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NGC 4151

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

Title: XRISM Spectroscopy of the Fe Kα Emission Line in the Seyfert Active Galactic Nucleus NGC 4151 Reveals the Disk, Broad-line Region, and Torus
Authors: XRISM Collaboration
Status: Published in ApJL

Today we’re going to be taking a high-resolution look at X-rays from close to a supermassive black hole! But before we get into the astrophysics of today’s article, we first need to discuss the instruments that were built to do this science. More than 50 years ago now, charge-coupled devices (CCDs) began revolutionizing astronomy, and they continue to be one of the most commonly used detectors on telescopes. CCDs rely on the photoelectric effect, through which an incoming photon can liberate electrons in some material (semiconductors in the case of CCDs). These electrons are trapped by strong potential wells and electric charge can be applied to move the charge along and read this signal (check out this Astrobite for more details). CCDs are particularly powerful in the X-ray band, where the number of electrons trapped in each pixel scales roughly with the photon energy. This means that you get energy information (i.e., a spectrum) for free with CCDs! However, CCDs have limited spectral resolution, meaning they can’t determine this energy very precisely and therefore cannot resolve and unlock the power of narrow emission and absorption lines.

X-Ray Microcalorimetry and 20/20 Vision

cartoon of a microcalorimeter

Figure 1: Schematic showing how a microcalorimeter works. An X-ray photon with energy E will produce a spike in the temperature of the absorber of E/C, where C is the heat capacity of the absorber. The thermometer is extremely sensitive to small changes in temperature, which means that we can get very accurate energies for each of the incoming X-ray photons. Therefore, a microcalorimeter can produce an X-ray spectrum with the best energy resolution of any current instrumentation. [NASA]

There are other ways to get better spectral resolution in the X-ray, including using gratings that will disperse your spectrum, as is commonly done with optical spectroscopy. However, even these techniques can’t reach the high spectral resolution needed; instead, new technology called a microcalorimeter has been engineered to solve this long-standing issue. As the name suggests, this instrument detects incoming photons by measuring tiny (micro) changes to the temperature (calorimetry) of the detector. Figure 1 shows the basic set-up of a microcalorimeter and how the energy of the photon is encoded in the strength of the resulting temperature fluctuation. In order to detect tiny changes to the temperature, microcalorimeters need to be extremely cold, 50 millikelvin to be precise! This is a huge engineering feat, but one that has recently been achieved by the X-ray Imaging and Spectroscopy Mission (XRISM)! XRISM is a JAXA/NASA collaborative mission, and it has two instruments on board: a CCD camera called Xtend and a microcalorimeter called Resolve. It was launched in September 2023, and its first science results are just starting to roll in!

Now, XRISM isn’t actually the first X-ray microcalorimeter to fly, but it’s the first to live through its commissioning phase! Although the X-ray microcalorimeter has been in the works since the 1990s, previous X-ray microcalorimeters have been cut from missions, lost to launch failures, and left unable to operate due to loss of coolant for the detector. In 2016, JAXA successfully launched and operated the first X-ray microcalorimeter on the Hitomi Satellite. However, unfortunately, shortly after taking a beautiful spectrum of the Perseus Cluster, one of the best-studied galaxy clusters in the local universe, communication was lost with the satellite and never recovered. XRISM’s Resolve instrument has been the most successful X-ray microcalorimeter so far, and it has allowed us to start looking at the universe with 20/20 X-ray vision!

Supermassive Science with XRISM

Today we’re going to put on our high-resolution X-ray spectroscopy glasses to look at one of the first XRISM targets: NGC 4151, one of the most well-known active galactic nuclei in the local universe. An active galactic nucleus consists of a supermassive black hole that is gobbling down gas from its surroundings through a process known as accretion. While we’ve known about active galactic nuclei for more than 50 years now, we still don’t really understand how they are fueled and what the structure is around them. XRISM can unlock this information indirectly by resolving some of the key X-ray emission and absorption lines. In particular, the most prominent emission line in the X-ray spectrum of an active galactic nucleus is a neutral iron Kα line at 6.4 kiloelectronvolts (keV), which arises from material around the supermassive black hole being illuminated by the light from the accretion process. This line holds the keys to probing the structure of the surrounding gas, as its dynamics can tell us about the structure of the accretion disk and trace gas in the torus that is thought to connect the local host galaxy to the accretion flow.

Figure 2 shows the XRISM Resolve spectrum of NGC 4151 from two separate observations. The spectrum shows a prominent 6.4 keV line that is resolved, meaning that the measured width of the line is greater than the instrument’s resolution limit. Additionally, the line cannot be fit with a single emission line and instead requires multiple lines, signaling multiple physical scales contributing to this emission line. The right panels of this figure highlight that there are three distinct components to this emission line with broad (magenta), intermediate (dark blue), and narrow (cyan) widths. Since gas that is closer to the black hole will be moving faster than more distant gas, the authors can use these line widths to estimate where this gas is located. They find that these three lines range from about 100 gravitational radii (about 100 times the size of the black hole) to about 10,000 gravitational radii. Determining the multi-scale nature of this line has been extraordinarily difficult to detect with other instruments due to their limited energy resolution!

