Astrobites RSS

image of HD 163296's disk

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

Title: A Gap-Sharing Planet Pair Shaping the Crescent in HD 163296: a Disk Sculpted by a Resonant Chain
Authors: Juan Garrido-Deutelmoser et al.
First Author’s Institution:  Pontifical Catholic University of Chile and the Millennium Nucleus for Planet Formation
Status: Published in ApJL

An extra protoplanet might be lurking in the dust around a nearby star.

The pre-main-sequence star HD 163296 plays host to an extensive circumstellar disk, with gas reaching out beyond 500 astronomical units (au). Observations of this disk have revealed it to be quite the playground for the young planets forming within — and these authors claim there are more planets than previously thought.

Image of the disk surrounding HD 163296

Figure 1: The observed structure of the disk around HD 163296, as reported in Isella et al. (2018). The crescent-shaped region is visible at the bottom left of the inner gap, as indicated by the white box and as shown in the zoomed-in image (a). It appears to be a cloud of gas and dust within the gap, distinct from the overdense ring around it. [Adapted from Isella et al. 2018]

HD 163926’s disk has a series of rings — bumps and dips in surface brightness, corresponding to over- and under-densities of material at different distances from the host star (Figure 1). Observations of this sort of ringed structure have become common fare since the advent of high-precision millimeter imaging in the last 15 years. These rings imply the presence of protoplanets or other large substellar bodies, which can clear out gaps through their growth and alter what would otherwise be a smooth(er) profile.

Trying to figure out the exact setup of bodies that gives a disk its observed structure is an interesting problem — and in the case of HD 163296, it’s a problem that has proven a bit tricky.

It only took low-resolution images of this particular disk (like those taken with the Hubble Space Telescope at the turn of the century) for Grady et al. to suggest that a giant planet might be present in the outer reaches of this system. Jumping ahead to 2018, Teague et al. used rotation curves of observed gas to claim that there were likely two planets out there — both roughly as massive as Jupiter, at 87 and 113 au. Just a few months later, high-precision observations by the Atacama Large Millimeter/submillimeter Array (ALMA) revealed that the disk contains not just a series of gaps but also an intriguing substructure within the innermost one.

Today’s article focuses on this innermost gap, which extends from 38 to 62 au, and the crescent-shaped region near the edge of it that appears to have more material than it should (Figure 1).

The standard idea that gaps form along the orbit of a protoplanet doesn’t allow for this sort of uneven, crescent-shaped structure; the protoplanet should clear the material evenly all the way around the orbit, but it seems to have missed a spot. Modeling this gap, and the substructure within, would complete our current understanding of the HD 163296 system.

Luckily, the crescent has a fairly straightforward explanation. To understand it, though, we need to talk about Lagrange points.

diagram of the Lagrange points of a star–planet system

Figure 2: A diagram of the Lagrange points of a star–planet system. Smaller objects, like asteroids and dust, often accumulate at L4 and L5 due to the long-term stability of these points. [Mark Dodici]

If you’ve taken a class on classical mechanics, you might remember that Lagrange points are sort of like gravitational islands. For any pair of massive bodies (say, a star with a protoplanet), there are five points where the gravitational forces of the bodies balance nearly perfectly to keep much-less-massive things at those points, fixed relative to the more massive bodies. Two of these (L4 and L5) are stable against small displacements, meaning smaller things like asteroids and dust often accumulate at or around these two points. L4 lies almost exactly on the orbit of the less-massive body, in front of it by ~60 degrees. L5 trails behind the less-massive body by the same angle (Figure 2).

In the HD 163296 system, this crescent-shaped region with extra dust and gas could perhaps be explained as a build-up of material in the L4 or L5 of some massive protoplanet, which had otherwise cleared out the gap. In 2021, Rodenkirch et al. simulated the interactions between a gap-clearing planet and the dust around it, and they showed that this could work: a Jupiter-mass planet orbiting the star at 48 AU would both open up the observed gap and trap a significant amount of dust at its trailing L5.

And so the system was solved. The crescent-shaped substructure in HD 163296’s disk was the result of a Jupiter-mass planet. The other gaps were caused by two other planets farther out.

And yet, today’s featured article came out just recently. Why?

It turns out there were two problems with the Lagrange point idea. First, the crescent is centered at a radial distance of 55 au, which requires a lot of dynamical hoop-jumping-through to make sense for a Jupiter-mass planet at 48 au. Second, a Jupiter-mass planet would open up a deep gap in the gaseous disk. Less than a year after the first submission of Rodenkirch et al., observations by Zhang et al. of the disk’s carbon monoxide (CO) surface density — a great tracer for the overall gas density throughout a disk — showed that the gas gap between 38 and 62 au is ten times shallower than it would be if it were carved by a Jupiter-mass planet.

Enter Garrido-Deutelmoser et al. Last year, they studied the effects of having two planets in the same gap in a protoplanetary disk. Through hydrodynamical simulations, they showed that if two sub-Jupiter-mass planets are close enough to each other, their gravitational interactions would create relatively stable “vortices” at L4 and L5 of either of the planets. These vortices could maintain over-densities of dust and gas for thousands of orbits — plenty of time for us to have observed one of them.

In today’s featured article, Garrido-Deutelmoser (and a slightly different) et al. applied this concept to HD 163296. They set up simulations of the system mostly matching those of Rodenkirch et al., with the two proposed outer planets and a smooth disk of gas and dust. But in place of one Jupiter-mass planet at 48 au, they implanted two planets with a few times the mass of Neptune in that region. Since these two combine for a much smaller mass than Jupiter, they would create a much shallower gap in the gas density profile — ideally matching that found in Zhang et al.

A plot showing normalized gap depth as a function of semimajor axis

Figure 3: The radial gas density profile of HD 163296. Dark Purple: observed profile from Zhang et al. (2021). Magenta: simulated profile with one planet opening the 38–62 AU gap (the Rodenkirch et al. (2021) model). Orange: simulated profile with two planets opening said gap (this paper). Neither model fits well beyond ~85 AU, but the two-planet model matches the CO gap depth much more closely up to that point. [Garrido-Deutelmoser et al. 2023]

Through trial and error, they found that planets at 46 and 54 au could, in fact, carve out the appropriate density profile for this gap in both dust and gas (Figure 3) over the course of a half-million-year simulation. And in line with expectations from their previous work, material congregated at L5 for the outer super-Neptune (though they note that this ebbed and flowed over time). They do point out that neither their model nor the Rodenkirch et al. captured the density profile accurately beyond ~85 au, which they explain might be an issue with gas dynamics beyond that point. Regardless, their two-planet model for the gap of interest seems to be a winner.

They close the article with a final proposition, suggesting where in their orbits one might find each of the protoplanets, based largely on the fact that they seem to be close to a mean motion resonance chain — that is, they seem to have orbital periods that are roughly integer multiples of each other. Using a relationship for the orbital angles of objects in such a resonance, along with the location of the crescent and observations of kinematic features in the gas, the authors infer the precise locations of each of the protoplanets within the disk (Figure 4).

In the end, this might provide one final check for this finicky system. If the protoplanets are where they say they are, we’re golden. If not, the saga of HD 163296 will go on.

