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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: An In-Depth Study of Gamma Rays from the Starburst Galaxy M82 with VERITAS
Authors: The VERITAS Collaboration
Status: Published in ApJ

Starbursts: Not Just a Candy!

Cosmic rays are charged particles (electrons, protons, and atomic nuclei) that we’ve known about for more than a century. These particles notoriously zig and zag around the universe due to magnetic fields that attract them and then shoot them off in whichever direction the field goes. This makes it really hard to figure out what’s making them, especially because we detect them up to really high energies (petaelectronvolt-scale) — thousands of times more energetic than the particles accelerated at accelerators like the Large Hadron Collider! The mystery of what out there in the universe is making cosmic rays at these high energies has plagued astronomers ever since we discovered that cosmic rays exist in the first place.

Luckily, there are other ways to figure out where these enigmatic particles are made, including using plain old light — namely, gamma rays. Cosmic rays produce gamma rays in all sorts of different interactions with the material in the sources where they’re born. In other words, a cosmic-ray source should also be a gamma-ray source! By looking at how the gamma rays from a given astronomical object are distributed in brightness and energy (i.e., the spectral energy distribution), we can figure out what sort of cosmic rays make the gamma rays we observe and identify the big cosmic-ray factories of the universe.

Starburst galaxies (often just called “starbursts”), as their names imply, are galaxies that are forming stars very quickly — at rates 10–30 times higher than the Milky Way. This is probably just a phase, though, since these galaxies will quickly use up all their star-forming material (i.e., gas and dust) and will need to wait for this material to be re-released in supernovae or planetary nebulae when their stars eventually die.

We’ve long thought that starbursts might be cosmic-ray factories, as they host several high-energy processes such as supernovae and stellar winds launched by massive stars, hitting the dense material in star-forming regions. Since these processes don’t occur on anywhere near the same scales in our own Milky Way galaxy, we need to look elsewhere to understand if these processes are responsible for cosmic-ray production.

VERITAS gamma-ray telescopes

Figure 1: The VERITAS gamma-ray telescopes, which are located in southern Arizona, USA. [Center for Astrophysics | Harvard & Smithsonian]

Today’s authors look at the nearby starburst galaxy Messier 82 (also known as M82 or the Cigar Galaxy for its distinctive oblong shape; see the image at the top of this post) using 335 hours of data taken over 15 years of observations with the Very Energetic Radiation Imaging Telescope Array System (VERITAS) gamma-ray telescopes (Figure 1). They dive deeper into M82’s gamma rays than ever before and try to piece together what sorts of cosmic rays might be making these gamma rays. If starbursts are cosmic-ray factories, it’s also possible that the galaxy’s brightness can tell us directly the number of cosmic rays it’s made during star formation episodes, allowing cosmic rays to be studied much more easily than ever before.

Long Time, No Gammas

Today’s article follows up on a previous attempt to study M82 with VERITAS in 2009, which frustratingly resulted in the weakest detection VERITAS has ever reported — even after 137 hours of observations! More than a decade later, the VERITAS collaboration is back with a solid detection of gamma-ray emission from M82 (see Figure 2) and enough data to give M82 the attention it deserves!

sky map of the region surrounding M82

Figure 2: Sky map of the region surrounding M82, showing the statistical significance that the gamma rays observed aren’t just random background gamma rays or cosmic rays (higher significance is better!). The angular resolution of gamma-ray telescopes is not very good compared to other wavelengths. This can be seen in the inset, which shows the contours of optical data (white) and radio data (blue), with the best-fit and location of the VERITAS data denoted by the black circle and cross. The white circle in the bottom left shows VERITAS’s point spread function, which dictates the resolution of the image. [VERITAS Collaboration 2025]

It’s All in the Spectrum!

Even though M82 is 12 million light-years away (or more than a billion trillion kilometres), we can still learn an incredible amount of information about its subatomic particles, which are over half a million times smaller than a single human hair! The authors accomplish this by looking at the spectral energy distribution (see Figure 3), which shows how M82’s brightness changes with the energy (or frequency) of the gamma rays and any other light we observe.

leptonic and hadronic fits to the gamma-ray emission from M82

Figure 3: The leptonic and hadronic fits to the gamma-ray emission from M82, with Fermi-LAT data in black and VERITAS data in green. The leptonic (electron-only) model is shown by the green dashed line (called bremsstrahlung or braking radiation). The hadronic components are any of the pink, blue, or red lines, with each representing different average particle masses (denoted here with the particle’s rigidity, s, which is sort of a proxy for mass — or more precisely, how easily the particle is deviated by magnetic fields). They infer the types of particles from our own galaxy’s interstellar medium (ISM) and assume that M82 should be similar. All of these components are needed to find a fit to the data, as represented by the black solid line. [VERITAS Collaboration 2025]

The authors use simulations of how the gamma-ray spectral energy distribution would look if all the gamma rays were produced by only electrons, only protons/nuclei (together called hadrons), or a mix of both, in order to create models to fit the observed data. The reason for the distinction between particles is that electrons are the much less exciting cousin to protons and nuclei. (Sorry, electrons.) Electrons are light and fairly easy to accelerate but lose their energy pretty quickly, meaning that they can’t make up most of the high-energy cosmic-ray population that the authors are interested in. We don’t know of any astronomical sources that produce the hadrons we detect on Earth, so nailing down M82 as a hadronic source would be huge for tracking down these pesky cosmic-ray factories.

What gets a little bit hairy is that hadronic particle interactions (protons/nuclei hitting things, accelerating, decaying, etc.) will also make a bunch of electrons called secondary electrons in the process, making it so that the authors are unlikely to see the proton/nuclei-only scenario. The spectrum is more likely to look more like a blend of both electrons and hadrons, even if electrons aren’t initially involved. These electrons are created after sudden bursts of star formation produce a bunch of cosmic rays, which will go on to make these secondary electrons that will stay within the galaxy over much longer timescales, leaving a lasting imprint of the cosmic-ray production that can be measured long after the star formation stops.

The authors compare leptonic (electron-only) and hadronic models to the observed gamma-ray data, to see which particles are responsible for making the gamma rays. They find that at least some hadronic component is needed to fit the observed gamma-ray data from the Fermi Large Area Telescope (Fermi-LAT) and VERITAS (see Figure 3), meaning that M82 is probably making cosmic rays that are protons and nuclei. They can also infer properties of the cosmic rays, such as the maximum energy of 60 teraelectronvolts, which is really impressive but doesn’t quite make it to the petaelectronvolt benchmark of the mystery cosmic-ray population (1,000 times the energy of M82’s particles). We know supernovae can get close to this benchmark, but we still don’t know what’s producing the higher-energy particles.

Star Light, Star Bright, Starburst!

Starbursts are promising sources that might be producing the elusive high-energy cosmic rays that astronomers have been hunting for more than a century. They also give us a larger sample size of star-powered sources that may allow us to gain more understanding about the smaller populations of supernova remnants and massive stars that exist in our own Milky Way. With the next-generation gamma-ray telescopes coming online soon (like the Cherenkov Telescope Array Observatory, which can detect gamma-ray sources in one-tenth the time it takes current-generation telescopes like VERITAS), hopefully studying these challenging and gamma-ray-dim sources will only be easier and more fruitful from this point forward!

Disclaimer: Today’s author was an author on this research article as a member of the VERITAS collaboration but was not directly involved in this project.

Original astrobite edited by Pranav Satheesh.

