nuclear fuel — gets pushed past its limit, the result is a spectacular thermonuclear explosion called a Type Ia supernova. Two stars are needed to trigger a Type Ia supernova explosion. In a binary system that gives rise to a Type Ia supernova, the more massive star, called the primary, steals mass from the less massive companion star. As the primary gains mass, it undergoes a runaway thermonuclear reaction and explodes. Despite the violent nature of the blast, it doesn’t always destroy everything in sight. While the primary star is obliterated, the companion star might survive the explosion by being launched, or “kicked,” into space at incredibly high speeds.

A few of these hyper-velocity survivors have been detected in surveys, particularly from the Gaia mission. Understanding how these stars survived a supernova provides important clues about how a supernova forms and explodes in the first place.

The D6 Model: (Double the Trouble) + (Double the Double the Trouble)

In today’s post, we explore the “dynamically driven double-degenerate double-detonation” model, fortunately shortened to the D6 model. (Try to say that ten times fast!) The D6 model describes a binary star system of two white dwarfs, each of which is generally composed of an even mix of carbon and oxygen. (Sometimes white dwarfs composed of helium or a mix of oxygen and neon are also possible.) As the white dwarfs spiral toward each other, the more massive primary star steals material, often helium, from the less massive companion star’s outer shell. If this mass transfer is violent enough, it can trigger a detonation within the helium shell of the primary star. This detonation then triggers an explosion deep within the core of the primary star, causing a supernova.

For a Type Ia supernova, it takes two stars to tango. What happens to the secondary (donor) star? One theory suggests that it can be blasted away from the scene of the crime at speeds ranging from approximately 1,000 to 3,000 km/s, becoming a so-called hyper-velocity star. Of these observed “survivors,” the hottest of the bunch have been theorized to be heated by the supernova explosion itself. But some of these survivors have been cooler (in temperature). If these companion stars were in the vicinity of the blast, how could they not be heated by the explosion? What can their temperature tell us about their origin?

Defining the Model

To explore the origins of these cool hyper-velocity stars, today’s author used the stellar evolution code MESA to model the evolution of different types of white dwarf companion stars after (presumably) surviving a Type Ia supernova. A key focus was on the Kelvin–Helmholtz mechanism, which is the process by which a star cools and therefore contracts over long periods as it radiates away its internal heat.

Because white dwarfs come in many flavors, they explored a range of possible elemental compositions for the companion white dwarf: helium-rich (He-rich), carbon/oxygen-rich (C/O-rich), and oxygen/neon-rich (O/Ne-rich).

One important detail of these models is that the stars were assumed to be fully convective, which is a common property of low-mass stars with masses less than around 0.4 M☉. (You can think of a fully convective star almost like a massive lava lamp where the heat source is at the center of the sphere.) Extensive mass loss can cause a more massive non-convective star to become less massive and convective, which in turn makes it susceptible to cooling quickly and avoiding a fiery death as a supernova. (Hotter gas rises to the surface, where the particles lose kinetic energy by doing work, gradually slowing down and cooling off.) This is key if we want to produce cool, fast-moving stars.

Detonate First, Simulate Later

For helium-rich survivors, the simulations suggest that if the companion star loses enough mass either before or during the explosion, the star’s natural Kelvin–Helmholtz evolution can potentially explain why we observe some cool hyper-velocity survivors. In the case of a star called D6-2, the simulations reproduced its low temperature and luminosity, assuming that it began its life as a helium white dwarf that was shredded but not entirely destroyed. This produces a tiny, convective, hyper-velocity supernova survivor.

D6-2 is an interesting object, however, because it has a fairly low velocity for a potential hyper-velocity survivor. Its velocity is estimated to be about 1,050 km/s, which simulations suggest should be higher based on its estimated mass. It’s likely that either the simulations and models need refining or D6-2 had an altogether different origin.

What About the Others?

So far, we’ve mainly talked about He-rich stars, but what about those C/O-rich ones? These stars would likely appear cooler and redder since they evolve at a nearly constant temperature before moving onto the standard white-dwarf cooling track. (This is called the Hayashi track.)

Red objects are harder for telescopes to detect and often get mistaken for other stars or objects, partially due to a pesky phenomenon called dust extinction, or interstellar reddening. To expand the search for these hyper-velocity candidates, surveys like Gaia might benefit by expanding their search limits to include redder stars, although this opens up the possibility of increasing the number of false positives.

A different class of fast-moving, faint stars — like LP 40-365 — could be related to this population. They are theorized to be remnants of white dwarfs around 1.4 M☉ that only partially exploded. Low-mass, O/Ne-rich survivors might match the observed temperatures and luminosities of LP 40-365, but the ages don’t line up as well as one might hope. (More work will be needed to figure out this particular puzzle.)

The Odds of Stellar Survival

Based on these simulations, it’s estimated that about 2% of Type Ia supernovae might leave behind a He-rich hypervelocity star like D6-2 (see Fig. 1). If we consider C/O-rich survivors (like D6-2’s cousins D6-1 and D6-3), the rate drops to about 0.2%, which is intriguingly close to the estimated rate of SN 2003fg-like events: unusually bright, slowly evolving Type Ia supernovae that often display tell-tale signs of unburned carbon and oxygen in their spectra.