Two images of the surface brightness of a disk

Figure 4: The observed structure of the disk around HD 163296 (left) and the faux-observed structure from this simulation (right). The proposed locations of the four protoplanets are labeled on the left panel. While the simulated disk isn’t a perfect replica, it recreates most of the important details of the interior portions of the observed disk. [Garrido-Deutelmoser et al. 2023]

Original astrobite edited by Lucie Rowland and Zili Shen.

About the author, Mark Dodici:

Mark is a first-year PhD student in astronomy and astrophysics at the University of Toronto. His space-based interests include planetary systems, from their births to their varied deaths, as well as the dynamics of just about anything else. His Earth-based interests include coffee, photography, and a little bit of singing now and again. You can follow him on Twitter @MarkDodici.

Hubble image of the star at the center of the Bubble 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

Title: Constraints on Magnetic Braking from the G8 Dwarf Stars 61 UMa and τ Cet
Authors: Travis S. Metcalfe et al.
First Author’s Institution:  White Dwarf Research Corporation
Status: Published in ApJL

How to Brake a Star

You might be familiar with the classic example of conservation of angular momentum where an ice skater is spinning on a (frictionless) piece of ice with their arms tucked in. When they extend their arms, they increase their moment of inertia. Conservation of angular momentum then requires that the rotation rate of the skater decrease — the skater “spins down.”

However, conservation of angular momentum is only valid if the system (the spinning ice skater) is isolated. Things are a little different if, for instance, the skater is holding weights as they spin. When they extend their arms, they again increase their moment of inertia and slow their rotation rate. Then, the skater can drop the weights. The instant that the skater drops the weights, the system is no longer isolated, and angular momentum is no longer conserved. The reduction in the moment of inertia caused by dropping the weights also reduces the angular momentum.

This same principle is at work in stars. Instead of a figure skater holding weights, there is a stellar magnetic field holding plasma. Winds from the star can push the plasma farther and farther out, causing the star to spin down like a skater with extended arms. Eventually, the plasma is pushed so far away that the magnetic field isn’t strong enough to contain it anymore, and the plasma is lost along with some of the star’s angular momentum. This is called magnetic braking.

Because magnetic braking gradually removes the star’s angular momentum and slows down the star’s rotation, a star’s rotation rate can be used to estimate its age. This principle drives a field of study called gyrochronology. More specifically, stars’ ages are characterized by their Rossby number: the ratio between the star’s rotation period and its convective overturn timescale (the time it takes for a bubble of plasma to move through the convective zone). As a star ages and its rotation rate decreases, its Rossby number increases. Eventually, a star’s rotation slows down so much that the critical Rossby number is reached. At this point, the star experiences weakened magnetic braking and the star spins down at a slower rate than it had previously experienced.

This Work

The authors of this research article investigate the transition to weakened magnetic braking for stars cooler than the Sun — the first time this has been done. This is an important distinction; cooler stars have deeper convective zones and thus longer overturn timescales. This means their Rossby number is smaller than it is for hotter stars with the same rotation period. It also means that at the critical Rossby number, their rotation period will be longer than hotter stars’ periods.

For this work, the authors look at two G8 dwarf starsthese are stars a few hundred degrees cooler than the Sun. In order to investigate the transition to weakened magnetic braking, they chose two stars of very different ages: the younger of the two stars is named 61 UMa and is about 1 billion years old. The older star is named tau Ceti and is ~9 billion years old, which is about twice the age of the Sun! To figure out the effects of magnetic braking on these stars, the authors consider two major parameters besides age: the stellar magnetic field shape and strength and the mass-loss rate of the wind. Stronger magnetic fields can hold plasma out to greater distances and hence provide a larger torque than weak fields do. Additionally, the higher the mass-loss rate is, the faster the angular momentum is lost.

For 61 UMa, the authors determine the magnetic field properties from previously collected Zeeman–Doppler imaging data and calculate the mass-loss rate from the X-ray luminosity. For tau Ceti, they collected data with the PEPSI instrument on the Large Binocular Telescope to estimate the star’s magnetic field and determined its mass-loss rate from previously collected Lyman alpha measurements. With all of this information, they can estimate the torques from the fields and winds that are braking the stars.

The results of their calculations show that 61 UMa experiences a torque about 300 times stronger than tau Ceti’s torque. This is consistent with the idea that older stars, especially those with Rossby numbers above the critical Rossby number, are much less efficient at braking than younger stars that haven’t yet reached the critical Rossby number. The torque they calculated is plotted against the Rossby number in Figure 1, along with hotter stars that had been previously studied. Besides a trend for stars with higher Rossby numbers to have weaker torques, this figure shows that this work extended the stellar sample to include both smaller and larger Rossby numbers and torques than had previously been investigated in this context.

A plot of the wind braking torque versus the Rossby number for several stars

Figure 1: Rossby number (Ro) vs the torque caused by stars’ stellar winds. Blue triangles are for stars hotter than the Sun, yellow circles are for stars around the same temperature as the Sun, and the red squares are for the two stars studied in the paper that are cooler than the Sun. The black dashed line is the empirically derived critical Rossby number. [Metcalfe et al. 2023]

Aside from the magnetic field and mass-loss rate parameters, other stellar parameters like rotation period and stellar size are also used to determine torque. The authors were able to investigate the contributions of the various evolutionary model parameters by varying them, one at a time. What this work confirmed is that, by far, the evolutionary change in mass-loss rate and magnetic-field properties dominate the effects of braking. Changing other parameters like the evolution of the rotation period, the stellar mass, and stellar radius contribute about 2–10 times less to the decrease in torque over time.

This research serves as an important expansion to our understanding of stellar spin evolution as a function of spectral type. This is crucial for understanding both stellar histories and futures and provides important insight to the environment of young and old stars alike. It also represents the beginning of work dedicated to understanding these cooler stars and solar analogs; the authors have plans to collect spectropolarimetric data to map magnetic fields on cooler K-dwarf stars so that they can extend their analysis to a broader sample. Although these stars are slowing down, the authors are moving full speed ahead!

Original astrobite edited by Sarah Bodansky.

About the author, Ivey Davis:

I’m a third-year astrophysics grad student working on the radio and optical instrumentation and science for studying magnetic activity on stars. When I’m not crying over RFI, I’m usually baking, knitting, harassing my cat, or playing the banjo!

ultraviolet image of the Andromeda 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

Title: On the Gamma-Ray Emission of the Andromeda Galaxy M31
Authors: Yi Xing et al.
First Author’s Institution: Shanghai Astronomical Observatory, Chinese Academy of Sciences
Status: Published in ApJL

Gamma rays are the highest-energy photons in our universe. Naturally, they come from some of the most extreme environments in the universe, such as pulsars, active galactic nuclei, supernovae, and potentially even dark matter. Though many gamma-ray sources have been detected both in the Milky Way and extragalactically, the nature of gamma-ray emission from our closest neighbouring galaxy, Andromeda (or Messier 31), remains somewhat of a mystery.

The Fermi Large Area Telescope (Fermi-LAT) is an instrument on the Fermi Gamma-ray Space Telescope that has been surveying the sky for high-energy gamma rays since 2008, with ample data taken on Andromeda throughout its flight. Many groups have analyzed these data, with more data giving more insight into what’s making these gamma rays.

To Extend or Not to Extend?