About the author, Samantha Wong:

I’m a graduate student at McGill University, where I study high energy astrophysics. This includes studying all sorts of extreme environments in the universe like active galactic nuclei, pulsars, and supernova remnants with the VERITAS gamma-ray telescope.

cloud-9 neutral hydrogen contour map

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: Examining the Nature of the Starless Dark Matter Halo Candidate Cloud-9 with Very Large Array Observations
Authors: Alejandro Benítez-Llambay et al.
First Author’s Institution: University of Milano-Bicocca
Status: Published in ApJ

Astronomy, in many ways, is the study of light — in every wavelength that exists — coming at us from light-years away. But most of the mass in our universe is made of dark matter, a material that neither emits nor reflects any light. So, how exactly are we supposed to find this dark matter? Well, the dominant theory of what our universe is made of, Lambda cold dark matter (ΛCDM), predicts that this dark matter can form small halos — regions of gravitationally bound matter — that host reservoirs of cold gas but no stars. While we cannot directly observe dark matter, this cold gas can reflect light at radio wavelengths. Finding these dark halos, referred to as reionization-limited neutral atomic hydrogen clouds (RELHICs), is therefore rather important to confirm ΛCDM. The authors of this article are attempting to do just that by taking a close look at Cloud-9, a potential RELHIC.

How to “See” in the Dark

Cloud-9 was first discovered in 2023 when a team of astronomers noticed an excess of neutral hydrogen (HI) gas with no bright stars around it, near the spiral galaxy Messier 94 (M94). This discovery was made with the Five-hundred-meter Aperture Spherical radio Telescope (FAST), which doesn’t have the best resolution. For reference, this article found Cloud-9’s diameter to be roughly 3 arcminutes in the sky, while FAST’s resolution is 2.9 arcminutes. So, the authors of this article decided to look at Cloud-9 again, this time with the Very Large Array (VLA), an array of radio telescopes that can pick out more of the structure of this system.

With this upgraded resolution, the authors were able to get a clearer picture of the shape of Cloud-9 and compare it to the previous study (see Figure 1). They found that Cloud-9 was slightly smaller and much more lopsided than previously thought. This funky shape is likely due to gravitational interactions with the larger nearby galaxy M94, causing the gas in Cloud-9 to squish and stretch.

neutral hydrogen density contours for Cloud-9

Figure 1: Left: The HI gas column density from the previous FAST observations. [Benítez-Llambay & Navarro 2023] Right: The HI gas column density from the VLA observation in this article. [Benítez-Llambay et al. 2024] Corner circles represent the resolution of each telescope and the x and y axes are the position on the sky. Note the scale of the axes in each plot; the right plot is a zoomed-in version of the left.

RELHIC or Just RELHIC-tively Dim?

To determine if Cloud-9 really is a RELHIC, the authors needed to compare its HI radial density profile to the profiles of simulated RELHICs. Density profiles are a good tool to use here since although we don’t fully understand what dark matter is, we do know how it will affect things around it gravitationally. If the only matter hosted by Cloud-9 is HI gas and dark matter, then that gas will have a specific distribution that we can observe. If other baryonic matter is hosted by Cloud-9 that we just aren’t picking up right now, it will affect that density profile.

The authors found that for a detailed, general simulation the profiles did not match well, specifically in the outer regions. But when they compared it to a sphere of gas with a constant, specific temperature, they were able to get the fits to line up (see Figure 2). However, the authors point out that these simulations are isolated, meaning there is no big galaxy next to them affecting their shape, unlike Cloud-9.

observed and modeled neutral hydrogen density

Figure 2: Left: Comparison of Cloud-9’s HI profile (grey dots) to a general simulated RELHIC’s profile (green line) and a simulated RELHIC at a specific temperature (red line). Right: Comparison of Cloud-9’s profile (black dots) to Leo T’s profile (orange line). Although the positions are shifted, the slopes of the profiles match. [Benítez-Llambay et al. 2024]

The authors also tried to test another explanation for Cloud-9’s apparent lack of stars: the stars are there but just too dim for us to see right now. The Milky Way sits near many ultra-faint dwarf galaxies, which are small and have quite dim stellar populations. We’ve only just developed telescopes in the last few years that can take in enough light to see these galaxies, and we might not be able to detect stars in an ultra-faint dwarf galaxy as far away from us as Cloud-9. The authors compare the HI density profile of Cloud-9 to that of Leo T, a nearby ultra-faint dwarf galaxy. They find that these profiles match up better than for the general RELHIC simulations, particularly in the innermost regions of Cloud-9 and Leo T.

What Are the Next Steps?

The authors conclude that, as of right now, they can’t definitively say whether Cloud-9 is or is not a RELHIC, but there are a few things astronomers can do to clear things up. First, theorists can re-run the RELHIC simulations with halos that have been affected by gravity like Cloud-9. This will allow them to better compare their observations to the simulations.

Second, observers can image Cloud-9 with an optical telescope that is powerful enough to detect any stars that could be there. They suggest the Hubble Space Telescope since it would be able to detect the brightest handful of stars in the potential dim population. JWST would be an even better choice, with its even deeper imaging capabilities, but it is very difficult to get observing time on it. (JWST recently received the most proposals in one year for any telescope ever!)

We will likely have to wait a bit for a definitive answer on the nature of Cloud-9, but either way the authors are excited by this gas cloud. Either it is the first starless dark matter halo, a confirmation of one of the predictions of ΛCDM, or it is the most distant ultra-faint dwarf galaxy ever detected! Although Cloud-9 is not much to look at right now, you should still definitely keep your eye on it.

Original astrobite edited by Maggie Verrico and Cole Meldorf.

About the author, Veronika Dornan:

Veronika is a final-year PhD candidate at McMaster University. Her research is in observations of extragalactic globular star clusters and what they can tell us about galaxy evolution and dark matter distribution in the universe.

Illustration of an exoplanet orbiting a white dwarf

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 Fate of Oceans on First-Generation Planets Orbiting White Dwarfs
Authors: Juliette Becker, Andrew Vanderburg, and Joseph R. Livesey
First Author’s Institution: University of Wisconsin–Madison
Status: Published in ApJ

Toward the ends of their lives, stars like the Sun are destined to expand into red giants, expel their outer layers, and leave behind their Earth-sized cores as white dwarfs. What happens to any planets during this stage of stellar evolution is far more uncertain. Planets sufficiently close to their host star are expected to be engulfed as the star expands into a red giant, including our very own Earth. However, some planets can survive or perhaps even form during white-dwarf formation, and we know of a handful of planets and planet candidates around white dwarfs from transits, direct imaging, and detection of mid-infrared excess.

Planets orbiting white dwarfs are particularly attractive targets for searches for biosignatures and, more speculatively, technosignatures, because their atmospheres are easier to detect due to their stars’ small sizes. We have yet to find a terrestrial planet orbiting a white dwarf, let alone one in the habitable zone, but searches are ongoing. Another important factor for habitability is the presence of water, and today’s article investigates whether a planet could retain an ocean through its star’s evolution and end up in the habitable zone, where life might exist.

Stellar Ocean Loss

To set the scene, let us imagine an ocean-bearing planet orbiting a Sun-like star evolving off the main sequence. Even if the planet survives engulfment, it could easily lose its water and become likely uninhabitable if the following steps occur: 1) high surface temperatures evaporate the ocean into the atmosphere, 2) high-energy photons dissociate the water molecules into hydrogen and oxygen, and 3) those atoms escape into space and do not re-condensate.