A histogram of detectable hypervelocity survivors from the He-rich track

Figure 1: A histogram of detectable hyper-velocity survivors from the He-rich track assuming every Type Ia supernova produces a companion with a mass of 0.02 solar mass. These survivors are assumed to be ejected from their Type Ia supernovae at a velocity of 1,050 km/s, matching D6-2. The x-axis, tmidplane, describes the apparent travel time from the midplane of the simulation’s galaxy. A negative value means the survivor was observed before it passed through the plane. A total count of 43 hyper-velocity survivors from every Type Ia supernova yields an estimated survival rate of about 2%. [Shen 2025]

The presence of these hyper-velocity survivors might be linked to rare types of supernovae, which would provide an interesting way to look into the origins of these oddball events.

Choose Your Own (Stellar) Adventure

This article suggests different evolutionary paths for how binary white dwarfs might evolve. Depending on the properties of the merger, the system might do any of the following:

  1. Trigger nuclear reactions within the outer shell of the primary without detonating the primary’s core
  2. Become a normal Type Ia supernova
  3. Leave behind a hyper-velocity remnant
  4. Become a SN 2002es-like supernova, which is a fainter type of Type Ia supernova

There are lots of potential outcomes for these types of binaries, and hyper-velocity survivors indicate just a tiny fraction of a particular configuration of binary white dwarfs (see Fig. 2).

diagram of the speculative outcomes for a white dwarf–white dwarf binary

Figure 2: A diagram of the speculative outcomes for a white dwarf–white dwarf binary. The y-axis shows the secondary’s initial mass, whereas the x-axis shows the primary’s initial mass. The dashed lines indicate where the combined white dwarf mass is 1.4 M☉. The plot illustrates the wide variety of outcomes of white dwarf–white dwarf binaries, of which hyper-velocity survivors (HVS) are rare. sdB/sdO = subdwarf B/O stars; R CrB = R Coronae Borealis, variable star; Fe CC = iron core-collapse supernovae; HVS = hyper-velocity survivor; NS = neutron star. [Shen 2025]

These stellar survivors are rare and fast. Cooler hyper-velocity survivors, in particular, are fascinating because they may originate from white-dwarf binaries with unusual properties. Studying these fast-moving stars helps piece together our understanding of Type Ia supernovae as a whole. With improved surveys and simulations, we may discover more about these elusive escapees.

Original astrobite edited by Chloe Klare.

About the author, Mckenzie Ferrari:

I’m currently a PhD grad student in the Geophysical Sciences program at the University of Chicago. While I now study the atmosphere and oceans of Earth, most of my previous undergrad and grad research focused on simulations of Type Ia supernovae and galaxy formation and evolution. In my free time, I foster cats for a local organization, enjoy cooking, and can often be found running along Lake Michigan.

Illustration of a giant planet with a large moon orbiting a distant 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: Astrometric Methods for Detecting Exomoons Orbiting Imaged Exoplanets: Prospects for Detecting Moons Orbiting a Giant Planet in α Centauri A’s Habitable Zone
Authors: Kevin Wagner et al.
First Author’s Institution: University of Arizona
Status: Published in ApJL

Six of the eight planets in our solar system host at least one moon; the innermost planets Mercury and Venus are the exceptions. The origins of these moons are widely studied and hotly debated. Earth’s very own moon seems to have formed in the aftermath of a collision between the young Earth and another protoplanet. Mars seems to have captured two asteroids as its moons, Phobos and Deimos, a process thought to have produced many of the irregular satellites orbiting the gas giants as well. Using our solar system as a model, the presence of moons seems like a natural outcome of planet formation.

Why then don’t we observe exomoons, moons orbiting any of the ~6,000 known exoplanets? Well, the largest moon in our solar system, Ganymede, is 2.5% as massive as Earth and has 40% of the radius, making it marginally larger than Mercury but still less massive. You might have heard how difficult it is to find Earth-like exoplanets, and finding exomoons is even harder. A few exomoon candidates have been announced via microlensing and transits, but the authors of today’s article investigate whether a different technique, astrometry, could help find moons.

Astrometry involves precisely tracking the positions of objects like stars or planets on the sky. In a simple star–planet system, the star and planet trace out ellipses around their shared center of mass. With a moon present, there is an additional deviation, as the planet wobbles to and fro due to the gravitational tug of the moon. The authors of today’s article check whether moons can be detected by tracking such wobbles exhibited by directly imaged planets.

To start, the authors consider whether any known planets are promising targets for astrometric moon searches. There just so happens to be a giant planet candidate in Alpha Centauri, and if there were a massive moon orbiting this large planet around this nearby star, it would be as good as it gets. The authors simulate orbits of this system (a Saturn-like planet in a 1.8 au orbit around a Sun-like star at a distance of 4.2 light-years) with a 30-Earth-mass moon injected. They simulate observing such a system with a space-based 6.5-meter telescope (similar to the planned Habitable Worlds Observatory) with realistic noise over a 3-year observing campaign. The simulated and modeled orbits are shown in Figure 1. After the authors subtract the best-fit planet orbit, they are left with what is shown in Figure 2, where a clear periodic perturbation from the moon as it orbits is visible.