XRISM resolve spectra of NGC 4151

Figure 2: XRISM Resolve spectra of NGC 4151. The left panels show the spectrum in the 5.8-7.2 keV range from two separate observations, with the data in black and the best fit total model in red. The right panels show a zoom in on the iron Kα 6.4 keV line with the three different components for the line also shown. The magenta model corresponds to the widest line, arising potentially from a warped disk, the dark blue model corresponds to the intermediate width line coming from the inner edge of the broad line region (BLR), and the cyan model corresponds to the most narrow line that arises from the inner edge of the dusty torus. [XRISM Collaboration et al. 2024]

Together these three components to the iron Kα line provide a compelling picture for the nuclear structure, which is shown in Figure 3. There are some additional pieces of evidence from the data that support this model as well. For example, the broadest line (magenta) shows variability on timescales of less than a day. This timescale corresponds roughly to the distance light could travel before reaching the magenta part of this figure, supporting the idea that there is a broad component associated with the disk. In addition to the location of the emitting gas, the dynamics and density can be constrained using the energy and shape of the line, respectively. In this source, the line is at the rest-frame energy and the shape is relatively symmetric, which together suggest that the emission comes from relatively optically thin gas that has not been accelerated to high velocities. Together, these diagnostics give one of the most in-depth pictures of supermassive black hole environments to date and will be crucial for testing our models of black hole feeding!

Schematic highlighting where each of the iron Kα emission lines arise from

Figure 3: Schematic highlighting where each of the iron Kα emission lines arise from. The magenta component corresponds to the broadest line, potentially from a warp in the disk. The dark blue component corresponds to the intermediate-width line and arises from the inner edge of the broad line region (BLR). The cyan component corresponds to the narrowest line and arises from the inner edge of the active galactic nucleus torus. [XRISM Collaboration et al. 2024]

What’s Next?

These XRISM observations are rich with information, and today’s article focused only on the 6.4 keV emission line. The authors are planning a series of further articles, including on the active galactic nucleus winds traced by the absorption lines (i.e., the major dips seen at ~6.7 and ~7 keV in the left panels of Figure 2), comparisons of the emission lines with optical emission lines, and looking for faint evidence of broader emission from even closer to the supermassive black hole. The next obvious steps are also to observe more active galactic nuclei to test whether this multi-zone emission is a common occurrence in active galactic nuclei. One thing’s for sure, this 20/20 vision is sure to reveal new secrets about the lives and environments of supermassive black holes!

Original astrobite edited by Roel Lefever.

About the author, Megan Masterson:

I’m a 4th-year PhD student at MIT studying transient accretion events around supermassive black holes, including tidal disruption events and changing-look active galactic nuclei. I primarily use multi-wavelength observations to study from the inner accretion flow to the obscuring material in these transients. In my free time, you’ll find me hiking, reading, and watching women’s soccer.

illustration of Betelgeuse

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.

Betelgeuse within the constellation of Orion

Figure 1: A schematic of the Orion constellation, with a small pink arrow indicating the location of Betelgeuse in Orion’s left shoulder. Click to enlarge. [Wikipedia]

Betelgeuse (Figure 1) is one of the most famous stars in the sky. As the closest red supergiant to Earth, it provides a unique opportunity to study the final stages of massive stellar evolution. In 2020, it captured our attention with a substantial, unexpected decrease in brightness that astronomers thought could be a sign of an impending supernova. Though we have since figured out that this “Great Dimming” was likely caused by a dust cloud forming from ejected mass, the event highlighted just how much we still don’t understand about the behavior of this enigmatic star.

Red supergiants like Betelgeuse are known to experience radial pulsations: repeated expansion and contraction of the star’s outer layers that cause periodic fluctuations in brightness. Like standing waves on a string, these pulsations include both fundamental and higher-order modes, with the fundamental mode dictating the longest possible pulsation period. For Betelgeuse, astronomers have measured a fundamental-mode period of about 420 days. However, they have also observed a long secondary period of 2,100 days, the origin of which is a mystery. Or is it?

Today’s bite covers two articles that independently reach the same conclusion: Betelgeuse’s long secondary period is caused by the presence of a low-mass binary companion! Such a small star would be drowned out by Betelgeuse’s intrinsic brightness and variability, explaining why we haven’t detected it before. But as today’s articles show, careful analysis of radial velocity and astrometry data can tease out signatures of Betelgeuse’s hidden buddy.

Article 1: One Long-Secondary-Period Mechanism to Rule Them All

Title: A Buddy for Betelgeuse: Binarity as the Origin of the Long Secondary Period in α Orionis
Authors: Jared A. Goldberg, Meridith Joyce, and László Molnár
First Author’s Institution: Flatiron Institute
Status: Published in ApJ

In Article 1, the authors use light curves from the American Association of Variable Star Observers (AAVSO) and radial velocities from STELLA to test the plausibility of eight different explanations for Betelgeuse’s long secondary period. Light curves are a record of how a star’s brightness (or magnitude) changes over time, and radial velocities record how quickly a star is moving towards or away from us. For Betelgeuse, both datasets show the ~2,100-day long secondary period. The authors measure a phase offset between the datasets of about −2 radians, meaning that the radial velocity curve lags behind the light curve by about half an orbit. With these data in hand, they are able to rule out all proposed long-secondary-period mechanisms that don’t involve a binary companion. For example:

  1. Is the long secondary period really the fundamental mode? No! If this were the case, Betelgeuse would need to have a much larger radius than what we’ve measured. The ~420-day fundamental mode aligns much more closely with our observations.
  2. Is the long secondary period caused by the motion of convective cells on Betelgeuse’s surface? No! Convection would introduce random variability that we don’t observe. Plus, we expect convective motions on the surfaces of all luminous giant stars, but we know that not all of these stars show long secondary periods like Betelgeuse does.
  3. Is the long secondary period caused by starspots coming in and out of view? No! Betelgeuse’s long-secondary-period variations are stronger at bluer wavelengths than redder wavelengths, which starspots can’t replicate. We’d also expect Betelgeuse’s magnetic activity cycle to have a longer period than the long secondary period.