As the star leaves the main sequence, the planet responds to changes in the star’s size, brightness, and mass. The top four panels of Figure 1 show variations in stellar and planetary properties during this stage of stellar evolution. During the asymptotic giant branch phase, the star brightens considerably and expels ~30–80% of its mass, causing the planet’s orbit to expand. X-ray and extreme-ultraviolet flux from the star can cause the planet to lose atmospheric mass from photoevaporation (i.e., when high-energy photons deposit sufficient energy for particles to reach escape velocity). As the planet’s surface temperature increases, the ocean could evaporate, creating a predominantly water vapor atmosphere. If the extreme-ultraviolet flux is sufficiently high such that oxygen and/or hydrogen escape the atmosphere, the ocean is lost. The bottom panel of Figure 1 shows that water retention becomes more difficult if the planet’s initial orbital radius is small.

plot of evolution of stellar parameters

Figure 1: From top to bottom, stellar luminosity, stellar mass, planetary semi-major axis, and planetary temperature as a star becomes a red giant and subsequently a white dwarf. The bottom panel shows the fraction of the ocean retained for an Earth-like planet with various values of initial semi-major axis. [Becker et al. 2025]

Tidal Ocean Loss

Not only does the ocean have to survive the aforementioned complications, but the planet needs to end up in the habitable zone despite starting far away from the star. The planet must be perturbed to achieve high eccentricity and then tidally circularize its orbit in the white-dwarf habitable zone (~0.01 au). Planet–planet scattering (i.e., dynamical interactions between planets in a multi-planet system) is the most plausible mechanism to drive a planet inwards. These interactions could be delayed substantially after white-dwarf formation. Since white dwarfs cool and emit less extreme-ultraviolet flux over time, delaying inward scattering could enhance water retention.

Large eccentricity helps drive a planet inwards, but it also stokes tidal heating that could increase the surface temperature. The exact effects on ocean evaporation and atmospheric mass loss are highly sensitive to how energy is dissipated. In general, tidal heating can result in Jeans escape, in which atmospheric particles reach sufficient thermal motion to escape into space. The authors find that while tidal heating is effective at evaporating the ocean into the atmosphere, it is less effective than the extreme-ultraviolet-driven mechanism at driving atmospheric mass loss.

Takeaways

plot of ocean survival percentage as a function of orbital distance and temperature at scattering

Figure 2: The effects of white-dwarf scattering temperature and final orbital radius on ocean survival. The authors use an Earth-like planet with an initial orbital radius of 5 au and varying eccentricity. [Becker et al. 2025]

There are a variety of factors that affect whether an ocean can be retained, including the planet’s initial orbital radius, the initial quantity of water, the stellar extreme-ultraviolet flux, the time at which the planet is scattered inwards, and the planet’s final orbital radius. To hold onto water, a planet must either start in a distant orbit (greater than 5–6 au for an Earth-sized ocean) or start with a massive quantity of water. Since large extreme-ultraviolet flux is required to drive water loss via photoevaporation, delaying inward scattering until the white dwarf cools aids ocean survival, as shown in Figure 2, which also shows that a larger final radius enhances water retention. If certain conditions are met, an ocean could be retained by a planet orbiting a white dwarf. This is an exciting finding for those searching for planets and signs of life around white dwarfs.

Original astrobite edited by William Smith.

About the author, Kylee Carden:

I am a second-year PhD student at The Ohio State University, where I am an observer of planets outside the solar system. I’m involved with the Roman Space Telescope, a small robotic telescope called DEMONEXT, and exoplanet atmospheres. I am a huge fan of my cat Piccadilly, cycling, and visiting underappreciated tourist sites.

Fornax dwarf galaxy

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: Low-Mass Galaxy Interactions Trigger Black Hole Activity
Authors: Marko Mićić et al.
First Author’s Institution: The University of Oklahoma
Status: Published in ApJL

Most galaxies have a central supermassive black hole. Over time, these black holes grow by eating up lots of gas and stars, and occasionally by merging with another black hole. As telescopes have improved, and especially with the recent launch of JWST, astronomers have discovered supermassive black holes that are more massive than we originally thought black holes should be in the early universe (you can read more about black hole growth here and here). This observation implies that black holes can grow very quickly during the first 700 million years of the universe’s existence.

But understanding this early phase of black hole growth is no easy task. In the early universe, the majority of galaxies were low-mass, dim dwarf galaxies that are difficult to observe, even with our strongest telescopes. One way that astronomers can overcome this challenge is by studying nearby dwarf galaxies that we think resemble early universe dwarf galaxies.

When a black hole is growing and eating a lot of gas, we call it an active galactic nucleus, or AGN. The process of black hole growth also releases a huge amount of energy, making an AGN very bright, especially in X-rays. Astronomers think that black holes build up a lot of their mass during these AGN phases, but it’s unclear what triggers the beginning of an AGN phase and whether AGN triggers are more common in the early universe.

One possibility is that galaxy mergers trigger AGN phases. Studies have found evidence that a higher percentage of galaxies that have recently undergone mergers also host an AGN, supporting this idea. However, these studies focus on galaxies that are much more massive than early universe galaxies, making it difficult to say whether we can extrapolate these results and apply them to low-mass dwarf galaxies.

The authors of today’s article set out to answer the question of whether galaxy mergers could trigger enough AGN activity to explain the existence of supermassive black holes in the early universe. To do so, they studied pairs of dwarf galaxies that are much closer to us but might be representative of early universe galaxies.

images of four dwarf galaxy systems

Figure 1: Four dwarf galaxy systems found by today’s authors. The red boxes show the galaxies that they’ve determined to be close to each other. The original images are from the 3D-HST survey. Click to enlarge. [Adapted from Mićić et al. 2024]

To find these elusive pairs of dwarf galaxies, the authors used data from the 3D-HST survey, which was conducted using the Hubble Space Telescope and observed over 200,000 galaxies. From this huge catalogue, they selected galaxies with at least 10 times fewer stars than the Milky Way. They then inspected the images taken of these galaxies to see whether there was at least one other dwarf galaxy within 100 kiloparsecs (that’s around 326,000 light-years or 3×1018 km!). Using this method, they identified 93 systems that contained at least two nearby dwarf galaxies. As you can see in Figure 1, these dwarf systems vary in terms of the number of galaxies in the system and the distance between each galaxy.

For each dwarf galaxy in a pair or group, the authors also identified a galaxy at a similar distance from us with a similar mass but without any nearby neighbours. This sample of isolated galaxies acted as the control sample against which the authors could compare their results.

To determine whether each galaxy was hosting an AGN, the authors crossmatched their galaxies with X-ray data taken by the Chandra X-ray Observatory. Since the AGN in these galaxies are expected to be fairly faint, very high-quality X-ray data are needed in order to definitively say whether a galaxy has an AGN or not. As a result, the authors were only able to check for AGN in 29 of their dwarf-galaxy-pair systems, and they found seven AGN within this subsample. In the control sample, they only found three AGN in a sample of 183 galaxies.

plot of AGN frequency as a function of galaxy stellar mass

Figure 2: The AGN frequency (the two blue points) for interacting dwarf galaxies is much higher than the AGN frequency for the control sample (black point) and the AGN frequency reported in previous papers (red, yellow, green, and purple points). Click to enlarge. [Mićić et al. 2024]

Since the dwarf galaxy pairs are fairly close to each other, Chandra is unable to separate out the light from each galaxy, and the authors are unable to say whether both dwarf galaxies have an AGN, or just one of the two. If every single galaxy in the sample hosts an AGN, then the AGN fraction might be as high as 16.4%, but if only one of the pair hosts an AGN, then the fraction may be as low as 9.8%. Regardless, both of these fractions are significantly higher than the AGN fraction in the control sample, which was just 1.6%, and are generally higher than the AGN fractions reported in other articles (see Figure 2).

The results of today’s article support the idea that dwarf galaxy mergers might be a trigger of AGN activity. Since the majority of galaxies in the early universe are dwarf galaxies, this might result in a higher AGN fraction, which could help to explain how black holes are able to grow so quickly in the early universe. Further X-ray observations of the dwarf galaxy pairs identified by the authors will help to confirm this result and better constrain the AGN fraction in dwarf galaxy mergers — so stay tuned!

Original astrobite edited by Archana Aravindan.

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.