plots of the hypothetical orbit of a moon in the Alpha Centauri system

Figure 1: Left: The zoomed-out orbit of the hypothetical Alpha Centauri star–planet–moon system. The blue curve shows the Keplerian orbital fit. Right: The zoomed-in orbit. The red points are the simulated observations, showing deviations caused by the moon. [Wagner et al. 2025]

plot showing deviations in position of the planet’s orbit over time

Figure 2: Left: Deviations in position of the planet’s orbit over time. The red points show the simulated observations, and the black curve shows the data smoothed. Right: Zoom-in showing the moon’s effect on the planet’s motion. [Adapted from Wagner et al. 2025]

The authors then repeat this procedure with more realistically sized moons and a more optimistic observing campaign (5-year baseline, 1-hour observing cadence, precision of 0.1 milliarcsecond) looking at the Alpha Centauri giant planet candidate. They use the difference in the chi-squared (χ2) test statistic to determine whether the presence of a moon is statistically preferred. Figure 3 shows the moon-induced deviations for two different moon masses and the resulting χ2 difference. Using their χ2 difference threshold of ~5, the lowest-mass detectable moon is ~0.2 Earth mass. This is much more massive than the Moon, which is around 1% of Earth’s mass. The authors additionally vary the moon’s orbital period and find that periods of 4–30 days are detectable.

plot of periodic position deviations caused by a moon

Figure 3: Left: Moon-induced planet position deviations over the first 90 observing days. Middle: Deviations from the entire 5-year observing baseline folded around the best-fit moon orbital period. Right: χ2 difference as a function of period, showing a peak in the signal at the moon’s orbital period. [Adapted from Wagner et al. 2025]

The authors continue to consider more specific observing scenarios: a 39-meter ground-based telescope (similar to the planned European Extremely Large Telescope) and a 3-meter space telescope built specifically to find moons. They find that the ground-based telescope observing once per day could detect an Earth-mass moon around a Saturn-like planet over a 5-year observing campaign. The dedicated space telescope observing once per hour could make the same detection observing over 5 years. While detecting moons astrometrically is neither easy nor fast, it may be feasible to start finding moons around planets orbiting nearby stars in the coming decades.

All of this is great news for fans of the hit movie (and still the highest-grossing movie of all time) Avatar, which features a habitable exomoon in the Alpha Centauri system. Searching for moons will help us understand their properties and formation, probe whether our solar system is unique, and even look for life on rocky moons orbiting gas giants in the habitable zones of their stars.

Original astrobite edited by Ryan White.

About the author, Kylee Carden:

I am a PhD student at Johns Hopkins University, where I am an observer of planets outside the solar system. I’m interested in dynamics, disks, demographics, the Roman Space Telescope. I am a huge fan of my cat Piccadilly, cycling, and visiting underappreciated tourist sites.

illustration of a planetary system

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 Gap–Giant Association: Are Planets Hiding in the Gaps?
Authors: Caleb Lammers and Joshua Winn
Authors’ Institutions: Princeton University
Status: Published in ApJ

The Kepler space telescope played an almost decade-long game of hide-and-seek. After nine and a half years of operation, Kepler detected more than 2,700 planets outside of our solar system primarily by using the transit method, which is particularly efficient at detecting planets that orbit close to their host stars. Astronomers have also been detecting planets with the radial velocity technique, which is better at finding larger planets at longer orbital periods. By looking for planets with both the transit and radial velocity techniques, astronomers can look for both close-in and far-out planets to paint a more complete picture of other solar systems in our galaxy.

Using the Kepler Giant Planet Survey, the authors of today’s article found that among the 26 systems with three or more transiting planets, four were found to also have an outer giant planet. They quickly noticed that instead of an evenly spaced out inner system of planets, every single one of these four systems with the outer giant planets revealed a notable gap between two of their inner planets. They dubbed this phenomenon the “gap–giant association” — in other words, when an outer giant planet exists in a planetary system, there is evidence of a large gap between two of the inner planets, as shown in Figure 1. This pattern has been observed before, but there has been little theoretical work to explain the effects of outer giants on orbital spacings. In today’s article, the authors ask the question: are there planets inside the gap hiding from us? To address this, they conduct simulations to see if (a) these systems can host a hiding planet in their gaps without becoming dynamically unstable and (b) if such a planet can remain hidden when looked for with the transit method.

Plot of the orbital spacing of planets

Figure 1: Orbital spacings of systems in the Kepler Giant Planet Survey with three or more transiting planets in the inner planetary system. The parameter C is a metric denoting the regularity of orbital spacings, where a smaller value would indicate a more uniform spacing. The four systems of interest all have large orbital gaps between two adjacent inner planets, and therefore high values of C. [Lammers & Winn 2025]

Close Your Eyes and Count to N

The authors of today’s article model these four systems (Kepler-48, Kepler-65, Kepler-90, and Kepler-139) with a planet added to their gaps and use an N-body simulation (i.e., fancy physics calculations that track how planets gravitationally interact) to evolve the systems over time and evaluate their long-term stability. They find that each of these injected planets has a high survival rate, which means that each of these four systems could stably host an additional ~2–20 Earth-mass planet in its gap for billions of years without falling apart. The authors then calculated whether the outer giants could “hide” these theoretical gap planets by tilting the planets’ orbits enough so that they would not be detectable with the transit method. In order to do this, the outer giant would have to exert a large enough gravitational force on the gap planet to cause it to precess at a rate independent of its neighbors, allowing its orbital inclination to grow. However, they found that the outer giant planets are either too far away or not massive enough to do the job.