The authors conclude the long secondary period is most likely caused by binarity. However, a small companion passing in front of Betelgeuse would not cause noticeable dimming compared to the variability from pulsations. Since red supergiants like Betelgeuse have dusty circumstellar environments, previous work suggested that a hypothetical companion could drag a cloud of dust along with it to produce more significant dimming. This theory would also explain why long-secondary-period variations are stronger at bluer wavelengths, where dust scatters more light than at redder wavelengths.

There’s just one problem: the measured phase offset of −2 radians suggests that the companion would be in front of Betelgeuse when the system reaches maximum brightness, not behind it as the above theory suggests. To address this, the authors propose that rather than dragging dust along, the companion somehow destroys or modifies dust to cause an increase in Betelgeuse’s brightness as it passes in front of the larger star (see Figure 2). However, they note that future work is necessary to determine exactly how this could occur.

observed and modeled light curve and radial velocity curve for Betelgeuse

Figure 2: A sketch showing how Betelgeuse’s light curve variability (top graph) and radial velocity variability (bottom graph) can be explained by the presence of a binary companion. The light curve is noticeably out of phase with the radial velocity curve, as found in both articles. The middle row of drawings shows what an observer on Earth would see at each of the four points labeled on the two graphs. Betelgeuse is shown as a red circle, its hypothetical companion is shown as a black circle, and its circumstellar dust is shown as curly orange and red lines. Note that at maximum brightness (Point C), the companion is in front of Betelgeuse instead of behind it. [Goldberg et al. 2024]

From their radial velocity data, the authors estimate a lower mass limit of 1.17 ± 0.07 M☉ (just a little bigger than our Sun!) and an orbital separation of 1,850 ± 70 R☉ for Betelgeuse’s companion. As expected, they find that such a small star would be nearly impossible to detect so close to Betelgeuse, which is much brighter, larger, and more variable than its hypothetical buddy.

Article 2: Finding Binarity in a Century’s Worth of Data

Title: Radial Velocity and Astrometric Evidence for a Close Companion to Betelgeuse
Authors: Morgan MacLeod et al.
First Author’s Institution: Center for Astrophysics | Harvard & Smithsonian; Institute for Theory and Computation
Status: Published in ApJ

In Article 2, the authors leverage more than 100 years of radial velocity data — including the radial velocities from Article 1 and several other, independent datasets — to search for a binary companion to Betelgeuse. First, they construct a model including the unseen companion, a flexible Gaussian process kernel to represent variability from other sources, and a noise term. Then, they fit their radial velocities with this model to retrieve the period, phase, and amplitude of the long-secondary-period signal (see Figure 3).

plots of observed and modeled radial velocity data for Betelgeuse

Figure 3: Results of fitting a model (blue lines) to 100 years of radial velocity data (black points). The top panel shows the full model, including the flexible kernel used to fit all variability sources other than the long secondary period (labeled “GP” here for “Gaussian process”). The middle panel shows just the sinusoidal component of the fit that represents the long secondary period, which remains a good fit over the whole baseline. The bottom panel shows the residuals after the full model (from the top panel) is subtracted from the data. [MacLeod et al., in press]

The authors find that their century-long dataset is well-described by a single periodic signal, implying that the long secondary period is stable over time. This supports binarity as the long-secondary-period mechanism, since other mechanisms like convection would show random variations over such a long timescale. By comparing their radial velocities with the AAVSO light curve (which provides coverage all the way back to 1920!), the authors also find a phase offset of about one-half of an orbit, in good agreement with the results from Article 1.

Using their fitted parameters, the authors derive a mass of 0.60 ± 0.17 M☉ and an orbital separation of 1,818 ± 6 R☉ for Betelgeuse’s hidden companion. This mass is significantly smaller than the estimate from Article 1, which the authors attribute to differences in the fitted long-secondary-period amplitudes between the articles. Betelgeuse’s radial velocity curve includes multiple sources of variability from radial pulsations, the signature from the binary companion, and other random changes. As a result, the true amplitude of the long-secondary-period variations is highly uncertain, even when the period is well constrained.

In addition to radial velocities, the authors also investigate Betelgeuse’s long secondary period with astrometry. Astrometric data record the relative positions and motions of the stars, which are expected to follow predictable patterns. An unseen binary companion will introduce an extra “wobble” in this pattern by tugging the visible star back and forth as it moves through space. These wobbles can be modeled to determine the orbital parameters of the binary, which should agree with the parameters derived from radial velocity data.

The authors fit a model to their astrometry and find two prominent periods: 1) the long secondary period at ~2,100 days and 2) an unexpected periodicity at ~1,650 days (about four times the fundamental mode). They also find a variability amplitude that is higher than their fitted radial velocity amplitude, implying a companion mass of 2.1 ± 0.5 M☉. However, their data are fit equally well by a binary model or a single-star model that includes a significant noise term. This is likely due to the fact that Betelgeuse’s radial extent is larger than its expected astrometric wobble, making precise astrometric measurements difficult. The authors conclude that additional observations are needed to constrain the binarity of Betelgeuse with astrometry, noting that their radial velocity results are more trustworthy given the longer baseline, higher cadence, and higher precision of the radial velocity data.

Using their measured parameters of the Betelgeuse system, the authors calculate the evolution of the hypothetical binary due to tides. Just like the Moon’s gravitational pull creates tides on Earth, the stars in a binary system pull on each other as well, dissipating angular momentum from the system and moving closer together in a process called “orbital decay.” In the case of Betelgeuse, the authors find that tides will cause runaway orbital decay over the next 10,000 years, where the system will be unable to stabilize as the orbital separation shrinks. This means Betelgeuse will interact with and eventually swallow its tiny companion!