X-ray image of Kepler's Supernova remnant

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: 1991T-Like Type Ia Supernovae as an Extension of the Normal Population
Authors: John T. O’Brien et al.
First Author’s Institution: Michigan State University
Status: Published in ApJ

Famously, Type Ia supernovae have been used to measure the local Hubble constant, or the rate at which our universe expands. These objects earned the nickname “standard candles” since their near-constant intrinsic luminosities allow us to measure distances in space. Slowly but surely, however, we’ve learned that some of our standard candles aren’t that “standard” after all…

Branch classification diagram for Type Ia supernovae

Figure 1: Example of a “Branch classification” diagram for Type Ia supernovae. This figure compares the width of two silicon lines in Type Ia supernovae. Four groups are shown: shallow silicons (SS), broad lines (BL), cools (CL), and core normals (CN). Event SN 1991T is a member of the shallow silicons group (green triangles), indicating that the widths of the minor and major silicon lines are smaller than normal Type Ia supernovae (core normals). Click to enlarge. [Burrow et al. 2020]

Historically, Type Ia supernovae were proposed to develop from the transfer of mass between two stars, where the star receiving the mass was a carbon–oxygen white dwarf — the core of a low-mass to intermediate-mass star that’s reached the end of its life. After the white dwarf accretes a certain amount of mass, it explodes as a Type Ia supernova. Spectroscopic studies of these supernovae over the decades have shown a wide range of absorption features, one major absorption line being silicon, a key element produced in the explosion. In fact, a subclassification scheme of Type Ia supernovae — often referred to as the Branch classification — emerged based on the relative strengths of particular absorption features commonly identified in the spectra of these events (see Figure 1). One of these subclassifications is “shallow silicon,” which signifies a lack of silicon produced in the explosion. This subclassification (compared to other subclassifications in Figure 1) shows how Type Ia supernovae are like snowflakes: they have very similar structures yet vary in detail.

The supernova SN 1991T was the first observed event of its kind. What was so special about it? This event was considered over-luminous, or more luminous than the typical “near-intrinsic luminosity” of the average Type Ia supernova. Later, as observations improved, more events like SN 1991T were detected, contributing to the growing class of aptly named “1991T-like” events. The spectra of these events have shallow silicon lines compared to the normal range of Type Ia supernovae. The peculiarity of these absorption lines hints at something unique about these events, and the answer lies in studying the ejecta, or the ejected material in which chemical elements are produced. This article is a step toward understanding what differentiates these events from the norm and what we can infer about their origins.

Outside of this work, recent hydrodynamic simulations of various progenitor models, or stellar origins, have successfully recreated some of the observable signatures of Type Ia supernovae, including synthetic, or computed, optical spectra of theoretical events. Except, as previously mentioned, the observable signatures of Type Ia supernovae can vary quite a bit amongst all these subtypes and classifications! Instead of hydrodynamic simulations, the authors of this article chose to reconstruct the supernova ejecta using Bayesian inference and active learning conducted on early-time (within a few days after explosion) optical spectra of already observed normal and 1991T-like events. This is the time when 1991T-like events show their features! After training the model on this data, the authors developed a model to link the optical spectra and the ejecta properties corresponding to normal and 1991T-like events.

fraction of intermediate-mass elements versus ionization ratio

Figure 2: A plot showing the fraction of intermediate-mass elements (IME) as a function of the ionization ratio of the authors’ simulations. Moving to the right on the bottom axis indicates higher ionization states, whereas moving up on the left axis indicates more intermediate-mass elements for a given total ejecta mass. The break between blue stars (normal Type Ia supernovae) and orange stars (1991T-like supernovae) is called the “turnover.” Because the turnover is fairly smooth, it suggests that the progenitor, or stellar origin, of 1991T-like events might be similar to normal events. Click to enlarge. [O’Brien et al. 2024]

The team’s emulator successfully recreated both normal and 1991T-like events, at least with 68% confidence (think one sigma!). Furthermore, the authors discovered that the variety in the parameters used in their model illuminates some differences between these 1991T-like events and normal Type Ia supernovae. Remember those silicon features? They recreated those pesky absorption lines, particularly the major iron and silicon features experts look for. Their model successfully recreated silicon absorption features that were suppressed, or not as deep. This indicates a low fraction of intermediate-mass elements, which range from lithium to iron, produced in the explosion compared to the total mass. They also matched the deep, major iron line seen in 1991T-like events. Fewer intermediate-mass elements in 1991T-like supernovae suggest that these elements exist at higher ionization states than in normal Type Ia supernovae (see Figure 2). This suggests that there isn’t just a single mechanism that produces a 1991T-like supernova; it’s likely a combination of different physical processes.

The question now becomes: what can we learn about 1991T-like origins from this? Can a single progenitor model lead to different pathways? Or do we need different progenitor models to explain these differences in spectroscopic features? The authors believe fewer intermediate-mass elements and higher ionization states hint at normal and 1991T-like events sharing similar progenitor systems. In other words, 1991T-like events might just be an extension, or extreme, of the normal population. Perhaps the candle just burned a bit too bright!

Aside from this work, in addition to these over-luminous 1991T-like events, there also exists another interesting class of Type Ia supernovae dubbed “super-luminous,” which are roughly one, maybe two, magnitudes brighter than normal Type Ia supernovae. (Only in astronomy could the words over-luminous and super-luminous mean different things, right?) Because of this, researchers advocate for Type Ia supernovae to be called “standardizable” candles instead because, as you now know, their intrinsic luminosities really aren’t that uniform after all.

Original astrobite edited by Ansh Gupta and Dee Dunne.

About the author, Mckenzie Ferrari:

I’m a grad student at the University of Chicago. Most of my research focuses on simulations of Type Ia supernovae and galaxy formation and evolution.

field of stars with a star brightened by gravitational microlensing

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: On Finding Black Holes in Photometric Microlensing Surveys
Authors: Zofia Kaczmarek et al.
First Author’s Institution: Lawrence Livermore National Laboratory; Heidelberg University
Status: Published in ApJ

Searching for stellar-mass black holes is no simple task — how do you look for an object floating in the vastness of space, hundreds or thousands of light-years away, that is at best the size of Houston, Texas, and emits no light? As our surveys of the night sky become more and more regular and increase in resolution, there is hope that we will be able to observe more and more chance alignments of these objects with stars, generating an observable effect known as microlensing. This mechanism provides us with a way to pick a proverbial black hole needle from the galactic stellar haystack, but the data we get from these surveys are still difficult to process efficiently. Today’s article introduces a new method for rapidly assessing the chances that a given microlensing event is indeed caused by a wandering black hole, allowing astronomers to make more effective decisions about which events to follow up on with targeted observation campaigns.

A Microlensing SOBH Story

While astrophysical black holes were once squarely in the realm of speculative science fiction, it is now commonplace to find these extreme objects through a variety of techniques. One such technique involves observing a star that is moving around in a binary system, making its motion regular and predictable. Astronomers can use this regular motion to deduce the mass of the star’s partner — and if there’s no visible signal associated with the companion, it may turn out to be a black hole.