Up until today’s article, it looked like gamma rays from Andromeda were coming from a blob-like shape (i.e., extended emission) surrounding the centre of the galaxy (similar to Figure 1, left). This was particularly exciting, since extended structure in gamma-ray emission often suggests either a distribution of cosmic rays or the presence of a massive dark matter halo.

significance map of the Andromeda Galaxy in two gamma-ray energy ranges

Figure 1: Significance maps of Andromeda at energies from 0.1 to 500 gigaelectronvolts (left) and 2 to 500 gigaelectronvolts (right). The region of optical emission is represented by the white contour. The colorbar corresponds to test statistic, which is similar to significance. A test statistic of 25 corresponds to a detection. Green markers correspond to nearby sources found in the SIMBAD database. The left figure shows a hint of additional structure in the southeast region of Andromeda, but both point sources emerge out of the seemingly extended region only with the lowest energies cut out. [Xing et al. 2023]

Cosmic rays are charged particles that travel at relativistic speeds through the universe but get easily diverted by magnetic fields, making it very difficult to trace their origin from Earth. Luckily, since there are processes that produce gamma rays from charged particles (hadronic processes), identifying regions of extended gamma rays can trace regions where populations of cosmic rays are interacting with their environments. On the other hand, clumps of massive dark matter located in the centre of Andromeda could decay or annihilate, producing gamma rays in the process.

Where are the Gamma Rays Coming From?

A plot of observed and modeled spectral energy distributions

Figure 2: A spectral energy distribution showing flux (quantity of gamma rays received) plotted against energy of Andromeda’s centre (black) and southeast (red) emission regions, along with the Milky Way’s galactic centre (blue). It is apparent that both sources are not only similar in brightness but are also producing significantly more gamma rays than our galactic centre. Click to enlarge. [Xing et al. 2023]

A reanalysis of 14 years of Fermi-LAT data by the authors reveals that the emission of gamma rays isn’t extended after all. In fact, it seems that it’s constrained to two point sources: one located right at the centre of the galaxy and another ~20,000 light-years to the southeast (see Figure 1). This only became apparent when the authors cut out the lowest-energy gamma rays, which still make the data appear more or less extended when they’re included. Even more curiously, the authors found that both of these regions are significantly brighter than expected when compared to the gamma-ray emission of our own galactic centre (see Figure 2).

This new picture of Andromeda’s gamma rays changes a lot about our understanding of the galaxy. It’s no longer likely that Andromeda’s central gamma-ray hotspot is coming from a dark matter halo or cosmic ray distribution, so the authors looked to the Milky Way’s galactic centre to figure out what sorts of objects could be responsible for the gamma rays. One of the leading theories for our own galactic centre gamma rays is a population of old, unresolved objects, such as millisecond pulsars. However, in the case of Andromeda, at least 15,000 millisecond pulsars would be needed to account for the especially bright gamma-ray emission. While it’s still uncertain whether or not the centre of Andromeda can host this huge number of pulsars, we’ve only detected around 200 in the Milky Way’s centre, so this explanation seems unlikely.

The authors also investigate the southeast source that appeared in their new analysis. Since galaxies are pretty far apart from one another, the chance of finding two or more galaxies by coincidence in a circle drawn around both the central and southeast sources is only ~0.4%. This means that the emission is most likely coming from within Andromeda. As seen in Figure 2, the off-centre source is almost exactly the same brightness as Andromeda’s centre source (which is peculiar in its own right!), leading to the same problem of identifying sources capable of emitting such bright emission. After looking through X-ray and optical surveys, the authors determined that there weren’t any good counterparts for this region in other wavelengths either. Even considering the low probability of this being an extragalactic source behind Andromeda, there aren’t any known counterparts in the region of the sky where this hotspot is located.

The results are certainly unexpected and open up a whole new can of worms when it comes to figuring out the origin of the gamma rays in our neighbouring galaxy. Even though there are still a lot of unknowns, future observations and analyses of these newly constrained regions will help us understand how bright gamma rays are produced near the centres of galaxies and may even help us better understand our own galactic centre.

Original astrobite edited by Ivey Davis and Katya Gozman.

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.

An image of Saturn with a white circle to show the planet's oblateness

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

Title: On The Effects of Planetary Oblateness on Exoplanet Studies
Authors: David Berardo and Julien de Wit
First Author’s Institution: Massachusetts Institute of Technology
Status: Published in ApJ

The world is a complicated place, and all scientists are just storytellers trying their best to explain it with more and more accurate fables. One of their most commonly accepted tropes in the canon of physics is assuming that anything round-ish, even a cow, is a perfect sphere. Astronomers implicitly do this all the time when it comes to exoplanets: we assume that all of them, big and small, hot and cold, are immaculate orbs.

Even in our own solar system, though, we know that this is not strictly true. Consider the hypothetical cosmic prospector: if they wanted to drill a hole to the center of Saturn, they’d better carefully consider their starting location. If they broke “ground” on the equator, they’d have to dig about 10% farther than if they had started from the north pole (setting aside the difficulties of “digging” through a gas giant). This is because Saturn is slightly squashed: its equatorial radius is larger than its polar radius, and it bulges out in the middle due to its rapid rotation.

Even though our investigations of worlds beyond our neighborhood have turned up strange and unexpected systems wholly different from our own, we have no reason to assume that there wouldn’t be similarly squished planets out there. Today’s authors take that tension between our simple models and expectation of non-spherical planets and answer two resulting questions: can we do better and actually measure a planet’s bulge, and, if not, what are the implications of using the wrong model?

Can We Detect It?

diagram demonstrating how the area of a star that is blocked by a transiting planet varies from a spherical planet to an oblate planet

Figure 1: The difference in the area of the star blocked by a spherical planet and an oblate planet. Note that as the oblate planet crosses the stellar limbs, it blocks different amounts of stellar area than a spherical planet would. The bigger this difference is, the easier it would be to detect that a planet is oblate. [Adapted from Berardo and de Wit 2022]

Actually measuring the degree of squishedness, more technically called oblateness, of a planet is tricky work. When we observe the transit of an exoplanet, the only thing we can measure at any moment is the area of the star blocked by the planet, not the shape of the photobomber blocking the light. As Figure 1 shows, the only time an oblate planet gives itself away are the moments it enters and exits our stage, just as it’s crossing the stellar limbs. Only then is the area blocked by the star different than we’d expect for a spherical interloper.

To assign a quantitative measure of this difference, the authors created fake data of oblate and spherical planets passing in front of their stars, zoomed in on just the beginning and end of the transits, then measured the root mean square of the difference between the two types of planets. They found that this value depends strongly on the cadence, or amount of time between measurements, of their fake data. This is illustrated in Figure 2. All told, they estimate that several tens of currently known planets would differ from a spherical model by a few tens of parts per million if they were actually oblate.

Figure 2: The number of known planets (y axis) that would differ from a spherical model by a given amount (x axis) if they all actually had an oblateness of 0.2. Note that shorter-cadence data can reveal more oblate planets than longer-cadence data. This is because the authors focus only on the ingress/egress of the planet, and shorter-cadence data allows for more measurements during that time. [Adapted from Berardo and de Wit 2022]

Unfortunately, most of our transit measurements aren’t that precise, meaning it would be very difficult to measure the oblateness of a single planet using existing data. That said, even though it isn’t easy to measure the oblateness of one planet, Kepler data are good enough to make statements about population-level trends. After fitting some real Kepler data with their oblate model, the authors concluded that most planets aren’t severely oblate, and short-period planets don’t seem to be systematically more oblate than long-period planets.