Staying Hidden… for Now

Despite using different datasets and fitting methods, both of today’s articles find evidence that the ~2,100-day long secondary period in Betelgeuse’s light curve is likely due to the presence of a previously undetected, low-mass binary companion. Direct detection of such a companion is nearly impossible with current instruments, but further study of the dust around Betelgeuse could help constrain the companion’s properties. If confirmed, Betelgeuse’s binarity would have significant implications for both its evolution and for other evolved stars with long secondary periods, which may also host hidden binary buddies!

Original astrobite edited by Lindsey Gordon.

About the author, Alexandra Masegian:

Alexandra is a second-year PhD student in astronomy at Columbia University and the American Museum of Natural History. She is broadly interested in stellar astrophysics, especially evolved stars and binaries. Outside of work, she enjoys cooking, reading and writing science fiction, and visiting national parks.

Stellar bow shock

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: Probing the Low-Velocity Regime of Nonradiative Shocks with Neutron Star Bow Shocks
Authors: Stella Koch Ocker and Maren Cosens
First Author’s Institution: California Institute of Technology and Observatories of the Carnegie Institution for Science
Status: Published in ApJL

Neutron stars are fascinating remnants of massive stars that have undergone a supernova explosion. These stellar remnants often move at incredible speeds through space, producing bow shocks, the regions where the fast-moving neutron star collides with interstellar gas. Imagine a cosmic wind so powerful that it creates a shock wave in space, much like a speedboat cutting through water. These powerful shock waves hold clues to study non-radiative shocks, which play an important role in heating plasma and accelerating particles, such as cosmic rays. Today’s article took a closer look at the properties of three neutron-star bow shocks in unprecedented detail, revealing new insights into the hidden physics behind these cosmic collisions.

What Are Bow Shocks?

Image of the LL Orionis bow shock taken with the Hubble Space Telescope

Figure 1: Image of the LL Orionis bow shock taken with the Hubble Space Telescope. [NASA and The Hubble Heritage Team (STScI/AURA); Acknowledgment: C. R. O’Dell (Vanderbilt University)]

A bow shock forms when a fast-moving object, like a neutron star, passes through a medium — in this case, the interstellar medium, the gas and dust that fills the space between stars. The interaction between the neutron star’s wind and the interstellar medium causes form a shock wave, which resembles the bow wave that forms at the front of a boat moving through water (for example, see Figure 1).

In the context of neutron stars, the bow shock is non-radiative, meaning it does not emit much in the form of light or heat. However, the shock does produce a particular type of emission called Hα (hydrogen alpha), which occurs when neutral hydrogen atoms in the interstellar medium are excited and emit light at a specific wavelength in the optical wavelength range. Observing this Hα emission is one of the main ways astronomers can study neutron-star bow shocks.

Understanding the Shock’s Velocity and Structure

Today’s authors focused on three known neutron-star bow shocks (see Figure 2): J0742−2822, J1741−2054, and J2225+6535 (also known as the “Guitar Nebula”). Using integral field spectroscopy, a technique that captures both the spatial and spectral information of an object, they were able to observe these bow shocks in detail. For their observations, they used the Keck Cosmic Web Imager (KCWI) on the Keck II Telescope in Hawaii. Unlike traditional spectroscopy, which provides a one-dimensional spectrum of light from a single region, integral field spectroscopy collects spectra across a two-dimensional field, allowing the astronomers to map the shock properties. This allows astronomers to study the shock shape, velocity structure, and Hα emission intensity in exquisite detail, giving a more complete picture of how these shocks behave.

neutron-star bow shock images

Figure 2: KCWI data of the three neutron-star bow shocks, showing the morphologies of each bow shock at different velocity slices. [Ocker & Cosens 2024]

Studying the relative contributions to the Hα emission is crucial to unlocking the detailed shock physics.  There are two main components to the Hα emission: a narrow line that represents the ambient gas in the interstellar medium and a broad line produced by the shock itself. The ratio between these two lines, the broad-to-narrow line intensity ratio (Ib/In), provides crucial information about the velocity of the shock and the processes occurring within it, including the electron-ion temperature and the particle energy distribution.

The study revealed that the Ib/In values for all three neutron-star bow shocks indicated low shock velocities, all below 200 kilometers per second. This is notably different from the much higher velocities seen in supernova remnants, where shocks can exceed 1,000 kilometers per second. These results suggest that neutron-star bow shocks operate in a distinct low-velocity regime, and current models, which are designed for higher-velocity shocks, may not fully capture the behavior of these slower shocks. To better understand the temperature ratios between electrons and ions, as well as how particles are accelerated in this regime, new models are needed.

Why Is the Low-Velocity Regime Important?

Understanding the low-velocity regime of non-radiative shocks is important for several reasons:

  • Cosmic-Ray Acceleration: Non-radiative shocks are believed to accelerate particles to very high speeds, contributing to the population of cosmic rays — high-energy charged particles that travel through space. Studying how these shocks operate at different velocities helps scientists understand how cosmic rays are produced and what role neutron stars might play in this process.
  • Energy Transfer in Shocks: Non-radiative shocks are also key to understanding how energy is transferred between different types of particles, such as electrons and protons. In faster shocks, the temperature of electrons and protons can differ significantly, but in slower shocks, like those studied here, the temperatures might be more equal. Understanding this balance provides insight into the physics of shock waves and how they heat and accelerate particles.
  • Astrophysical Modeling: Most models of non-radiative shocks are based on high-velocity shocks in supernova remnants. However, the findings from this study suggest that these models need to be expanded to include slower shocks, which behave differently and require new theoretical approaches.