Only one system, Kepler-90, has an outer giant that could potentially tilt the gap planet’s orbit enough for it to fly under the radar if the giant were also on a modestly inclined orbit. However, previous detections of Kepler-90’s outer giant suggest that its orbit is well-aligned with those of the inner system, making this hypothesis implausible. They therefore concluded that it is unlikely that planets between ~2 and 20 Earth masses are hiding within these gaps.

Seeking Out Another Option

Before completely abandoning this hypothesis, the authors propose that maybe the gaps do contain planets, but they’re just too small for Kepler to detect. They calculate the detection efficiencies as a function of planet radius and orbital period for each of the four systems and find that planets smaller than about ~0.5–1 Earth radius could have gone unnoticed (as shown in Figure 2). While this would make these systems slightly unusual (most multiplanetary systems have relatively uniform planet sizes), it’s not completely impossible. However, they don’t rule out the possibility that these gaps are truly empty, and that the presence of an outer giant could prevent planets from forming in certain regions or disrupt their orbits after formation. While it is hard to draw any firm conclusions with a sample size of four systems, this study highlights how much we still don’t understand about planetary system architecture, and therefore planetary formation and evolution.

Plots of transit detection efficiency as a function of planetary radius and orbital period

Figure 2: Transit detection efficiency as a function of planetary radius and orbital period for each planetary system. The inner planets and location of the gap are overplotted. The darker contours show regions where Kepler is not sensitive to detecting planets. In order to avoid detection, the planets in each of these systems would have to be much smaller relative to their neighbors, except for the Kepler-90 system, where a hidden planet would only have to be marginally smaller. This suggests that there could exist a demographic of exoplanets that are evading detection within these gaps. [Lammers & Winn 2025]

Though the Kepler mission has come to an end, ongoing radial velocity surveys will continue to expand the sample of systems like these four so astronomers can get a clearer picture of what’s behind this gap–giant association.

Original astrobite edited by Annelia Anderson.

About the author, Tori Bonidie:

I am a 5th-year PhD candidate studying exoplanet atmospheres at the University of Pittsburgh. Prior to this, I earned my BA in astrophysics at Franklin and Marshall College where I worked on pulsar detection as a member of NANOGrav. In my free time you can find me cooking, napping with my cat, or reading STEMinist romcoms!

illustration of a quasar

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: Quasar Lifetime Measurements from Extended Lyα Nebulae at z∼6
Authors: Dominika Ďurovčíková et al.
First Author’s Institution: MIT Kavli Institute for Astrophysics and Space Research
Status: Published in ApJ

Observations have shown that galaxies, from our own Milky Way to far out into the distant universe, often host supermassive black holes at their centres. While the exact growth history of supermassive black holes is still uncertain, astronomers think that they likely begin as much less massive black holes, which grow primarily by eating up gas in a process known as accretion. As gas falls into the black hole, it releases a huge amount of energy, allowing astronomers to observe accreting black holes even when they’re billions of light-years away from us. The most luminous accreting supermassive black holes are known as quasars.

A supermassive black hole pulls gas in towards itself due to the force of gravity, but light emitted by the gas simultaneously exerts an outward pressure known as radiation pressure. The faster gas is being pulled into the black hole, the more light is emitted by the gas, and the stronger the pressure becomes. Eventually, the pressure will win out over gravity, preventing the black hole from accreting more gas. The theoretical maximum rate at which a black hole could accrete gas, without the gas being blown out by radiation pressure, is known as the Eddington rate.

If you took a black hole that initially weighed about 100 times the mass of our Sun and consistently fed it at the Eddington rate, it would take about 1 billion years to grow to the size of a supermassive black hole. However, measurements of quasar lifetimes suggest that black holes don’t continuously accrete at the Eddington rate, and instead, black holes go through phases of accretion. As a result, we should not expect to find supermassive black holes within the first billion years of the universe’s history.

But the universe loves to throw astronomers curveballs. Indeed, we have observed quasars less than 1 billion years after the Big Bang, suggesting that this simple picture of supermassive black hole growth is not quite right. Many mechanisms have been proposed as ways to speed up black hole growth, including accretion rates higher than the Eddington rate, mergers between two black holes, and phases of obscured growth during which the black hole accretes at the Eddington rate, but most of the light released in this process is hidden from view.

Today’s authors tackle the question of whether black holes have substantial phases of obscured growth by measuring the lifetimes of early universe quasars. Previous measurements have suggested that these quasars have only been active for less than 1 million years. However, the method that was previously used could be underestimating quasar lifetimes if there was a period of obscured growth. To determine whether this is the case, today’s authors use a different, independent method of measuring the quasar’s lifetime; if there’s a significant mismatch between the two age estimates, then it’s likely that the quasar has had significant periods of obscured growth.

The key to the methods used by today’s authors is that they probe different lines of sight to the quasar. Previous methods quantified the effect of a quasar’s light on the intergalactic medium (the diffuse gas in between galaxies) along the line of sight from the quasar to us. The method used in today’s article measures the size of a nebula of ionised gas, in the plane of the sky, at a right angle to the line of sight. While light from the quasar may have been obscured along our line of sight, it’s unlikely to have also been obscured at a different angle at the exact same time.

A quasar emits a lot of photons capable of ionising hydrogen, and as a result, a quasar can carve out bubbles of ionised gas in the otherwise neutral circumgalactic medium. The size of the ionised gas bubble, or nebula, grows at the speed of light, so if you know the size of the nebula, you can estimate the time since quasar activity began. Today’s authors looked for ionised gas in the circumgalactic medium of six early universe quasars, all of which are estimated to have very short lifetimes based on line-of-sight measurements.