How Wrong Is Circular?

If we can’t really measure the oblateness of a moderately squished planet, does it even matter?

Unfortunately, the authors show that it might. Much like a slightly square peg can still be jammed through a round hole, we can still fit an oblate light curve with a circular model, but it won’t be a great match. Our estimates for many of the model parameters will be biased — that is, they’ll lean away from their true value in a given direction. For example, in Section 3 of the research article, the authors show that we’re likely to underestimate the true radius of a planet and overestimate its inclination.

This is unfortunate, but it’s important when we consider the downstream effects of how we use these transit-derived parameters to construct other descriptions of a planet. Astronomers have measured the masses and radii of a growing number of planets using the transit technique and by careful monitoring of the host star’s radial velocity, respectively. It is tempting to combine these measurements into an estimate of the density of the planet, but doing so requires assuming the volume of the planet. This requires assuming the planet is spherical, or at least that your measured radius is correct. If either of those are false, your final density will be incorrect. The authors estimate that available data can only rule out oblateness over about 0.25, but if that planet was even slightly rounder than that, we’d get its density wrong by more than 10%.

It’s nice to pretend that all cows are spheres. But we learn a lot, and can be more honest about the accuracy of our measurements, when we consider that some planets might be more complicated than we’d wish.

Original astrobite edited by Lili Alderson.

About the author, Ben Cassese:

I am a second-year Astronomy PhD student at Columbia University working on simulated observations of exomoons. Prior to joining the Cool Worlds Lab I studied Planetary Science and History at Caltech, and before that I grew up in Rhode Island. In my free time I enjoy backpacking, spending too much effort on making coffee, and daydreaming about adopting a dog in my NYC apartment.

a near-infrared view of hundreds of galaxies

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

Title: CEERS Epoch 1 NIRCam Imaging: Reduction Methods and Simulations Enabling Early JWST Science Results
Authors: Micaela B. Bagley et al.
First Author’s Institution: The University of Texas at Austin
Status: Published in ApJL

Astronomers around the world breathed a sigh of relief when the JWST, a telescope more than two decades in the making, successfully launched and aligned its mirrors last year. However, there are still several challenges and kinks to work out in the imaging processing. In particular, there are many intermediate steps involved in turning JWST’s raw data into the beautiful final images released to the public. This article, part of the JWST Directors Discretionary Early Release Science (DD-ERS) public program, is one of the first to try to calibrate and measure some of these issues using real data taken in space.

The 13 DD-ERS programs are the first to receive science data from JWST, and in turn, they promise to publicly share all their data products, tools, software, simulations, and documentation to the community to help astronomers learn how to utilize and analyze JWST data. This article describes in detail one of these programs: the Cosmic Evolution Early Release Science Survey (CEERS), which is obtaining imaging and spectroscopy of the Extended Groth Strip Hubble Space Telescope legacy field. The Extended Groth Strip is an image of a small region between the Ursa Major and Boötes constellations, covering about 100 square arcminutes. The CEERS team’s main science goal was to test efficient observation strategies for extragalactic surveys with JWST.

This article presents the analysis of imaging from JWST’s Near Infrared Camera (NIRCam). This is one the first official public dataset releases from any DD-ERS programs. NIRCam has two channels that observe in parallel: one short-wavelength and one long-wavelength channel. Each channel has two modules: A and B, each having a field of view of 2.2 arcmin × 2.2 arcmin. Each module has four short-wavelength detectors, A1-A4 or B1-B4, tuned for observations in the range 0.6–2.3 microns (1 micron = 10-6 meter), and one long-wavelength detector, ALONG or BLONG, tuned for observations in the range 2.4–5 microns. The long-wavelength channel has a resolution of 0.06 arcseconds per pixel and the short-wavelength channel has a resolution of 0.03 arcseconds per pixel. The A and B modules have unique fields of view that lie adjacent to one another. As shown in Figure 1, the same field is simultaneously observed with A1-A4 and B1-B4 (short-wavelength) and ALONG and BLONG (long-wavelength), respectively.

Demonstration of fields of view and wavelength ranges for various JWST and Hubble filters

Figure 1: Top left: field of view of the eight short-wavelength detectors A1-A4 and B1-B4. Bottom left: field of view of the two long-wavelength detectors ALONG and BLONG. The transmission throughput curves (which show which wavelengths of light are filtered through a given filter) are shown in the middle-left panel, where F115W, F150W, and F200W are short-wavelength filters and F277W, F356W, F410M, and F444W are the long-wavelength filters. Example images from the F200W and F277W filters are shown on the bottom right. An image from the Hubble filter F160W is displayed on the top right for reference. The improvement in signal-to-noise and sensitivity from Hubble to JWST is striking. [Bagley et al. 2023]

This article describes the team’s challenges and solutions during the JWST image reduction process. Image reduction in astronomy is processing and converting the raw photons that a detector receives into a flux value from astronomical objects. However, sometimes after processing the images, non-astronomical artifacts can appear in the images. Below is a summary of the three main issues found in the CEERS team imaging:

  • Snowballs are large cosmic ray events that can affect hundreds of pixels and appear as a circular feature on the NIRCam detectors (see Figure 2 for an example of snowball removal). The team saw an average of 25–30 snowballs per detector in their images. To remove the snowballs, the CEERS team identified large contiguous pixels that had jumps in flux and then masked them out of the final image.
example of snowball correction

Figure 2: Example of snowball correction. The left image shows a count-rate map, where snowballs — large cosmic ray events — are present. There is a particularly large snowball in the lower left corner of the image. The middle image shows the identified snowballs. The right image is the result after subtracting the snowballs from the image. [Adapted from Bagley et al. 2023]

  • Wisps are created from stray light reflected off the secondary mirror supports. The strength of the wisp features depends on the source of the reflected light. They are visible on detectors A3, A4, B3, and B4 (see Figure 3 for an example). The CEERS team used wisp templates provided by JWST to fit for wisps in their images and then masked out the wisp features. The wisp templates will continue to improve as more programs obtain NIRCam imaging to characterize the wisps.
before and after images showing the effect of wisp removal

Figure 3: Top panel: an example of a wisp in NIRCam imaging in the black box. Wisps are visible in detectors A3, A4, B3, and B4 (inner four panels). The images are fit with wisp templates and then the wisps are masked out from the final images. The bottom panel shows a cleaned version of the image where the wisp feature has been removed.[Adapted from Bagley et al. 2023]

  • 1/f noise, also called pink noise, is correlated noise introduced in the images when the detectors are read out. In many modern detectors, incoming photons create photoelectrons that are trapped in local potential wells in a given pixel. After a specific time, the photoelectrons are counted, or read out, and the pixels are emptied and reset. In contrast to white noise, which has equal intensity per frequency, pink noise dominates at lower frequencies. In the NIRCam images, this noise presents as a horizontal and vertical striping pattern, as shown in Figure 4. To remove the noise, the CEERS team corrected pixel values more than two standard deviations away from the median of a given row or column.
illustration of removing 1/f noise

Figure 4: Illustration of removing 1/f noise, which presents as horizontal and vertical striping patterns in the NIRCam images. [Adapted from Bagley et al. 2023]

In conclusion, the CEERS team was able to robustly characterize and tackle many of the image-processing problems present in the NIRCam detectors. With more data and time, errors due to the reduction procedures will decrease. The CEERS team put in diligent work to better understand NIRCam, to the benefit of all astronomers using JWST!