This study provides critical new insights into the enigmatic nature of neutron-star bow shocks, particularly in the unexplored low-velocity regime. By probing these slow shocks, we unlock a deeper understanding of how astrophysical plasmas are heated and how particles are accelerated to cosmic-ray speeds — shedding light on some of the most powerful processes in the universe. The findings challenge existing models of non-radiative shocks, emphasizing the need for new theory to capture the unique behavior of these slower shocks. As a result, this research not only reshapes our understanding of cosmic rays but also paves the way for exciting new directions in astrophysics, with potential breakthroughs on the horizon.

Original astrobite edited by Megan Masterson.

About the author, Janette Suherli:

Janette is a PhD student at University of Manitoba in Winnipeg, Canada. Her research focuses on the utilization of integral field spectroscopy for the studies of supernova remnants and their compact objects in the optical. She is also the current chair of Graduate Student Committee for the Canadian Astronomical Society (CASCA). She grew up in Indonesia where it is summer all year round! Before pursuing her PhD in astrophysics, Janette worked as a data analyst for a big Indonesian tech company, combating credit card fraud.

illustration of planets colliding

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: Accelerating Giant Impact Simulations with Machine Learning
Authors: Caleb Lammers et al.
First Author’s Institution: Princeton University
Status: Published in ApJ

Planet Formation

In the nebular hypothesis view of planet formation, planets form out of a protoplanetary disk, starting out as small dust grains, some of which combine and grow to form planetesimals and eventually planets. Part of this process is the giant-impact phase, in which the planetesimals experience frequent, violent collisions, leading to the growth of what will eventually become fully fledged planets.

Numerically modeling the giant-impact phase is complicated by the computational difficulty of running simulations of many bodies over long timescales. Machine learning has already been adopted to improve and speed up planetary simulations, such as with the Stability of Planetary Orbital Configurations Klassifier (SPOCK) package. SPOCK’s first incarnation (SPOCKI) predicts whether a compact planetary system is stable over 1,000,000,000 orbits based on the results of a shorter 10,000-orbit integration, and an extension (SPOCKII) uses those results to predict when a planetary system will destabilize.

Creating a Machine Learning™ Framework

Today’s article extends previous work by using machine learning to predict the outcomes of planet–planet collisions in three-planet systems with two subtasks: 1) predicting which planet pair will collide and 2) predicting the orbital configuration of the resulting system. The authors use supervised learning: giving a model a training set with inputs and correct outputs so that the model can learn the mapping from inputs to outputs. Predicting collisions (subtask 1) requires classification, producing an outcome from a set of discrete options or categories (in this case, which planets collide). Predicting resulting orbital configurations (subtask 2) requires regression, producing numerical values describing the orbit of the post-collision system. The authors use a training set of more than 500,000 N-body simulations integrated with the REBOUND package. They initialize tightly packed three-planet systems with randomized initial conditions and integrate the systems for 10,000,000 orbits (of the innermost planet) with mass and momentum conservation. The authors only keep the systems with mergers between 10,000 and 10,000,000 orbits so the machine learning framework does not concern itself with non-merging systems.

The authors use separate multi-layer perceptron models independently trained on 80% of the training set (leaving the rest as a validation set) to complete both subtasks, following the schematic shown in Figure 1. The collision classifier takes as inputs the orbital elements of the three planets after they’ve completed 10,000 orbits, generates the probabilities of planet-pair collisions, and samples the probabilities to determine which pair of planets collide. The orbital outcome regressor takes the orbital elements of the three planets and the choice of which planets collide to predict the new orbital elements (semi-major axis, eccentricity, and inclination) of the resulting system.

schematic of the machine learning framework

Figure 1: A schematic of the machine learning model in which a classifier predicts which pair among three planets collides and a regressor predicts the orbital configuration of the two resulting planets. [Lammers et al. 2024]

Piecing Together the Giant-Impact Emulator

The authors combine their machine learning model with SPOCKII to create an iterative emulator to model the giant-impact phase, with a schematic shown in Figure 2. The emulator takes in overly packed, multi-planet systems with randomly initialized configurations, groups the systems into trios of planets, uses SPOCKII to predict when the systems will destabilize, merges the most unstable trio, and then repeats until stability is achieved. The authors also run N-body simulations for 500 ten-planet systems for comparison with the results of the emulator. As shown in Figure 3, there is close agreement with masses, spacings, inclinations, and most system-level properties.

demonstration of the iterative model of the emulator

Figure 2: A schematic of the giant-impact emulator in which a multi-planet system is broken into trios. The machine learning model shown in Figure 1 predicts the results of a collision in the most unstable trio, and the process repeats until a stable system is formed. [Lammers et al. 2024]

comparison of the properties of the N-body and machine learning–based planetary systems

Figure 3: A comparison of the properties of the N-body (red) and machine learning–based (blue) planetary systems resulting from giant impacts. The machine learning–based framework produces largely similar results except that machine learning tends to produce systems that are less dynamically excited (bottom right). [Lammers et al. 2024]

In comparison with the N-body simulations, the machine learning–based emulator is ~10,000 times faster. The collision classifier model predicts probabilities with a scatter of ~10% and minimal offsets from the N-body-derived probabilities. The orbital outcome regressor predicts orbital configurations for the validation set almost at the accuracy limit set by chaos inherent in N-body dynamics.

Planet formation is a messy, unsolved problem. Until the discovery of exoplanetary systems, we had only the solar system and its single formation outcome to study. It turns out that nature produces a beautiful mosaic of planetary systems, many of which bear little resemblance to our own. The giant-impact phase has long been a bottleneck in simulating planet formation due to computational constraints, and today’s article presents a truly exciting advancement in modeling planet–planet collisions. The model is limited in that it breaks multi-planet systems into trios of adjacent planets and models collisions and scattering only within trios, though the authors expect this is a minor effect. The model is publicly available and will certainly expand the frontier of possible planet formation analyses.

Original astrobite edited by Nathalie Korhonen Cuestas.