To observe ionised nebulae in the circumgalactic medium, today’s authors use observations from the Very Large Telescope’s Multi-Unit Spectroscopic Explorer (MUSE). The first three panels of Figure 1 show you (left to right) the quasar; the point-spread function (PSF), or a model of how the quasar’s light diffracts as it’s observed by MUSE; and the image of the region surrounding the quasar once you subtract the PSF from the image. Each pixel is colour-coded by brightness. The last two panels also show the PSF-subtracted image, but are instead colour-coded by the ratio of signal to noise in each pixel. In the last panel, the signal has been smoothed out, and you can see the structure of a nebula (outlined in red) emerge from the image.

observations of a quasar

Figure 1: To observe the nebula (red outlined region in the rightmost panel), you have to subtract out the light coming from the quasar (leftmost panel). [Adapted from Ďurovčíková et al. 2025]

Only three of the six quasars have a detected nebula. In the case of the non-detections, the authors argue that this is likely because the nebulae are just too small to be resolved by the telescope, rather than the nebulae being too faint. In fact, the nebulae could have been ten times fainter than the ones observed, and they still would have been detected. As a result, the authors can only estimate the ages of three of the quasars and place upper limits on the ages of the other three.

plot of quasar age estimates

Figure 2: The age estimates derived by today’s authors (y-axis) are similar to the line-of-sight age estimates (x-axis), and generally follow a one-to-one relationship, suggesting that line-of-sight obscuration effects are not leading astronomers to underestimate the age of a quasar. [Adapted from Ďurovčíková et al. 2025]

Figure 2 shows the agreement between the ages implied by nebula sizes (y-axis) and the pre-existing line-of-sight age estimates (x-axis). The grey shaded region indicates that ages below about 7,600 years could not have been detected. The black dotted line shows the one-to-one agreement between the two age estimates, and individual measurements are shown by the red squares with error bars.

Age estimates from the two methods are broadly pretty consistent, suggesting that obscuration effects are not causing one method to be severely underestimating the lifetime of a quasar. Therefore, for these six quasars, it seems unlikely that their growth can be primarily explained by phases of obscured growth. Instead, some other mechanism must have allowed these black holes to grow rapidly during the early universe and reach their supermassive sizes.

The mystery of how supermassive black holes can grow so quickly is still to be solved, but today’s article shows us that we haven’t been missing phases of obscured growth. The results of today’s article provide an independent measurement of quasar lifetimes, which models of supermassive black hole growth should be able to explain.

Original astrobite edited by Cesily King.

About the author, Nathalie Korhonen Cuestas:

Nathalie Korhonen Cuestas is a second-year PhD student at Northwestern University, where her research focuses on the chemical evolution of galaxies.

supernova remnant N49

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: SIRIUS: Identifying Metal-Poor Stars Enriched by a Single Supernova in a Dwarf Galaxy Cosmological Zoom-In Simulation Resolving Individual Massive Stars
Authors: Yutaka Hirai et al.
First Author’s Institution: Tohoku University
Status: Published in ApJL

All of the elements in stars come from, well, other stars. Each star has its own unique makeup of elements, kind of like our own DNA. Just like genes passing down generation after generation, elements in stars can be passed down to newly forming stars after the previous generation has died. So, if you’re looking at the chemical makeup of a particular star, what you’re really seeing is all the elements that were created after another star in the region exploded (went supernova) and enriched the gas (that the new star formed from) around it with elements like oxygen, nitrogen, iron, and more.

Like genealogy for stars, astronomers can use stellar enrichment to work their way back from a star they observe to its potential predecessors. It’s a bit trickier for stars that have a lot of elements, dubbed “metal-rich” stars, because there’s no way to tell which star contributed what mixture of elements at what point in time. However, scientists have recently been observing “extremely metal-poor” stars, which are stars with only small amounts of elements like oxygen, nitrogen, or carbon. Because there are so few of these elements, it’s safe to assume that these stars formed out of gas that didn’t have many predecessor stars enriching it — in fact, astronomers are hoping to find stars that only ever had one ancestor, calling them “mono-enriched” stars. Finding a mono-enriched star would tell us exactly what elements were produced in the supernova — aka in supernova nucleosynthesis.

However, how many of these metal-poor stars are mono-enriched is unknown. Estimating this fraction could help researchers identify more of them. The authors of this study tackle this problem by examining how many might exist in dwarf galaxies and what kind of chemical signatures they could produce.

Simulating Mono-Enriched Stars

To do this, they simulate a dwarf galaxy with the hydrodynamic code ASURA and model the gas physics in the galaxy with CLOUDY. In this method, stars form once the density of hydrogen gas in a region exceeds a certain threshold at a temperature that is cool enough for the gas to clump together. Pockets of this simulated region are then randomly assigned a stellar mass from the initial mass function, and eventually explode, diffusing elements into the gas particles around it.