Original astrobite edited by Katya Gozman.

About the author, Abby Lee:

I am a graduate student at UChicago, where I study cosmic distance scales and the Hubble tension. Outside of astronomy, I like to play soccer, run, and learn about fashion design!

a foreground star shining in front of the galaxy NGC 7250

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

Title: Uranium Abundances and Ages of R-process Enhanced Stars with Novel U II Lines
Authors: Shivani P. Shah et al.
First Author’s Institution: University of Florida
Status: Accepted to ApJ

As someone who has recently left their 20’s, I think a lot about how age shows up in my body. I can look up my birth date on the calendar, even count all the minutes of my existence, but I don’t need to go through all that work. Something inside of me just feels… older. While the self realization of the unyielding passage of time on my mortal form may be daunting, I find solace in the fact that I’m no different than the stars — they also carry around their own clocks. Today’s article is about an interesting technique to determine how old a star is by looking at how much uranium is “ticking” in its atmosphere.

The Smallest Hand of the Clock

The technique is based on radioactive dating, a tool used in a variety of ways but most famously in carbon dating. Living things on Earth have carbon atoms in their bodies, some of which are carbon-14 (C14). C14 is a radioactive isotope of carbon, meaning it has a slightly different mass than other carbon atoms, and it decays over time. Even though it decays, C14 is regularly replaced while an organism is alive, and so the ratio between regular carbon and C14 within living things stays mostly steady. Once the flow of C14 stops (aka something dies), the ratio between carbon and C14 changes as the latter decays. By measuring the remaining ratio and comparing it to the normal ratio, we can calculate how much time has passed for the correct amount to decay.

Radioactive dating isn’t just for living things. C14 decays at such a rate that you can use it to measure the ages of objects up to around 50,000 years old, but the same technique works for any element with a radioactive isotope. Our best estimate for the age of our planet and solar system comes from radioactive dating using different elements that have radioactive isotopes that decay at slower rates.

Uranium is an element that is perfect for this, as its radioactive isotope takes billions of years to decay. Today’s article is all about trying a new way to measure the abundance of uranium in stars to find an age estimate for stars with radioactive dating. It’s known as nucleocosmochronometry (a word that spans one and a half Scrabble boards).

Tiny Atoms in Massive Stars

plot of an example uranium feature in the spectrum of a star

Figure 1: An example uranium feature in a star’s spectrum. The black points are the data. The red line is the best model for the spectrum that includes uranium. The authors also fit a model that doesn’t include uranium, which is the blue dashed line. By measuring the difference in the two models, the authors estimated an abundance of uranium responsible for absorbing the missing light. [Adapted from Shah et al. 2023]

It might seem incredibly difficult to detect atoms in a massive star that is light-years away, but it’s actually one of astronomy’s oldest tricks (astrobites has a whole guide about it!). Each element and molecule has its own characteristic fingerprint — its spectral signature — in the form of the specific wavelengths of light that it absorbs (called spectral lines). These can be measured in a lab, and then by looking at the light coming from a star and seeing which wavelengths are being absorbed, we can tell what’s in the star’s atmosphere.

This works great until elements and molecules have lines very close to one another, which is a major challenge with uranium. As it turns out, the typical line used to measure uranium abundance is blended with both an iron line and a cyanide feature (Figure 1). It’s still possible to get a measurement, but today’s authors wanted to use two new uranium lines to measure abundances and see how well they agreed with the single-line method. Even though these new lines are also blended, three measurements allow the authors to do a better job of describing the certainty of the measurement by using statistics to compare the abundances measured between the three lines.

plot of age estimates for four stars

Figure 2: The age estimate of the four stars (names on the x axis) from this work (colored squares) compared to other work (white squares). The accepted age of the universe is included as a black dashed line. The age estimate is not a ratio of uranium to a uranium isotope since only total uranium was measured, but uranium against europium, which does not have any radioactive isotopes so should be a constant and appropriate comparison. [Adapted from Shah et al. 2023]

Do You Have the Time?

The authors measured the abundances of uranium for four stars and compared the results from a fit using just a single-line measurement in each of the stars to one using all of the uranium lines. They found that the abundances from both methods were within a reasonable range of one another.

When the authors used the abundances to measure an age (Figure 2), they found ages that were similar to those calculated with just the single measurement. You might notice that the age estimates have big error bars — some stretch to an age older than the universe! There are clearly still some challenges with the method in general, in part because it’s hard to know how much uranium was in the star to begin with. The authors chose these four stars for the study because they are examples of stars that should have had more uranium. Regardless, the production rates of uranium remain a big question mark.

The Clocks Keep Spinning

It’s worth mentioning that the uranium that makes these stellar clocks tick formed in merging neutron stars, the dramatic burst of atomic creation when two “dead” stars collide. A star’s clock, and even its very existence, is due in part to the stars that came before them. Makes me think about how even if my body feels old, my time being alive has been traced through thousands of lifetimes similar to my own. 30(+) be damned, I’m going for a walk.

Original astrobite edited by Jessie Thwaites.

About the author, Mark Popinchalk:

I’m a PhD Candidate at CUNY/Hunter College based at the American Museum of Natural History. I study the age of stars by measuring how quickly they rotate. I enjoy ultimate frisbee, baking bread, and all kinds of games. My favorite color is sky-blue-pink.

Backlit Saturn as seen in an image mosaic from the Cassini 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

Title: A Circumplanetary Dust Ring May Explain the Extreme Spectral Slope of the 10 Myr Young Exoplanet K2-33b
Authors: Kazumasa Ohno et al.
First Author’s Institution: University of California, Santa Cruz
Status: Published in ApJL

Figure 1: Transit light curves of K2-33b using multiple instruments. The optical observations from K2 and MEarth show much deeper transits than those in the near-infrared observation, obtained with Spitzer IRAC’s Channels 1 and 2 and the Hubble Space Telescope. This could be because the planet’s atmosphere is blocking more light at bluer optical wavelengths than in the infrared. [Thao et al. 2022]

Interpreting the transmission spectra we observe from exoplanet atmospheres can be really tricky. While many of the features we see occur at characteristic wavelengths, the exact shapes and sizes of these features are controlled by a host of different factors, leaving a complex web of chemistry to untangle. For example, take what’s known as the “scattering slope”: a tilt in a planet’s transmission spectrum from more light transmitted at redder wavelengths to less light transmitted at bluer wavelengths. At bluer wavelengths, less light passes through the planet’s atmosphere, causing the depth of its transit at those wavelengths to appear deeper, as shown in Figure 1. This slope gets its name because it can be caused by the presence of clouds and hazes scattering light in the atmosphere, and how steep it is can provide information about such hazes. However, very steep slopes can also be caused by active regions on the host star’s surface, since transmission spectroscopy requires looking at the star’s light as it passes through the planet’s atmosphere.

K2-33b is one such planet with a very steep slope (check out this astrobite to find out more!), with ground- and space-based observations showing much deeper transits at bluer wavelengths, as seen in Figure 1. In this case, the host star probably isn’t active enough induce the slope we see, so a hazy atmosphere around a puffy, low-density planet is thought to be the culprit. But what if there were another possible explanation? The authors of today’s article consider whether a ring of dust around K2-33b could be responsible.