Another more recent technique that has proven successful in finding these exotic objects involves listening for the gravitational waves produced when a black hole merges with another compact object like a black hole, neutron star, or white dwarf. From these observations, astronomers can learn about the overall population of black holes in our universe, and by proxy can learn about the last stages of stellar evolution. But relying on these measurements alone would generate a biased picture of stellar evolution, because they only pick out black holes that formed in (or evolved into) binary systems. This leaves us without much information about the non-negligible fraction of stars (and therefore black holes) that prefer the “single life.”

animation of gravitational microlensing

Figure 1: Cartoon depiction of the process of gravitational microlensing. A foreground object intersecting our line of sight to a bright background object can cause optical distortions like brightening and doubled images. [NASA Ames/JPL-Caltech/T. Pyle]

This is where the topic of today’s article comes in: microlensing is a phenomenon wherein any object with mass, through the (not-quite) magic of Einstein’s General Theory of Relativity, is able to deflect rays of light like a lens, occasionally magnifying that light in a particular direction. This is useful for astronomers, because if a black hole passes in front of a star and the alignment is just right, we might observe a temporary brightening of that background star. This is occasionally paired with other optical distortions like the formation of multiple images of the star. Figure 1 depicts this process in more detail. Microlensing is a great way of looking for stellar-origin black holes (SOBHs), but it comes with inherent limitations due to the chance nature of these alignments and the subtlety of the effect. In fact, to date (October 2024) there has only been one candidate microlensing event that was confirmed to be a black hole after follow-up observations were made with the Hubble Space Telescope. This is despite the fact that collaborations like the Optical Gravitational Lensing Experiment (OGLE) have cataloged more than 10,000 microlensing events to date.

One Quick Classification Trick

For the most part, microlensing events are found by looking for subtle changes in the light coming from a star — this observation is a photometric measurement of the microlensing event. Photometric data for a microlensing event are generally able to provide at least some constraints on two important microlensing parameters: the Einstein timescale 𝑡𝐸 (related to how long the foreground object lenses the background as it passes by) and the microlensing parallax 𝜋𝐸, which results from Earth’s acceleration towards or away from a particular lensing event. Unfortunately, from these variables alone it can be hard to confidently determine the nature of the lensing object, motivating attempts to make higher-resolution follow-up observations of these events. Telescopes with strong spatial resolution can sometimes pick up on the way the lensing object subtly distorts the apparent position of the background star. These so-called astrometric observations can help pin down important information such as the size and/or mass of the lensing object, letting astronomers confirm the presence of a SOBH or another object of interest.

plots of distribution of two microlensing parameters

Figure 2: This plot from today’s article shows the distribution of two microlensing parameters produced by various lensing sources. The separation of SOBHs in this parameter space indicates that measurement of these parameters in photometric data may allow for the rapid identification of microlensing events caused by SOBHs. [Kaczmarek et al. 2025]

One problem that arises in this process, however, is the fact that astrometric follow-up is difficult to conduct and can take up valuable time on busy telescopes like Hubble. For this reason, it is important to try to do as much as possible with the limited photometric data products and ensure that only the follow-up campaigns that are most likely to succeed are performed. The authors of today’s article worked on this particular problem by developing a fast and flexible classification program that assesses the likelihood of a given microlensing event fitting into a given source category using only the photometric estimates of 𝑡𝐸, 𝜋𝐸, and an underlying galactic stellar population model. By simulating the distribution of stars, white dwarfs, neutron stars, and SOBHs in the galaxy, the authors were able to simulate the expected distributions of lensing parameters 𝑡𝐸 and 𝜋𝐸 they produced. Understanding these underlying distributions allowed the authors to perform Bayesian estimations of the probability that a given photometrically observed microlensing event was caused by a particular type of lens. In Figure 2, the distributions of events from different sources given by a representative galactic population model are shown in 𝑡𝐸 and 𝜋𝐸 space. Promisingly, SOBH lensing events tend to be well separated from stellar, white dwarf, and neutron star events in these simulations.

After introducing their classification pipeline, the authors applied it to an existing microlensing dataset from the OGLE collaboration. This dataset contained nearly 10,000 events, from which the classification pipeline returned 23 high-probability SOBH candidates that were agreed upon across all three models of star-to-black-hole evolution (“initial–final mass relations”) the authors used. Applying further selection rules to find candidate events that could potentially be observed by the Gaia telescope, the list was whittled down to just four events. Unfortunately, all four of these remaining candidates were found to be unlikely to produce significant astrometric deviations, meaning we will likely have to wait for larger microlensing surveys coming up in the near future for a solid chance of finding a new SOBH candidate with this method.

estimated 𝑡𝐸 and 𝜋𝐸 parameters for the only confirmed SOBH microlensing event

Figure 3: This plot from today’s article depicts the estimated 𝑡𝐸 and 𝜋𝐸 parameters for the only confirmed SOBH microlensing event compared against the regions of parameter space expected to correspond to white dwarfs (blue) and SOBHs (green). The minimal overlap with the green region indicates that this event may have been an outlier compared to galactic stellar population models. [Kaczmarek et al. 2025]

OB110462: A Chance Encounter?

Using a stellar-population-model-informed classification method like the one presented in this article may also allow us to directly examine weaknesses in these models. For example, if in the future we find many microlensing events that are later confirmed to be SOBHs but exist outside of the expected SOBH region of 𝑡𝐸–𝜋𝐸 parameter space, it could point us towards a flaw in the underlying population models. As of the publication of this article, however, we only have one confirmed SOBH microlensing event to compare to (denoted OB110462). Working with a sample size of one is pretty uninformative (to say the least), but the authors do note that this event is already somewhat of an outlier given their population model. In Figure 3, you can see the recovered 𝑡𝐸 and 𝜋𝐸 probability contour for OB110462 only barely overlaps with the region corresponding to SOBHs, and the contours fit more snugly in the region corresponding to white dwarfs. This tension is interesting, because even if it doesn’t point to a problem with the stellar population models, it could indicate that the successful confirmation of this event as a SOBH was an unlikely success, and so choosing to dedicate time on Hubble to do follow-up measurements was, in retrospect, a high-risk move that paid off.

Regardless of how things turned out with OB110462, this sort of analysis points to a more general benefit this classification scheme provides: it allows for a very rapid estimation of which microlensing events we should focus our attention on with follow-up observations. The authors propose that this makes their method ideally suited as an initial filter through which microlensing events can pass before more complicated analyses are performed. As surveys like the Vera C. Rubin Observatory Legacy Survey of Space and Time begin to take unfathomably huge amounts of time-domain data, the number of detected microlensing events is going to sharply increase, making it more important than ever that we think carefully about which events are worth following up on.

Original astrobite edited by Lindsey Gordon.

About the author, Lucas Brown:

I’m a graduate student at the University of California, Santa Cruz. My research involves figuring out how to use exotic phenomena like gravitational waves to learn about elusive astrophysical objects like primordial black holes or dark matter. Outside of physics I love playing piano, climbing, and spending time with my dog.

the MACE telescope

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: Very High-Energy Gamma-Ray Episodic Activity of Radio Galaxy NGC 1275 in 2022–2023 Measured with MACE
Authors: S. Godambe et al.
First Author’s Institution: Bhabha Atomic Research Centre
Status: Published in ApJL

the MACE telescope

Figure 1: The MACE telescope. [Khurana et al. 2023]

The Major Atmospheric Cherenkov Experiment (MACE) (see Figure 1) is a new ground-based gamma-ray telescope (specifically the type of telescope called an imaging atmosphere Cherenkov telescope or IACT) located near Hanle, Ladakh, India. Though the atmosphere is opaque to gamma rays, this can actually be used to our advantage. The particles created after a gamma ray interacts with atmospheric molecules travel faster than the speed of light in the atmosphere, creating a flash of optical light called Cherenkov radiation that is analogous to a sonic boom. Large optical detectors like MACE can use this Cherenkov radiation to directly measure the direction and energy of a gamma ray on the ground, even though the original photon is long gone.