Finding Mono-Enriched Stars in the Simulated Stellar Haystack

plot showing stellar metallicity, carbon enhancement, and mass of simulated stars in a dwarf galaxy

Figure 1: Every simulated star in the dwarf galaxy, shown as a function of their stellar metallicity, [Fe/H], carbon enhancement, [C/Fe], and their mass. Orange points are identified as mono-enriched stars. Click to enlarge. [Hirai et al. 2025]

The authors define a mono-enriched star as one with a carbon-to-iron ratio (denoted [C/Fe]) similar to that expected of a core-collapse supernova in their model. They identify a portion of the stars created as being mono-enriched, shown in orange in Figure 1. In total, this makes up about 1.5% of stars in this simulated dwarf galaxy.

Once these data points are collected, the authors investigate the fraction of mono-enriched stars at different metallicities. The authors essentially ask, are mono-enriched stars more likely to occur at lower metallicities? They find that, indeed, stars that are lower metallicity (and thus have lower [Fe/H]) are more likely to be mono-enriched (Figure 2). For stars with exceedingly low metallicities, [Fe/H] < −5, about 11% of them in this simulated dwarf galaxy have formed out of gas enriched by only one supernova.

Fraction of mono-enriched stars in the stellar population depending on the stellar metallicity

Figure 2: Fraction of mono-enriched stars in the stellar population depending on the stellar metallicity ([Fe/H]) of the population. Stars with much lower metallicities ([Fe/H] < 2.5) are more likely to be mono-enriched. [Hirai et al. 2025]

Finding Mono-Enriched Stars in the Observed Stellar Haystack

These theoretical predictions help observers prepare what to look for when they want to find a mono-enriched star. These predictions seem to suggest that astronomers should keep looking for these extremely metal-poor stars if we want to find these unique stars that tell us about what elements are made in core-collapse supernovae. There is currently a decently large database of extremely metal-poor stars found with photometry, and if observers could follow up with the most ideal candidates spectroscopically we could really test what kind of elements are in these stars. Further, the upcoming Subaru Prime Focus Spectrograph will take many spectroscopic observations of close-by dwarf galaxies, which may contain more extremely metal-poor stars.

The authors note there is more work to be done in simulations, as they are interested in testing how extremely metal-poor stars, specifically ones with enhanced carbon, form. All of this will hopefully lead to a better understanding of how elements are made when stars explode, perhaps leading us to how some of the earliest elements formed in the early universe.

Original astrobite edited by Diana Solano-Oropeza.

About the author, Caroline von Raesfeld:

I’m a third-year PhD student at Northwestern University. My research explores how we can better understand high-redshift galaxy spectra using observations and modeling. In my free time, I love to read, write, and learn about history.

Tarantula Nebula

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 AURORA Survey: The Nebular Attenuation Curve of a Galaxy at z = 4.41 from Ultraviolet to Near-Infrared Wavelengths
Authors: Ryan L. Sanders et al.
First Author’s Institution: University of Kentucky
Status: Published in ApJ

Imagine a galaxy from 13 billion years ago, long before the Milky Way took its current form. Now picture trying to uncover the secrets of that ancient galaxy. How quickly did it create stars and evolve? Here’s the tricky part: its light has journeyed across an unimaginable distance to get here. On its journey, cosmic dust — tiny grains of carbon and silicates — has scattered and dimmed the light, making the task harder.

Dust doesn’t just block light — it changes it. Ultraviolet (UV) light gets scattered much more than light at longer wavelengths, which is why galaxies seem redder and dimmer than they truly are. This dual nature can be seen in the “Pillars of Creation,” in Figure 1. A new near-infrared image from NASA’s JWST, shown in the right panel below, helps us peer through more of the dust in this star-forming region. The thick, dusty brown pillars are no longer as opaque, and many more red stars that are still forming come into view.

Pillars of creation as seen by Hubble and JWST

Figure 1: On the left, NASA’s Hubble Space Telescope captures the iconic Pillars of Creation in stunning visible light (2014). On the right, JWST unveils a breathtaking infrared view, revealing even more details hidden within the cosmic dust. [NASA, ESA, CSA, STScI; Joseph DePasquale (STScI), Anton M. Koekemoer (STScI), Alyssa Pagan (STScI)]

To quantify how dust affects light at different wavelengths, astronomers use dust curves — tools that reveal how much light is blocked or scattered, helping them correct for dust-induced distortions. For instance, the Milky Way’s curve stands out with a distinct “bump” around 2175 Å, which comes from tiny carbon-based particles in the dust. But the Small Magellanic Cloud (SMC) tells a different story. Its curve is steeper in the UV and doesn’t have that bump at all. These differences aren’t just random — they give us clues about the size, makeup, and distribution of dust grains in each galaxy. (See Figure 3 below for a visualization of these dust curves.)

But here’s the catch: most of the dust curves we have were designed for galaxies much closer to us, like the Milky Way or the SMC, so they may not apply in the exact same way to distant galaxies. Whether those same curves work for the much younger, chaotic galaxies of the early universe is an open question. The dust in nearby galaxies is well studied and relatively predictable, but does dust behave the same way in galaxies billions of years in the past?

This question drove Ryan Sanders and collaborators to study GOODSN-17940, a starburst galaxy located at a redshift of z = 4.41, when the universe was just 1.36 billion years old. Observed as part of the Assembly of Ultradeep Rest-optical Observations Revealing Astrophysics (AURORA) survey using JWST, this galaxy provided an unprecedented opportunity to investigate how dust behaved in the distant past. Using JWST’s NIRSpec instrument, the team constructed a unique dust curve by studying 11 hydrogen emission lines from Hα to H12 (the twelfth line in the rest-frame optical Balmer series), shown in Figure 2. These lines act like lighthouses, their brightness giving away how much light is being absorbed by dust at each wavelength. By comparing the observed brightnesses of these lines, the researchers created a detailed dust curve tailored to GOODSN-17940.