Ringing Out the Details

Using the presence of exoplanetary rings to interpret seemingly inexplicable observations isn’t a new idea. Rings could explain why some seemingly low-density exoplanets have flat transmission spectra; since the presence of rings would increase the radius obtained from the transit method while the mass of the system remains the same, rings could lead us to believe a planet’s density is lower than it is. But if rings produce a flat spectrum, how could they explain what’s happening with K2-33b? The authors of today’s article explain that the opacity of the ring is essential (take a look at Figure 2 for a handy guide!).

Cartoon illustrating the transmission spectrum of a ringed exoplanet

Figure 2: An illustration of how the presence of rings and their opacities can impact the transmission spectrum of an exoplanet’s atmosphere. [Ohno et al. 2022]

Too optically thick, as shown on the left-hand side of Figure 2, and the ring blocks light at optical wavelengths, producing a flat transmission spectrum. Too optically thin, as shown on the right-hand side of Figure 2, and the ring doesn’t interact with the star’s light at all, having no impact on the transmission spectrum. But as shown in the middle of Figure 2, if the ring’s opacity is just right, the star’s light passing through the ring will be absorbed more at bluer wavelengths. This creates a steep slope in the optical part of the transmission spectrum, similar to the slope that might be created by scattering from a hazy atmosphere. Crucially, a ring-induced slope can be much steeper than what might be produced by the atmosphere alone.

Does the Right Ring Make a Good Match?

To check whether this explanation could work for the transmission spectrum of K2-33b, the authors model both the atmosphere of the planet and rings of different mineral compositions.

Figure 3 demonstrates that with the right opacity, rings of all compositions are able to match the observations, reproducing the steep slope caused by the deeper transits at blue wavelengths. By comparing the coloured models to a model without the presence of a ring, shown by the grey line in each panel, it’s clear that the addition of rings is a big improvement! Many of the ring compositions also produce distinctive absorption features in the mid-infrared, which, if present, could be identified with JWST’s Mid-Infrared Instrument and would help confirm the existence of a ring.

K2-33b transmission spectrum compared to various models with and without rings of various mineral compositions

Figure 3: The transmission spectrum of K2-33b (black data points) along with models of the atmosphere without the presence of a ring (the flatter grey lines) and models including rings of different mineral compositions (coloured lines and shaded regions). Each panel highlights the impact of a ring made of a different mineral, as labelled in the bottom right of each panel. Note that the y axis shows the transit depth in parts per million (ppm), so a larger value here indicates less flux reaching the observer. [Ohno et al. 2022]

If the ring models provide a good match, does this mean K2-33b has a ring? Maybe! Since extremely low-density planets are expected to struggle to hold onto their atmospheres, and the ring scenario results in a higher-density planet than the hazy alternative, rings might start to seem like the more favourable option. But sustaining a dusty ring for long periods of time is also tricky. While mid-infrared observations will be helpful for understanding whether a ring is really present or not, until JWST points its hexagons at K2-33b, both scenarios remain perfectly reasonable.

Original astrobite edited by Jessie Thwaites.

About the author, Lili Alderson:

Lili Alderson is a second-year PhD student at the University of Bristol studying exoplanet atmospheres with space-based telescopes. She spent her undergrad at the University of Southampton with a year in research at the Center for Astrophysics | Harvard-Smithsonian. When not thinking about exoplanets, Lili enjoys ballet, film, and baking.

Elliptical galaxy IC 2006

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

Title: Beyond UVJ: Color Selection of Galaxies in the JWST Era
Authors: Jacqueline Antwi-Danso et al.
First Author’s Institution: Texas A&M University
Status: Published in ApJ

Separating the Living from the Dead

galaxy cluster observed by JWST

Figure 1: The galaxy cluster SMACS 0723, as seen by JWST. [NASA, ESA, CSA, and STScI]

Look at all those galaxies in Figure 1! With JWST, we will be able to observe galaxies near and far in unprecedented detail. But just what are those galaxies up to? One of the main ways astronomers characterize galaxies is by studying their star formation — are they still actively forming stars, or are they quiescent (dead)? By separating galaxies into these two populations, we can learn how the process of star formation begins and shuts down in galaxies across cosmic time.

Quiescent galaxies are often called “red and dead” because they appear redder in color than star-forming galaxies, which have younger and bluer stellar populations. Using this principle, quiescent galaxies are selected through what’s known as a UVJ diagram. In this diagram, the difference in a galaxy’s brightness in an ultraviolet filter (U) and a visible filter (V) is compared to the difference in its brightness in a visible filter (V) and a near-infrared filter (J). Because quiescent galaxies tend to be less bright than star-forming galaxies in ultraviolet and near-infrared bands (they tend to lack the infrared-emitting dust of dusty star-forming galaxies), they will clump together in the upper left part of the UVJ diagram, as seen in Figure 2. With just three photometric data points, large samples of galaxies can be classified as either quiescent or star forming!

Color–color diagrams for galaxy selection

Figure 2: UVJ diagrams color coded by galaxy number, star formation rate divided by stellar mass (specific star formation rate, or sSFR), and extinction (Av) are shown in the upper panel. [Antwi-Danso et al. 2023]

However, there are some problems with selecting quiescent galaxies through this method. For galaxies at higher redshifts (z > 3), the near-infrared J band is redshifted beyond the coverage of infrared space-telescope instruments like Spitzer/Infrared Array Camera and JWST/NIRcam. To place these galaxies on the UVJ diagram, astronomers have to extrapolate to determine the galaxies’ J-band magnitudes. Additionally, some galaxies have bright emission lines in the visible part of their spectrum, which can falsely boost their U – V color.

A more robust way to determine whether a galaxy is actively forming stars is to look at its spectrum, which we can now do even with high-redshift galaxies using JWST! But spectroscopy is more costly than photometry, and we can characterize many more sources by relying on photometric data. To counter these problems, the authors of today’s article present a new photometric selection method using synthetic filters.

Getting Rid of the Star-Forming Imposters with Synthetic Filters

The authors introduce the synthetic filters us, gs and is, which correspond to the u, g, and i filters used by the Sloan Digital Sky Survey. These top-hat filters are narrow — so they avoid emission lines — but are well separated from one another, which makes this combination of filters capable of distinguishing between dusty star-forming galaxies and quiescent galaxies. Importantly for higher-redshift galaxies, the is filter overlaps with Spitzer/Infrared Array Camera channels and JWST/Near Infrared Camera (NIRcam) coverage, as seen for a galaxy at z = 4.5 in Figure 3.

plots of system throughput as a function of wavelength for various sets of filters

Figure 3: In the second panel from the top, the synthetic filters us, gs, and is are shown with the spectral energy distribution of a galaxy at z = 4.5 with strong emission lines, while the locations of the traditional U, V, and J filters are shown in the bottom panel. The central wavelengths of the synthetic filters correspond with the Sloan Digital Sky Survey filters u, g, and i as shown in green in the third panel from the top. The synthetic filter is has better coverage by Spitzer/Infrared Array Camera channels (shown in the top panel) compared with the J band. Additionally, the synthetic filters avoid emission lines that overlap with the V band. The JWST instrument NIRcam goes out to 5 microns, which is the right edge of the Spitzer/Infrared Array Camera channel 2 in the top panel. [Antwi-Danso et al. 2023]

How do the synthetic filters perform compared with the classic UVJ selection? To investigate this question, the authors look at observational data of galaxies from the 3D-HST and UltraVISTA surveys as well as simulated JWST data of higher-redshift galaxies from the JAGUAR catalog. When making selections from this sample of galaxies, two properties of the selected quiescent galaxy population are important: completeness and contamination. Completeness tests what fraction of the total true population of quiescent galaxies is selected, while contamination is related to the number of star-forming imposters that sneak past the selection process compared to the total number of galaxies selected. Ideally, a selection would maximize completeness and minimize contamination. The authors also examine the ratio of true positives (galaxies that have been selected and are quiescent) to the number of false positives (the star-forming impostors).