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.

Jellyfish galaxy ESO 137-001

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: Dark-Matter-Free Dwarf Galaxy Formation at the Tips of the Tentacles of Jellyfish Galaxies
Authors: V. Lora et al.
First Author’s Institution: Institute of Nuclear Sciences, Mexico (UNAM)
Status: Published in ApJL

When Jellyfish Fly

Most galaxies are part of a galaxy cluster, which is exactly what it sounds like — a large collection of galaxies that are gravitationally bound to the larger cluster, much like how stars are gravitationally bound to a larger galaxy. In addition to the galaxies themselves, there is also gas between the galaxies in the cluster, referred to as the intracluster medium. When a disk-like galaxy moves through the intracluster medium in a galaxy cluster, some of the gas within the galaxy (the interstellar medium) gets stripped away from the galaxy. This creates long gaseous tails (or, if you will, tentacles), giving the galaxy an uncanny resemblance to a jellyfish!

Jellyfish galaxies, and their tentacles in particular, have been studied for decades. Astronomers have investigated how much of the gas in the tentacles comes from the intracluster medium versus the interstellar medium, as well as where and how star formation occurs within the tentacles. Interestingly, astronomers have found star-forming regions in the tentacles that have similar masses and sizes to ultra-compact dwarf galaxies. Today’s authors look to reproduce those results computationally and better understand how this dwarf galaxy formation channel works.

Hanging On by a Tentacle

The authors use data from the IllustrisTNG50 simulation, a cosmological simulation large enough to form dozens of galaxy clusters with enough resolution to accurately model features such as the arms of spiral galaxies. The authors identify a set of jellyfish galaxies within this simulation, then make additional cuts to

  • ensure the galaxies have obvious tentacles;
  • find locations of star formation within the tentacles; and
  • eliminate galaxies where tentacle-like features could be due to interactions with other galaxies.

These cuts leave only one galaxy with a mass of ~400 billion solar masses; compare this to the mass of the Milky Way, which is typically reported as ~1 trillion solar masses. (However, a 2023 study found that the Milky Way mass was closer to ~200 billion solar masses.)

The authors identify a star-forming site within one of the tentacles of this galaxy, highlighted in Figure 1. This both supports the observational evidence and suggests that this may be a new type of dwarf galaxy (more on this in a moment). Additionally, by tracking the galaxy’s history prior to the infall, they determine that the galaxy loses gas but not stars. This means that the gas in the tentacle came from the galaxy, but the stars are forming in the tentacle rather than being relocated from the galaxy. This is a consequence of ram-pressure stripping, the primary physical phenomenon that creates the tails of jellyfish galaxies. Another important finding about the dwarf galaxy candidate is that it lies well outside the dark-matter halo of the jellyfish galaxy, which has important ramifications for its status as a dwarf galaxy candidate.

Visualizations of a star-forming region in the tentacle of a jellyfish galaxy

Figure 1: Different visualizations of the selected galaxy. The top panel shows neutral gas (green), dark matter (white), and star formation (rainbow). The bottom panel shows the dark matter (white) and stellar mass (rainbow). The dwarf candidate is circled in magenta in both panels. [Lora et al. 2024]

Dark-Matter-Deficient Dwarfs

The authors perform additional analysis on the dwarf galaxy candidate. First, they determine that the gas and stars are gravitationally bound, meaning that they can be thought of as a single system much like how a galaxy is thought of as a single system. They also look at the dark-matter content of the dwarf galaxy candidate and find that none of it is gravitationally bound, making this a dark-matter-free dwarf galaxy. Furthermore, they estimate the mass and size of the dwarf galaxy candidate to be ~200 million solar masses and ~1–1.5 kiloparsecs. Based on these findings, the authors conclude that this system represents a new kind of dwarf galaxy, which they dub a ram-pressure-stripped dwarf galaxy; additionally, ram-pressure-stripped dwarf galaxies are unique among dwarf galaxies because they lack a dark-matter halo due to their creation via ram pressure stripping.

Plots of the star formation rate and the oxygen abundance

Figure 2: Star formation rate (top panel) and oxygen abundance (proxy for metal concentration, bottom panel) of the ram-pressure-stripped candidate (magenta). [Lora et al. 2024]

The authors also analyze the star formation and metallicity of the ram-pressure-stripped dwarf, shown in Figure 2. They find a high star formation rate compared to other star-forming regions created via ram pressure stripping. They also find that the ram-pressure-stripped dwarf is very metal rich compared to other dwarf galaxies of similar size and mass; this is because the jellyfish galaxy is also rich in metals, so the gas stripped into the tentacle to form stars has a higher concentration of metals.

Today’s authors have found evidence of a new type of dwarf galaxy, which they call a ram-pressure-stripped dwarf galaxy. These dwarf galaxies form via ram pressure stripping in the tentacles of jellyfish galaxies and are characterized as being gravitationally self-bound, hosting star formation, and lacking a dark-matter halo. The authors hope to continue studies of ram-pressure-stripped dwarf galaxies, noting that other cosmological simulations that can resolve smaller amounts of mass may lead to more discoveries of ram-pressure-stripped dwarfs with lower masses.

Original astrobite edited by Amaya Sinha.

About the author, Brandon Pries:

I am a graduate student in physics at Georgia Institute of Technology (Georgia Tech). I do research in computational astrophysics with John Wise, using machine learning to study the formation and evolution of supermassive black holes in the early universe. I’ve also done extensive research with the IceCube Collaboration as an undergraduate at Michigan State University, studying applications of neural networks to event reconstructions and searching for signals of neutrinos from dark matter annihilation.