Spectrum of GOODSN-17940

Figure 2: Spectrum of GOODSN-17940 from the AURORA survey, showing hydrogen Balmer lines. These features help estimate the galaxy’s dust and ionization conditions. The top panel presents the 2D spectrum, showing spatially resolved emission that traces the galaxy’s structure, while the bottom panel shows the corresponding 1D spectrum. [Adapted from Sanders et al. 2025]

GOODSN-17940’s dust curve is shown in Figure 3. The y-axis represents the factor by which light is blocked/scattered by dust compared to this amount at 9550 Å. For example, a value of 2 means that light at that wavelength is attenuated two times more than light at 9550 Å.

dust attenuation curve of a redshift 4.41 galaxy compared to nearby galaxies

Figure 3: The dust curve of GOODSN-17940 (solid red line) at z = 4.41, derived in this work, compared to established curves for the Milky Way (green dashed), Small Magellanic Cloud (SMC, dotted cyan), Calzetti et al. (blue dot-dashed), and Reddy et al. z ~ 2 galaxies (purple solid). This curve is steeper in the near-infrared and flatter in the UV, highlighting unique dust properties in this galaxy. [Sanders et al. 2025]

This dust curve is surprising. In the near-infrared, it is much steeper than the curves of the Milky Way or SMC. This suggests the galaxy’s dust grains might be smaller or distributed differently. But in the UV, the curve flattens out, showing less absorption than classical models predict. And unlike the Milky Way’s dust, there’s no 2175 Å bump at all. These findings hint at a galaxy with truly unique dust properties, shaped by its extreme youth and chaotic star-forming environment. But here’s the twist — GOODSN-17940 isn’t just any galaxy. Its star formation rate is 40 times higher than typical galaxies at its redshift. While rare at redshifts of z ∼ 2–4, galaxies like this are more common in the epoch of reionization, suggesting that what we’ve learned from GOODSN-17940 could apply to reionization-era galaxies — the ones that played a key role in shaping the early universe.

So, why does this even matter? If you used the Milky Way’s dust curve to adjust for the dust in a galaxy like GOODSN-17940, you’d be way off. In fact, you’d underestimate its star formation rate by up to 50%! This isn’t just a minor detail — it could explain why star formation rates derived from Hα don’t always match those derived from UV luminosity. Such details can completely change how we interpret a galaxy. It’s the difference between a galaxy steadily forming stars and one caught in a dramatic starburst phase. That’s why astronomers focus on creating dust curves tailored to individual galaxies. This study isn’t just about one galaxy — it’s about rethinking how we interpret dust, star formation, and galaxy evolution in the early universe. Before JWST, isolating individual emission lines from distant galaxies was challenging, but it has become much more efficient now. As more galaxies like GOODSN-17940 are studied, we might find that many early galaxies had dust curves breaking the mold, forcing us to refine how we measure star formation and understand cosmic history.

Original astrobite edited by Hilary Diane Andales and Delaney Dunne.

About the author, Niloofar Sharei:

I’m a third-year Astronomy PhD student at University of California, Riverside, where I study bursty star formation histories and how galaxies take shape. When I’m not busy exploring the universe, you can usually find me curled up with a good book, hiking somewhere peaceful, trying astrophotography, or getting lost in Bach’s music and art.

Earth's clouds seen from space

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: Clouds Can Enhance Direct-Imaging Detection of O2 and O3 on Terrestrial Exoplanets
Authors: Huanzhou Yang, Michelle Hu, and Dorian S. Abbot
First Author’s Institution: University of Chicago
Status: Published in ApJ

In the hunt for life beyond Earth, studying exoplanet atmospheres is one of our most powerful tools. The atmosphere of an exoplanet acts as a window into its environment and allows astronomers to take a guess at what processes are shaping the planet’s climate, chemistry, and thus, its potential for habitability. The gases present in the planet’s atmosphere impart a unique spectral fingerprint on the light that passes through the atmosphere and allows us to identify what gases might be present and look for possible signs of life.

JWST is already hard at work looking at distant worlds and gathering spectroscopic data for us to analyse. It has already observed several exoplanets and recorded the light that passed through their atmospheres. This has not only sparked a debate over what could be interpreted as the first possible signs of biological activity, but has also given us a glimpse of worlds that are remarkably different from our own.

However, JWST is mostly limited to observing the atmospheres of transiting exoplanets. That means planets that orbit close to their host star and are more or less directly edge-on, as viewed from us, so that they transit across the face of the star. The only planets that the telescope is able to observe directly are big, young, and hot planets farther from their host star, at distances more resembling those of the outer planets in our solar system, like Saturn or Uranus. If only we had a telescope powerful enough to image a potentially habitable planet directly and analyse the light reflected from it.