At all redshifts, but particularly at high redshifts, the (ugi)s  selection outperforms UVJ in terms of contamination. In Figure 4, the completeness, contamination, and ratio of true to false positives is shown as a function of redshift for the sample of high-redshift galaxies from the JAGUAR catalog. At z = 6, ~60% of galaxies selected by UVJ as quiescent are star-forming — so the selected sample is mostly composed of frauds! By comparison, ~33% of the galaxies picked out by the synthetic filters are star-forming, a significant improvement.

plots of completeness, contamination, and the true to false positive ratio as a function of redshift

Figure 4: Completeness, contamination, and the true positive to false positive ratio as a function of redshift for the selections from UVJ (solid gray), ugi (pink), and the synthetic (ugi)s filters (orange). All three selections have similar completeness, but (ugi)s has lower contamination and a higher true positive to false positive ratio. [Antwi-Danso et al. 2023]

Both selections perform similarly in terms of completeness, with less than 70% of the total quiescent galaxy population selected at z > 4 and ~85–90% of the total quiescent galaxy population selected at z = 3–3.5. Why do us, gs, and is miss more quiescent galaxies at higher redshifts? Galaxies in the early universe wouldn’t have had much time for star formation to shut down compared to local galaxies, which means they are more likely to be recently quenched. Although these post-starburst galaxies are no longer forming stars, they can appear bluer than a typical quenched galaxy and thus would be classified as star-forming by falling below the U – V or us – gs cutoff. Alternatively, there may exist a population of dusty quiescent galaxies that is relatively bright in J or is, which would be excluded by the V – J or gs – is cut.

In the era of JWST, color selection methods to distinguish between star-forming and quiescent galaxies will likely continue to play an important role in studying galaxy evolution. The (ugi)s selection is promising for weeding out star-forming galaxies at higher redshifts, and the authors note that upcoming spectroscopic data from JWST will further test the efficacy of this method. By being able to select quenched galaxies at higher redshifts (z ~ 6), we may be exploring the first galaxies ever to quench!

Original astrobite edited by Ishan Mishra.

About the author, Sarah Bodansky:

I’m a first-year graduate student at the University of Massachusetts Amherst studying galaxies. My current research is focused on using observations to better understand the evolution of dust mass in star-forming galaxies. Outside of research, I enjoy reading, cooking, and hanging out with my cat.

Visualization of Earth's magnetic field

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

Title: Exoplanet Radio Transits as a Probe for Exoplanetary Magnetic Fields — Time-dependent MHD Simulations
Authors: Soumitra Hazra, Ofer Cohen, and Igor V. Sokolov
First Author’s Institution: University of Massachusetts Lowell
Status: Published in ApJ

Earth’s magnetic field protects our ozone layer from the solar wind and cosmic rays, keeping dangerous ultraviolet rays from reaching us. In exoplanet theory, magnetic fields may play an important role in determining how a planet evolves and whether it retains an atmosphere. But how can we study the magnetic fields of planets so far away? Today’s article explores the radio transit method as an indirect way to measure these fields.

Radio Transits

Astronomers have observed natural radio emissions from Jupiter and other solar system planets, produced by the interaction of their magnetic fields with the solar wind, a continuous flow of particles from the Sun. However, this type of signal is generally too weak for current telescopes to detect at interstellar distances.

The majority of known exoplanets today have been discovered with the transit method, which is typically performed at optical frequencies, where stars’ spectra peak. This method detects planets as they pass in front of their stars, causing periodic dips in the star’s apparent brightness. Today’s article explores a similar method to study exoplanets at radio frequencies, as their magnetic fields affect the star’s thermal radio emission.

The outermost part of a star is called the corona, and it extends far beyond the photosphere, becoming less dense (and less hot) with increasing distance. This plasma emits radio waves via thermal bremsstrahlung emission, where charged particles in electric fields lose some of their kinetic energy by emitting electromagnetic waves. A very close-in planet (e.g., a hot Jupiter) and its magnetic field can interact with the star’s corona, altering this radio output and perhaps producing an observable signal in radio light curves.

Modeling Star–Planet Interactions

The authors use the BATS-R-US model and the Alfvén Wave Solar Atmosphere Model to study the magnetohydrodynamical (MHD; a long word to describe the behavior of conductive fluids in magnetic and electric fields) interactions between a planet and its host star. The stellar model is based on real observations of HD 189733, the nearest star that hosts a transiting hot Jupiter. The model planet (an idealized version of the real hot Jupiter) is assigned a radius of 0.2 solar radius. They test three different magnetic field strengths for the planet: no magnetic field, an Earth-like magnetic field (0.3 Gauss), and a higher strength magnetic field (3 Gauss). They simulate each of these three planets with two circular orbital distances: 10 and 20 times the radius of the star.

For each of these magnetic field and orbit scenarios, the authors use a ray tracing algorithm to simulate the coronal emission’s path through the ambient medium, undergoing refraction. This allows them to create synthetic radio images at different points throughout the planet’s orbit, which are then turned into simulated light curves. Figure 1 below shows an example of these images.

simulated radio images of a planetary transit

Figure 1: Radio images from the model at 1 Gigahertz for the 3 Gauss, 10 solar radii orbit case. The middle panel shows the planet in transit, and the side panels show the planet at its farthest apparent separation from the star on either side. [Adapted from Hazra et al. 2022]

Coronal Compression

As the radio images in Figure 1 show, the planet warps the coronal material as it moves throughout its orbit, creating a ring of compressed material with higher emission around itself, as well as a tail trailing it in orbit. As this over-density of ambient material passes in front of the star, it refracts radio emission, causing variations in the star’s apparent brightness beyond the standard visual transit dip.

As one moves farther from the star, the material becomes cooler, and coronal emission peaks at lower frequencies. Thus, the size of the planet’s orbit impacts what we observe at different frequencies. For the close-orbit case (10 stellar radii), the planet passes through hot plasma regions, while the farther-orbit (20 stellar radii) planet passes through lower-density outer regions of the corona. Figure 2 below shows the light curves for the magnetized models in both orbits.

plots showing the model results for two different orbital distances

Figure 2: Radio light curves for simulated transits. The left panel shows the close-orbit results, and the right shows the far-orbit results. The solid lines on both panels represent their respective 0.3-Gauss model and the dashed lines, the 3-Gauss model. The line colors correspond to radio frequencies as indicated in the legend. Along the x axis, phase 0 begins when the planet is behind the star, and the mid-transit point at phase 0.5 is marked with a black dashed line. There’s a lot going on here during and surrounding the transit, but that’s the important result. We see very different light curves for different frequencies and model scenarios, indicating that observing light curves like this from real stars may actually allow researchers to constrain planets’ magnetic field strengths. [Adapted from Hazra et al. 2022]

Measuring Magnetic Fields

Ultimately, the goal of this radio transit method is to translate the radio modulation signal to a planetary magnetic field strength. The authors calculate the “extreme modulation,” or difference between the maximum and minimum flux points in the light curves. This modulation varies based on three factors examined: the planet’s orbital separation, the planet’s magnetic field strength, and the frequency observed.