Cas A 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: A JWST Survey of the Supernova Remnant Cassiopeia A
Authors: Dan Milisavljevic et al.
First Author’s Institution: Purdue University
Status: Published in ApJL

Cassiopeia A, or Cas A for short, is in many ways the golden child of supernova remnant astronomy, a field that studies the hot clouds of gas and dust produced by the explosive deaths of stars. Beautiful and with a wealth of insights on stellar death to be gleaned from its billowy filaments, Cas A has mesmerised astronomers since its nascent glow first lit up the night sky in the late 17th century.

The hype behind Cas A has been sustained by the launch of new facilities, which provide increasingly detailed views of the dusty, gaseous nebula that was left behind by the cataclysmic explosion of a star 15–20 times the mass of the Sun. Luckily for the die-hard Cas A fans, JWST has obtained incredibly detailed images of the remnant’s near- and mid-infrared emission in the ~1.5 to ~26.7 microns (1 micron = 10-6 meter) range using a variety of filters referred to by their JWST filter name (e.g., F120W). These images are the focus of today’s article that studies Cas A’s structure and searches for evidence of its central neutron star.

NIRCam and MIRI images of Cas A

Figure 1: NIRCam (top) and MIRI (bottom) images of Cas A collected using JWST. The filters used to construct each image are listed in the top right corner. [Milisavljevic et al. 2024]

Using both the Near-Infrared Camera (NIRCam) and the Mid-Infrared Instrument (MIRI), the authors of today’s article have uncovered several surprising details about Cas A’s structure. The images are shown in Figure 1, with the NIRCam image above and the MIRI image below. These images are more spatially resolved than those seen previously using other facilities such as the Hubble Space Telescope, allowing the authors to identify a number of important features. For example, supernovae that produce remnants like Cas A are known to produce a shock wave from the star’s ejected material interacting with the surrounding gas. However, the authors detected a web-like ejecta structure that has not yet interacted with the supernova shock wave, arguing this is indicative of turbulent mixing processes that occurred shortly after the death of the star that produced Cas A. In addition, they resolved for the first time a feature they dubbed the “Green Monster,” which can be seen as the pock-marked, central green structure in the MIRI image in the bottom panel of Figure 1. They attributed the “Green Monster” to a thick sheet or sheets of infrared-emitting dust in the interior of the supernova remnant.

Not only did the authors consider Cas A’s structure in their article, they also searched for evidence of a central compact object such as a neutron star within its nebula. When massive stars die, they are expected to produce a compact object, be it either a black hole or neutron star. Therefore, astronomers are often eager to find evidence of these exotic objects in supernova remnant images. Previously, X-ray images from Chandra had revealed a point source at the centre of Cas A that was presumed to be its neutron star. Unfortunately, more recent visible and near-infrared Hubble and Spitzer images of Cas A did not show evidence of the reported central compact object. However, this result was not entirely unexpected given the expected low magnetic field strength of the neutron star or the high extinction (or dimming) of visible light, disfavouring the detection of the central compact object at wavelengths other than X-rays.

Given the non-detection in Hubble images, the authors of today’s article conducted a search for Cas A’s neutron star in their deeper JWST images. The results of this search are presented in Figure 2, which gives the flux density at the reported location of the neutron star as a function of frequency for the JWST, Hubble, Spitzer, and Chandra images of Cas A. In the figure, the red down arrows represent the JWST upper limits, meaning that no emission from the neutron star was detected using the deep JWST observations, but that emission is still possible at fluxes below these values. Figure 2 also shows the upper limits established from previous Spitzer and Hubble observations in grey, as well as the flux of the neutron star detected in Chandra X-ray observations in black. Additionally, the authors compared their results to three different models that could describe the neutron star emission given these upper limits, including power laws with indices of −2 and −1 in yellow and blue, respectively, and a blackbody with a temperature of 900K in red. While no neutron star was apparent in the JWST observations, the authors calculated a flux density upper limit of 20 nanoJanskys at a wavelength of 3 microns.

plot of flux density as a function of frequency

Figure 2: The flux density as a function of frequency for JWST (red), Spitzer (grey), Hubble (grey), and Chandra (black) observations of the location of Cas A’s neutron star. No emission from the neutron star was detected in JWST, Hubble, or Spitzer observations, which is indicated by the down arrows that represent the calculated upper limits on the flux from the neutron star. [Milisavljevic et al. 2024]

Thanks to the new JWST observations, there’s plenty of content to keep Cas A enthusiasts interested. Not only did the detailed images reveal new (and ominous) structures such as the “Green Monster,” but they also established deep upper limits on the infrared emission from the neutron star seen in X-ray observations. With additional JWST observations of Cas A, our picture of the galactic golden child will become even more intricate, so stay tuned.

Original astrobite edited by Ivey Davis.

About the author, Sonja Panjkov:

I’m a second-year PhD student at the University of Melbourne. My research focuses on the high-energy emission from the supernova remnants in the Magellanic Clouds. In my spare time, I enjoy hanging out with my cats and going to see live music.

Víctor M. Blanco 4-meter 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: The Dark Energy Survey: Cosmology Results with ~1500 New High-Redshift Type Ia Supernovae Using the Full 5-Year Dataset
Authors: Dark Energy Survey Collaboration
Status: Published in ApJL

The Dark Energy Survey (DES) Collaboration is an international team of scientists that aims to measure and understand the nature of an elusive energy density component in the universe, dark energy. The DES was conducted using the 4-metre Blanco Telescope at the Cerro Tololo Inter-American Observatory in Chile and took observations from 2013 to 2019. The survey used a special camera called the Dark Energy Camera (DECam). DECam has a wide field of view (about 14 times the size of the full Moon in the sky), allowing for detection of galaxies over a large sky area. It also allows for sensitive measurements of the redshifted light from these galaxies with a 570-megapixel camera with 74 CCDs with minimal readout noise in the measurements. This research article specifically focuses on the results of the DES supernova survey (more about their other survey data can be seen here), which was designed to test cosmology with a large sample of supernova observations.