The Habitable Worlds Observatory

This is where the Habitable Worlds Observatory (HWO) will come in. Now, I know what you are thinking. Why must astronomers always look towards greener pastures bigger telescopes when we already have perfectly functional space telescopes in orbit or practically on the launch pad? Well, it is true that the next flagship space telescope from NASA, the Nancy Grace Roman Space Telescope, is designed to directly image exoplanets and analyse their atmospheres. But space telescopes can take decades to plan and are often built on lessons learned from previous missions. Roman, with its 2.4-meter primary mirror and coronagraph, will be able to observe planets similar in size and orbital distance to Jupiter and will get us some of the way, for sure, but not all the way. At three times the mirror size, HWO, NASA’s proposed successor to Roman that is planned for the 2040s, will carry the torch even further and be able to directly image Earth-like planets in the habitable zone, where liquid water can exist on the planet’s surface.

But It Might Be Cloudy Tomorrow

This brings us to today’s article. If the HWO is going to potentially observe Earth analogues, we might expect it to run into the same issue that plagues everyone living in the UK for most of the year — clouds. Clouds in the atmosphere of an exoplanet can sometimes cause trouble when trying to analyse the light. Cloud particles scatter different wavelengths of light differently, and cloud variability creates dynamic changes in the observed brightness that can make it hard to know what exactly you are looking at. Clouds can also mean varying levels of opacity to look through depending on cloud composition, and they can hide underlying atmospheric properties such as water content beneath a thick cloud layer. For transmission spectroscopy, even a thin layer of clouds can disrupt the measurements as the light has to travel a long distance through the atmosphere. However, for direct imaging, the effect of clouds is perhaps more nuanced. While a thick cloud deck will block the signal from whatever gas lies beneath it, it will also increase the overall albedo of the planet and make it easier to detect the gas above. This means that cloud height and type are both critical variables in understanding atmospheric properties of exoplanets, which is what the authors of today’s article set out to investigate.

To understand how clouds affect the ability to detect signs of life on distant Earth-like planets, the authors used computer simulations. They focused on two gases, molecular oxygen (O2) and ozone (O3). Both gases are often regarded as biosignatures, although their astrobiological significance has been debated. The authors first used a tool that simulates how a telescope like the HWO might observe an Earth-like planet around a star 15 parsecs away. This tool predicts how light bounces off a planet’s surface and atmosphere, and whether the two gases would show up clearly in the reflected light. Next, they created realistic cloud conditions using a cloud microphysics model. This model calculates how clouds might form and behave depending on factors like surface pressure or how much sunlight the planet gets. With this they were able to change things like cloud height and particle size. They then combined the two tools by adding the simulated clouds into the observations model and building a mathematical model to help explain what they saw in the simulations. The sketch for their model can be seen in Figure 1.

diagram showing how clouds affect the amount of reflected light from an exoplanet

Figure 1: Clouds can affect the amount of reflected light (albedo) from the imaged planet. Depending on the cloud height and particle size, this can have a big impact on the observability of different species of gas in the atmosphere. Here the blue arrows indicate the amount of light entering the atmosphere and being reflected. The arrows get thinner from tail to head, representing absorption in the atmosphere. Depending on the presence of clouds, a varying amount is reflected back. The red colour indicates the assumed distribution of ozone, O3, which is concentrated at a high altitude. [Yang et al. 2025]

A Cloudy Sky Can Actually Be a Good Thing

The researchers discovered that low clouds can actually make gases like oxygen and ozone easier to detect, because these clouds reflect more light without blocking the gases above them. On the other hand, high clouds can make it harder since they can hide the gases from view. They tested different cloud types using real data from Earth as seen in Figure 2. They looked at five common cloud types, like stratus (flat and low), cirrus (high and wispy), and deep convective clouds (tall, thunderstorm-like), and compared them to their model clouds (labelled as CARMA in the figure).

plot demonstrating how different types of clouds affect our ability to detect oxygen and ozone on an Earth-like exoplanet

Figure 2: The figure shows how different types of clouds affect our ability to detect oxygen (blue) and ozone (red) on an Earth-like planet. The dashed lines show the results without clouds, while the bars show what happens when clouds are present. Solid bars represent larger cloud droplets, and striped bars represent smaller ones, which reflect more light. The figure shows that most cloud types — especially low clouds like stratus and thick storm clouds — actually make it easier to detect these gases, particularly when droplets are small. Only high, thin clouds (cirrus) slightly reduce oxygen detection, and even then, the effect is small. This is the article’s main finding: while clouds can block light in some observation methods, for direct imaging of reflected light, they often help us see signs of life better. The cloud types are based on real Earth data while the authors’ simulated cloud model is labelled as CARMA. [Yang et al. 2025]

They found that most clouds improved detection, especially if the cloud droplets were small (as they reflect more light). Stratus clouds and deep convective clouds gave the strongest boost to detection, because they have a lot of water and are either low (stratus) or extend through many layers (deep convective). Ozone saw the biggest bump in detectability as it is concentrated higher in the atmosphere, which means that it is in the region above most clouds where the increased reflection from the cloud layer below makes it easier to spot. This means that unlike the case for transit spectroscopy where clouds interfere with the detection of gases, for direct observations of the reflected light, clouds may actually be a good thing. This insight into the role of clouds in exoplanet atmospheres not only refines our current understanding but also helps guide the design of future telescopes, like the HWO, and our search for life on these remote worlds.

Original astrobite edited by Maria Vincent.

About the author, Kasper Zoellner:

I have a Master of Science in astronomy and I am currently working towards a PhD in physics and educational science. My greatest passion is the search for exoplanets and how stellar variability may influence the possibility of life. I am also interested in science outreach, education, and discussing what sci-fi novel to read next!

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