The results suggest that radio observations across a range of frequencies could reveal information about a transiting planet’s magnetic field and thus its interior. The authors note that the thermal radio emission from stellar coronae is difficult to detect with current technology and only possible for a few nearby stars at this time. While this study focuses on planetary modulations on thermal radio emission from stellar coronae, stars also emit stronger transient radio signals (during flares, for example), which should be considered in future studies. Overall, detecting exoplanetary magnetic fields via radio transits is a promising method, and as stronger radio telescopes are constructed (e.g., the Square Kilometre Array), it becomes more feasible.

Original astrobite edited by Lindsay DeMarchi.

About the author, Macy Huston:

I am a fifth-year graduate student at Penn State University studying Astronomy & Astrophysics. My current projects focus on technosignatures, also referred to as the Search for Extraterrestrial Intelligence (SETI), and on microlensing searches for exoplanets.

Hubble image of an ultra-faint 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

Title: Pegasus W: An Ultra-Faint Dwarf Galaxy Outside the Halo of M31 Not Quenched by Reionization
Authors: Kristen B. McQuinn et al.
First Author’s Institution: Rutgers University
Status: Accepted to ApJ

Our local patch of the universe is populated by a number of galaxies — the so-called “Local Group,” consisting of our very own Milky Way, the similar-in-mass Andromeda Galaxy (Messier 31), and between 50 and 100 known “dwarf” or low-mass galaxies. The faintest, least massive of these, termed ultra-faint dwarfs, range in mass from a few thousand solar masses down to just a few hundred solar masses! Ultra-faint dwarfs in the Local Group are of immense interest to astronomers, since they can be used to study a variety of phenomena ranging from dark matter dynamics to stellar feedback, and from chemical evolution to ram pressure stripping. Owing to the low mass and weak gravitational potentials of ultra-faint dwarfs, these various physical processes often have outsize effects on their stars and gas, making them ideal objects for study.

Today’s authors report the discovery of a new ultra-faint dwarf named Pegasus W and analyse some of its interesting properties. Most ultra-faint dwarfs are extremely difficult to detect as they are faint and often diffuse — in fact, looking at a simple image of one may not even reveal its presence, as Figure 1 shows! Therefore, they are often detected by looking for statistical overdensities of stars in large sky surveys, and that’s exactly how Pegasus W was discovered from Dark Energy Spectroscopic Instrument (DESI) data. The authors of today’s article then followed up with Hubble Space Telescope imaging to study the stellar populations in the galaxy.

plots of observations indicating the presence of an ultra-faint dwarf galaxy

Figure 1: Left-hand panel shows a Hubble Space Telescope image of the area of the sky where Pegasus W is located. The right panel shows a view of the stellar density distribution, with the contours highlighting the over-density of stars that indicates the presence of Pegasus W. [Adapted from McQuinn et al. 2023]

Pegasus W is about 3 million light-years from the Milky Way. It’s closer to Andromeda, but still outside Andromeda’s virial radius (a measure of how far a galaxy’s gravitational influence extends). Therefore, it is not considered a satellite of Andromeda but rather an isolated ultra-faint dwarf galaxy. It is also quite faint, with a V-band absolute magnitude of about 7.2 and an estimated stellar mass of only 6.5 x 104 solar masses!

One of the most important properties of a galaxy is its star formation history — a fossil record of how it assembled and grew over time. Local Group dwarf galaxies are especially well suited for star formation history studies because of how nearby they are. The Local Group is the only place in the entire universe where we can get resolved photometry (imaging) of the individual stars in a galaxy, whereas for all other galaxies farther away we can only observe their starlight as an unresolved blob! This is key for measuring accurate star formation histories, since resolved stellar imaging allows us to build a colour–magnitude diagram for a galaxy — a plot of all its stars comparing their luminosities to their temperatures. After constructing a galaxy’s colour–magnitude diagram, we can fit stellar evolution models to it to figure out how old its various stellar populations are, and this allows us to reverse-engineer the entire record of how it formed its stars over cosmic time!

Figure 2 shows how this analysis was carried out for Pegasus W. The top-left panel shows the observed colour–magnitude diagram for the galaxy, with the top right being the best-fit diagram from stellar evolution modelling. The bottom left shows the residuals (i.e., what results from subtracting the model from the data). The residual significance diagram on the bottom right shows a checkerboard pattern, which indicates that the model is a good fit.

simulated and observed color-magnitude diagrams

Figure 2: Top left: Observed colour–magnitude diagram for Pegasus W from resolved stellar imaging. Top right: Colour–magnitude diagram reconstruction using stellar evolution models. Bottom left: Residual resulting from subtracting the model from the data. Bottom right: Residual significance diagram showing that the model is a good fit. [McQuinn et al. 2023]

Figure 3 shows the star formation history that the authors inferred for Pegasus W. The y axis shows the fraction of its final stellar mass, and the x axis shows lookback time from present day (right-hand side being present day and the left-hand edge representing the Big Bang). The red curve shows the growth of Pegasus W’s stellar mass over time, with the orange shaded region representing the uncertainty on the star formation history.

plot of star formation history for Pegasus W

Figure 3: Star formation history for Pegasus W, showing the fraction of its present-day stellar mass at various points in time from the Big Bang (left-hand edge) to present day (right-hand edge). The orange shaded region represents the error on the star formation history, while the grey shaded region represents the epoch of reionisation. [McQuinn et al. 2023]

The authors note what is most unique about Pegasus W: most ultra-faint dwarfs known to date have very short star formation histories at very early times. That is, most ultra-faint dwarfs formed all their stars at early cosmic times and were quenched (ceased forming stars) over 10 billion years ago. Astronomers believe that this early quenching was likely due to cosmic reionisation, when the hydrogen gas in the universe went from neutral to ionised due to radiation from the first stars and galaxies. However, as Figure 3 shows, Pegasus W does not appear to have quenched during reionisation (indicated by the vertical grey shaded region) and continued forming stars well after!

The puzzle of Pegasus W’s star formation history is likely to generate significant debate amongst astronomers studying galaxy evolution and reionisation. The authors note that better photometric data and perhaps even spectroscopy would help improve the uncertainty on the star formation history measurements, and that JWST is likely to help shed more light on this mystery in coming years.

Original astrobite edited by Isabella Trierweiler.

About the author, Pratik Gandhi:

I’m a 3rd-year astrophysics PhD student at UC Davis, originally from Mumbai, India. I study galaxy formation and evolution, and am really excited about the use of both simulations and observations in the study of galaxies. I am interested in science communication, teaching, and social issues in academia. Also a huge fan of Star Trek, with Deep Space Nine and The Next Generation being my favourites!

1 2 3 34