Several other IACTs exist around the world, including the High Energy Spectroscopic System, the Major Atmospheric Gamma Imaging Cherenkov telescopes, the Very Energetic Radiation Imaging Telescope Array System, and the new Large-Sized Telescope, a prototype for the next generation array of gamma-ray telescopes like the Cherenkov Telescope Array Observatory. However, MACE is the IACT at the highest altitude (4,270 meters above sea level!) and is the third largest (after the Large-Sized Telescope and one of the High Energy Spectroscopic System telescopes), with an impressive light-collecting diameter of 21 meters of segmented mirrors. This makes MACE sensitive to lower-energy gamma rays than typical IACTs since low-energy gamma rays attenuate higher in the atmosphere and are dimmer, requiring larger mirrors and higher elevation. It’s important to look at this energy range (less than a few hundred gigaelectronvolts) since it bridges the sensitivity ranges of the Fermi Large Area Telescope (Fermi-LAT), a space-based gamma-ray telescope, and other IACTs.

In MACE’s first research article, the authors discuss observations of NGC 1275, a nearby radio galaxy. In just a month of observations, they discovered two gamma-ray outbursts from the source!

Does Jet Inclination Kill the Radio Star Galaxy?

Active galactic nuclei are understood to be supermassive black holes that accrete matter from their surroundings and often shoot out large jets that are larger than the galaxies that host them. For the very high energy (energies greater than 100 GeV) gamma rays, where IACTs operate, we expect to see mainly blazars, a class of active galactic nucleus where the jet points directly at Earth, beaming particles toward us through a process called Doppler boosting and producing gamma rays and other photons as they go. This beaming gives us bright and fast flares — bursts of gamma rays — whenever material falls into the jet.

What’s weird is that we also see flares from radio galaxies that are similar in brightness and speed to the flares from blazars. Since radio galaxies (named for having large radio lobes visible at the ends of the jets) are active galactic nuclei where the jet is misaligned from Earth and doesn’t beam directly at us, we’d expect them to be dimmer than they are. Think about looking sideways at a laser versus looking right into the laser. The latter is so bright that it will probably damage your eyesight (please don’t try this at home!), but the former is much dimmer. Observing and studying gamma-ray flares from radio galaxies is fun because they’re unexpectedly bright, and these observations are crucial for understanding how the flares are being powered.

spectral energy distributions

Figure 2: Spectral energy distributions composed of MACE, Fermi-LAT, and Swift Ultraviolet/Optical Telescope (ultraviolet) and X-Ray Telescope (X-ray) observations of the December flare (upper panel), January flare (middle panel), and the non-flaring period between the two flares (bottom panel). The dashed and solid lines represent the best-fit models for two different viewing angles of the jet. [Godambe et al. 2024]

New Year, New Flares

Today’s authors report on two flares from NGC 1275 that occurred in December 2022 and January 2023. Flares are unpredictable and often sporadic, so it’s impressive that two were seen within a month of each other!

Using data from Fermi-LAT and the X-ray/ultraviolet observatory Swift, they can construct a spectral energy distribution, which shows the brightness of the source across all observed energies (Figure 2). The authors fit different models to the spectral energy distribution to determine all sorts of parameters about the radio galaxy, like the size of the region that’s producing gamma rays, how tilted the jet is toward us, the maximum-energy gamma ray that can be accelerated in the jet, and more. These models are constructed by simulating the observed multi-wavelength photons from blobs of material that fall into jets of different configurations. The model that best fits the observed data should then be a good descriptor of the physical environment of the active galactic nucleus.

The authors find that the physical conditions for both flares are very similar. Consistent with other observations of NGC 1275 and other radio galaxies, they find a smaller Doppler factor and larger viewing angle (the “misalignment” of the jet with Earth’s line of sight). The “quiet” phase between flares seems to come from a reduction of either the Doppler factor — meaning that the particles in the jet aren’t being beamed as much — or an attenuation of the magnetic field strength, which makes it harder to accelerate particles to gamma-ray energies.

The authors conclude that more complicated jet processes must be happening for us to see these flares, such as different parts of the jet moving at different speeds or additional magnetic field acceleration before particles fall into the jet. The former scenario should increase the absorption of higher-energy gamma rays and make it impossible to see any gamma rays above 1 teraelectronvolt. The latter scenario requires particles to orbit large-scale magnetic fields that are the size of the active galactic nucleus’s event horizon (the radius at which light can no longer escape from the gravitational pull of the black hole), which makes it hard to see variability on timescales of less than a day.

Future observations are needed to see if higher-energy gamma-rays or faster flares are ever seen again from NGC 1275. If so, we’d need to go back to the drawing board to figure out other theories to explain how radio galaxies get so bright in gamma rays!

Original astrobite edited by Junellie Perez.

About the author, Samantha Wong:

I’m a graduate student at McGill University, where I study high energy astrophysics. This includes studying all sorts of extreme environments in the universe like active galactic nuclei, pulsars, and supernova remnants with the VERITAS gamma-ray telescope.

Vega

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: Small and Close-In Planets are Uncommon Around A-Type Stars
Authors: Steven Giacalone and Courtney D. Dressing
Authors’ Institutions: California Institute of Technology and University of California, Berkeley; University of California, Berkeley
Status: Published in AJ

Some of the most interesting articles in exoplanet science concern the discovery of new exoplanets. After all, most of us get into this field with dreams of discovery. Today’s article is as fascinating as it is empty of planets: the authors searched roughly 20,000 stars and found a whopping zero planets. What’s the deal?

While the Kepler mission’s survey that stared at a single patch of sky for four straight years searching for exoplanet transits has dominated exoplanet statistics for more than a decade, Kepler focused primarily on host stars with spectral types F, G, K, and M (i.e., FGKM stars). These stars all have temperatures less than about 7000K, and while there is a lot of variation among these types of stars, they are considered relatively Sun-like (our Sun is a G-type star). Through observing these stars, we were able to build up robust statistics on the occurrence rates of different kinds of planets. Astrobites has covered occurrence rate studies in the past (see these bites on small planets around M-dwarf stars, occurrence of systems with similar architecture to our own, and big planets around small stars). Essentially, the occurrence rate measures how many planets of a specified type (like “super-Earths” or “hot Jupiters”) are likely to be found if you survey a certain number of stars with a certain spectral type.

However, the Kepler mission did not observe enough A-type stars to measure the occurrence rate of different kinds of planets around hosts of this stellar type. A-type stars are hotter than our Sun, with temperatures between about 7500K and 10000K. They are bigger in both mass and radius than our Sun, and they emit more of their light in the ultraviolet portion of the electromagnetic spectrum. Very little is known about planetary systems around A-type stars, in large part due to Kepler’s blind spot, but also because these stars make for very poor targets in radial-velocity surveys. A-type stars have far fewer spectral lines than Sun-like stars and they spin much faster than our Sun, both factors that decrease radial-velocity sensitivity greatly compared to the more Sun-like stars. Most of what is known of planetary systems around A-type stars comes from direct-imaging surveys, which are only sensitive to massive Jupiter-size planets at very large separations from their stars.

Then, when the Transiting Exoplanet Survey Satellite (TESS) came along with the plan to observe most of the night sky, an opportunity to search for planets around more A-type stars became available. That’s where today’s article comes in. The authors used the TESS dataset to search A-type stars for small planets (between 1 and 8 Earth radii) on short orbits (orbital period less than 10 days). To say that this search was an immense labor is almost an understatement. The authors wrote a custom software pipeline to search through the dataset, identify potential transits, and then apply a few rounds of vetting on each candidate.

The authors first had to identify all the A-type stars in the TESS catalog — about 20,000 stars. Of these, the pipeline identified 299 transit candidates. Looking more closely at these with a complementary dataset, the authors ruled out many as false positives (mostly obvious-by-eye eclipsing binaries), leaving only 88 candidates remaining. Next, they inspected the candidates for secondary eclipses, which would indicate the transit is not planetary but stellar; this effort ruled out another half, leaving only 44 candidates. Next they tested for background eclipsing binaries, which can mimic planet transits, cutting more candidates so that only 10 remained. Lastly, they performed statistical tests on the leftovers by analyzing the way nearby stars get brighter or dimmer during the time of the transits to see if anything is correlated. In the end, they found that not one candidate passed and therefore the pipeline found zero planets.

Despite finding no planets, this null result is still very important. In this study, the null result was used to place constraints on the occurrence rates of different kinds of planets that orbit A-type stars. In particular, the authors found that sub-Neptune-sized planets occur six times less frequently around A-type stars than they do around FGKM stars. The authors dive into this result and point to earlier studies that show a decrease in planet occurrence as the host stars get hotter. In fact, this result is well in line with these earlier studies, but now the trend is finally investigated for the even hotter A-type stars, as shown in Figure 1. This is a fascinating result: big hot stars seem to host fewer planets than smaller, cooler stars. Why?

plot of sub-Neptune occurrence rate as a function of host star temperature

Figure 1: The occurrence rate of sub-Neptune planets versus host-star temperature. Previous studies show that sub-Neptunes are common around smaller, cooler stars. As host-star temperature increases, the occurrence of sub-Neptunes goes down. This has been noted in earlier works, but this work extends the temperature regime greatly at the hot end and shows that sub-Neptunes are very rare around hotter A-type stars. [Adapted from Giacalone and Dressing 2025]

The authors note a few caveats to their result. These A-type stars are known to pulsate more often than cooler FGKM stars, and this pulsation is imprinted into the flux measurements of the star, which can make it more difficult to find planets. Accounting for these pulsations is another project in itself, but it could explain why the team didn’t find any planets. Furthermore, the authors acknowledge that A-type stars spin so fast that they actually flatten out at the poles and bulge out at the equator. This in turn makes the high latitudes of the star brighter and the equator dimmer, thus finding small planets that orbit at higher inclinations becomes even more difficult. This effect, called gravity darkening, is essentially not a problem for FGKM stars.

Next, the authors discuss what their result means for the big picture of our understanding of planet formation. First, they discuss if this could be part of an observing bias. There are two ways that A-type stars make finding transits more difficult. A-type stars emit lots of their light in the ultraviolet, which can strip the atmospheres of Neptune-like planets through a mechanism called photoevaporation. Perhaps all the gaseous planets that orbit A-type stars have been stripped of their atmospheres and all that is left behind are the relatively small rocky cores, which are very hard to detect via transits. Additionally, the existence of binary systems, to which many A-type stars belong, can make planets harder to detect. If what is thought to be a single star is in fact a binary, the second star’s extra light can make the transit depths even smaller and therefore even harder to detect.

Finally, the authors pose the question of whether A-type stars simply make fewer planets or are able to retain fewer planets. The disks of gas and dust that form around all stars when they are born, and from which planets are born, are dissipated by the strong A-type star’s stellar winds much faster than those of FGKM stars. Perhaps these disks don’t survive long enough to produce many planets. On the other hand, A-type stars are very massive and studies show that the large gas disks they produce when they are born should produce many planets and in particular many big planets. Perhaps these systems are born with many large planets that make the system gravitationally unstable and all the inner, small planets get flung out of the system.

In all, the authors provide a rigorous study of the occurrence (or lack thereof) of small planets in close orbits of A-type stars. This work sheds light on a severely understudied population and better rounds out our understanding of planet formation across stellar mass and temperature regimes. Sometimes finding nothing is just as meaningful!

Original astrobite edited by Maria Vincent.

About the author, Jack Lubin:

Jack received his PhD in astrophysics from UC Irvine and is now a postdoc at UCLA. His research focuses on exoplanet detection and characterization, primarily using the radial velocity method. He enjoys communicating science and encourages everyone to be an observer of the world around them.

close-up of the center of the active galaxy Centaurus A

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: Extremely Dense Gas Around Little Red Dots and High-Redshift AGNs: A Non-Stellar Origin of the Balmer Break and Absorption Features
Authors: Kohei Inayoshi and Roberto Maiolino
Authors’ Institutions: Peking University; University of Cambridge and University College London
Status: Published in ApJL

Since its launch in late 2021, JWST has discovered all kinds of weird and wonderful objects. Its impressive sensitivity to infrared wavelengths has allowed astronomers to peer billions of years into the past and discover previously unseen populations of early galaxies. One distinct group of new galaxies was dubbed “little red dots,” or LRDs for short, and these galaxies were observed to be red and compact with distinctive “V”-shaped spectra. You can read more about LRDs here and here.

There’s been a lot of speculation about what kinds of galaxies LRDs might be. One of the most popular interpretations is that a little red dot is a galaxy hosting a supermassive black hole that’s being fed by a rapidly rotating disc of gas. This is known as an active galactic nucleus or AGN. One of the key signatures of an AGN is the presence of broad Balmer emission lines in the galaxy’s spectrum.

Electrons in an atom can only inhabit specific energy levels, and to jump down from one level to another, a photon with the exact same energy as the difference between the two levels must be emitted. Each element has unique energy levels, allowing astronomers to attribute different emission lines to specific transitions within specific elements. Wavelengths in the Balmer series are emitted when an electron in a hydrogen atom jumps from a higher energy level to the second energy level.

cartoon showing how Doppler broadening is produced

Figure 1: This diagram shows how a spinning disc creates Doppler broadening. The side that’s moving towards the viewer will emit blueshifted light and the side that’s moving away from the viewer will emit redshifted light. When you add up the slight shifts from each part of the disc, you end up with a broad emission line. [Nathalie Korhonen Cuestas]

But just having Balmer emission lines doesn’t tell us much — it just indicates that there’s hydrogen in the galaxy. Hardly surprising given that it’s the most common element in the universe! Normally, an emission line is narrow since light is being emitted at just one wavelength. However, if the gas is moving relative to the observer, then the Doppler effect kicks in, shifting light to different wavelengths. The breadth of the Balmer lines in LRD spectra can only be produced by a spinning disc of hydrogen (see Figure 1). From the observer’s point of view, one edge of the disc is moving towards you, and the other edge is moving away from you. As a result, light from the edge moving towards you will be blueshifted, and light from the edge moving away from you will be redshifted. Adding up the light from the entire disc results in a broad emission line, hence why a broad Balmer line is a hallmark of an AGN (although not all AGN are observed to have broad lines — you can learn more about these kinds of AGN here).

But there are other possible explanations for what LRDs might be. One explanation that’s garnered some attention is the possibility that LRDs are not AGN and are instead very dusty starburst galaxies. This explanation is supported by the presence of a Balmer break (sometimes also called a Balmer jump) in the spectra of some LRDs. A Balmer break refers to a significant dip in a spectrum for wavelengths shorter than the Balmer limit — or, the maximum wavelength of light that can ionise a hydrogen atom with an electron in the second energy level. Observing a Balmer break means that a significant fraction of hydrogen atoms with electrons in or above the second energy level have been ionised by high-energy photons. Typically, a Balmer break is associated with recent star formation, since you need lots of hot stars to be emitting photons beyond the Balmer limit.

There’s a problem with this explanation of LRDs. If LRDs are in fact dusty starbursts, then their spectra are consistent with stellar masses of tens of billions (or even up to hundreds of billions) of solar masses. In the local universe, these kinds of masses are pretty normal, but local galaxies have had 13.8 billion years to grow — an LRD at a redshift of z = 7 has not even had 1 billion years to grow. Our current understanding of the universe makes it seem pretty unlikely that this could happen.

Luckily, today’s authors are on the case and have shown how an AGN spectrum could have a Balmer break, allowing astronomers to assume a much lower stellar mass for LRDs. The authors suggest that if LRDs contain AGNs covered by a thick blanket of dense gas, then we could expect to see a Balmer break.

To test this idea, the authors use a photoionisation modelling code called Cloudy, which essentially calculates how many electrons should be in each energy level, given the temperature and density of the gas, as well as the light source illuminating the gas. The authors model the gas in the LRD and surrounding the AGN as a single slab of low-metallicity (10 times lower abundance of heavy elements than in the Sun) gas at a uniform temperature and density and use an AGN spectrum as the light source. They vary the density of the gas between 10 million and 100 billion atoms per cubic centimeter.

At low densities (see the magenta line in Figure 2), there’s no Balmer break because there just aren’t many electrons in the second energy level. As the density increases, collisions between particles become more common, and some electrons will excite to the second energy level due to these collisions. As a result, there are more electrons at the right energy level to absorb photons bluewards of the Balmer limit and photoionise. In Figure 2, you can see that the strength of the Balmer break increases as you go from 108 cm-3 to 1010 cm-3.

plots of spectra produced by different gas densities

Figure 2: This plot shows you the spectrum produced by slabs of different densities. You can see that the Balmer break (highlighted in yellow) becomes deeper at higher densities, although it becomes slightly shallower at the highest density. [Adapted from Inayoshi & Maiolino 2025]

At the highest density tested by the authors (1011 cm-3, the yellow line in Figure 2), the strength of the Balmer break actually decreases. This is because the equilibrium temperature associated with this density is slightly lower (7800K instead of 8000K), resulting in less frequent collisions and fewer electrons in the second energy level.

You can see from Figure 3 that the authors’ simulated spectra produced Balmer breaks that are just as strong as the Balmer breaks seen in LRDs. This means that the picture of LRDs as AGNs surrounded by very dense gas is consistent with observations! The authors also show that such dense gas can produce absorption features at the Balmer wavelengths and an oxygen emission line, which are also sometimes observed in LRD spectra.

Plot of Balmer break strengths as a function of density

Figure 3: Balmer break strengths as a function of density for a range of the authors’ simulated AGN spectra. The colorful horizontal lines show the Balmer break strengths actually observed in different LRDs. [Inayoshi & Maiolino 2025]

Further observations are needed in order to definitively say what LRDs are, and it’s possible that not all LRDs are the same kind of object. The results of today’s research article show that we don’t have to invoke large stellar populations in order to understand Balmer breaks in LRD spectra, but Balmer breaks are only seen in 10–20% of broad-line AGN observed by JWST, so astronomers will need to understand the different physical scenarios that produce the full range of LRD spectra.

Original astrobite edited by Storm Colloms.

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.

spiral galaxy NGC 1672

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: CEERS: Increasing Scatter Along the Star-Forming Main Sequence Indicates Early Galaxies Form in Bursts
Authors: Justin W. Cole et al.
First Author’s Institution: Texas A&M University
Status: Published in ApJ

In the local universe, galaxies tend to form stars at a slow and steady rate, but new observations suggest this is not the case in the early universe. JWST has allowed astronomers to peer further back into the universe’s history, and the galaxies that they’ve found seem to defy expectations. For example, astronomers keep observing more bright galaxies than initially expected. One explanation for the observations made by JWST is that galaxies in the early universe form their stars in bursts interspersed with periods of less intense star formation.

The average rate at which galaxies form stars varies over cosmic time: from the beginning of the universe, it rises for about 3.3 billion years, peaks at around a redshift of z = 2 (equivalent to about 10.4 billion years ago), and then begins to decline. While an individual galaxy might deviate from this general trend, it’s a good description of how an entire population of galaxies behaves over time. Importantly, this trend is slightly different depending on a galaxy’s mass. More massive galaxies tend to form more of their stars and reach their peak star formation rate earlier in the universe’s history.

The correlation between mass and star formation rate gives rise to a relationship known as the star-forming main sequence, or SFMS. The SFMS is an observed correlation between a galaxy’s stellar mass and its star formation rate — higher-mass galaxies generally form stars at a higher rate. Since the cosmic star formation rate changes with time, so does the SFMS. For example, the SFMS of galaxies close to the peak of cosmic star formation will be shifted towards higher star formation rates than the SFMS of local galaxies.

To make things more interesting, astronomers can use different features in a galaxy’s spectrum to estimate the star formation rate averaged over a different amount of time. For instance, you can use the luminosity of the Hα emission line to estimate the star formation rate averaged over the last 10 million years. This is because the Hα emission line is produced in ionised gas surrounding the most massive stars (O types), which only live for a couple million years. By contrast, the ultraviolet luminosity of a galaxy is more sensitive to the emission from lower-mass, longer-lived stars, giving astronomers a way to estimate the star formation rate over the past 100 million years.

The authors of today’s article use these two measures of star formation rate to investigate the star-forming histories of over 1,800 high-redshift galaxies. They find that the SFMS has a lot more scatter if you use a short-timescale, Hα-based star formation rate as opposed to a longer-timescale, ultraviolet-based star formation rate. This suggests that the star formation rate is more variable on short timescales and supports the idea of bursty star formation.

The galaxies used in the analysis were observed as part of the Cosmic Evolution Early Release Science (CEERS) survey using the Near Infrared Camera (NIRCam) on JWST. All of the galaxies are in a very well-studied region of the sky known as the Extended Groth Strip, so the authors were able to combine the JWST data with pre-existing Hubble data.

To determine how the SFMS evolves with time, the authors divided the sample into five different bins, each in a different redshift range. For each bin and each star formation rate indicator, they estimated the slope, normalisation (y-intercept), and scatter of the SFMS. Across all redshifts, the authors found that the shorter-timescale, Hα-based star formation rate generated an SFMS with more scatter (see Figure 1) and a lower normalisation than an SFMS based on a longer-timescale star formation rate. Larger scatter shows that the star formation rate varies more on short timescales than long timescales, reflecting a bursty star-formation history. The lower normalisation shows that the short-timescale star formation rate is, on average, lower than the long-timescale rate. So, the authors conclude that while star formation does happen in bursts, it’s more accurate to describe the star-formation history as interruptions to normal star formation (lulls or naps that last between 100 and 250 million years), as opposed to short periods of very intense star formation.

plots of star formation rate as a function of galaxy stellar mass

Figure 1: The left-hand panel shows a long-term star formation rate (averaged over 100 million years) and the right-hand panel shows a shorter-term star formation rate (averaged over 10 million years). You can see that the right-hand panel has a lot more scatter than the left. [Cole et al. 2025]

Today’s authors also found that the scatter of the shorter-timescale SFMS increased with redshift, suggesting that galaxies in the early universe had burstier star-formation histories. However, the normalization of the SFMS did not change significantly, suggesting that the intensity of the bursts was not significantly higher in the early universe.

plot of the ratio of short term star formation rate to long term star formation rate

Figure 2: Higher-mass (x-axis) galaxies have a lower short-term star formation rate as compared to their long-term star formation rate, suggesting that higher-mass galaxies have shorter periods of activity. Click to enlarge. [Adapted from Cole et al. 2025]

When the authors divided the sample into higher-mass and lower-mass galaxies, they found some interesting behaviour. On average, lower-mass galaxies had more similar long- and short-timescale star formation rates, while higher-mass galaxies showed a more marked difference between the two star formation rates, with the shorter-term star formation rate being lower than the longer-term rate. You can see this behaviour in Figure 2, which plots the ratio between the short- and long-term star formation rates on the y-axis and shows a negative correlation between the ratio and mass. This shows that lower-mass galaxies experience longer bursts of star formation than higher-mass galaxies. The authors estimate that star-forming bursts last around 60 million years in high-mass galaxies and about 110 million years in low-mass galaxies.

The results of today’s article give us an exciting insight into the early stages of galaxy evolution and will help us to model these newly observed baby galaxies. There are still lots of open questions regarding why star-formation histories seem to be so different in the early universe, so stay tuned as astronomers learn more about galaxy evolution!

Original astrobite edited by Will Golay.

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.

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