In 1998, two teams of scientists measuring the brightness of supernovae unexpectedly discovered anomalously faint supernovae at specific times in the earlier universe, indicating that the universe is accelerating in its expansion (they got a Nobel Prize for this discovery). Before 1998, cosmologists believed in three possibilities for future expansion of the universe: it would either stop and reverse (resulting in a collapse), it would come to a halt (resulting in a static universe), or it would reach a constant expansion rate. These scenarios assumed the universe only consisted of matter being influenced by gravity and radiation.

The discovery of an accelerating expansion changed this. Type Ia supernovae have a standard brightness, which allows us to determine their distance based on how faint they look in a telescope. We can also measure the redshift of supernovae from spectra, which can be compared to predictions from cosmological models that relate the redshifting of the light to the universe’s expansion rate over time and how far the light has travelled. Thus, we can plot the observed redshifts of the supernovae against their distance (from the measurements of their brightness). This plot is known as a Hubble diagram and can be used to fit a cosmological model. In today’s article, the DES Collaboration has done exactly this to test cosmological models. This time, however, instead of only the 52 supernovae that the discoverers of dark energy had in 1998, there are 1,635 supernovae in the DES five-year dataset — more than 30 times more!

Lighting the Way with the Universe’s Candles

The 1,635 supernovae found and used by DES (after quality cuts) cover redshifts greater than z ~ 0.1, so 194 Type Ia supernovae from samples external to DES are included in the data analysis to cover low redshifts (see Figure 1). In total, this resulted in an analysis of 1,829 supernovae. Part of the cuts to the data involved removing contaminants — transients that look like Type Ia supernovae but might actually be something else. In order to distinguish between the Type Ia supernovae and the contaminants, two machine-learning classifiers were used; they were trained on simulated Type Ia supernova light curves or Type II (core-collapse) supernova light curves (see more about different supernova classification in this bite and Type Ia light curves here).

Hubble diagram of Dark Energy Survey supernovae

Figure 1: The Hubble diagram of the DES supernovae from the five-year sample (blue points) and the external data (orange points) used in the analysis. The lower panel shows the difference from the measured and theoretical distance moduli for the best fit to a time-varying dark energy model. [DES Collaboration 2024]

Supernovae can be classified using spectroscopy, but in the DES analysis the machine learning classifies them using multi-band photometry. This is akin to low-resolution spectroscopy, as the flux from the supernovae is measured in a few different filters, instead of many different wavelengths. This approach allowed DES to observe many more supernovae than before in their survey. The classifiers gave the supernovae a probability of being a Type Ia, as shown in Figure 1 above, and these probabilities were used as weights in the model fitting analysis. To remove human bias in the analysis, the pipelines used were tested on blinded data — that is, the data were made to look different deliberately. This allows for one to ensure the pipeline works well and that those completing the analysis do not introduce bias towards an expected result.

Hints of Time-Varying Dark Energy?

In the standard model of cosmology, ΛCDM, dark energy is assumed to have a constant energy density — i.e., a cosmological constant. This model has been favoured by DES data previously. Furthermore, the results from measurements of the cosmic microwave background by the Planck space mission have preferred this model, and a ΛCDM model with zero curvature — that is to say, the universe has a flat geometry meaning that two parallel beams of light will stay parallel as they propagate through spacetime. If the universe has a curved geometry, the beams can eventually diverge or cross over (see more description here). However, the DES collaboration tests the data with various models: standard ΛCDM, a “flat” ΛCDM (zero curvature is assumed), and two time-varying dark energy models (also with the flat assumption).

The tests on the DES data alone and with combinations of external data for standard ΛCDM and flat ΛCDM find results consistent with those found previously for the matter density of the universe and the curvature — the fitted values are equal to those found previously by Planck within ~95% confidence bounds.

However, the story changes slightly for the time-varying dark energy models. In the first, wCDM allows dark energy to vary over time, letting the equation-of-state parameter, w, vary as a free parameter instead of being fixed to w = −1. In the second model, w0waCDM, the equation of state is modelled with a redshift dependence. One should find in the first model that w = −1, or in the second model that w0 = −1 and wa = −1, to be consistent with a cosmological constant dark energy. These constraints are not exactly favoured by the DES data and combinations, as shown by Figure 2 below.

contours and likelihoods for modeled parameters

Figure 2: Contours (best fit-regions in the parameter space) and likelihoods (conditional probability distributions for the fits to the parameters) for the fits to the matter density, Ωm, and dark energy equation of state parameters, for the w0waCDM model. The different coloured contours and likelihoods represent the different data combinations indicated by the legend. [DES Collaboration 2024]

There is a marginal preference for a time-varying equation of state as shown by the results above — the data prefer this over a model with a cosmological constant with ~95% confidence — just over 2σ. The best fits from the combination of Planck, DES and eBOSS find w = −0.773 (+0.075/−0.067) and wa = −0.83 (+0.033/−0.042) for the w0waCDM. The best fit for wCDM is w = −0.941 ± 0.026.

While we can’t confidently state from these results that dark energy must be time varying, these results here could be a hint at new physics to be discovered by cosmology in the future — but only further analysis and data can tell.

Original astrobite edited by Kylee Carden.

About the author, Abbé Whitford:

I am a third-year PhD student at the University of Queensland, studying large-scale structure cosmology with galaxy clustering and peculiar velocities, and using large-scale structure to measure the properties of neutrinos.

Infrared images of the exoplanet HIP 65426 b from JWST

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: HIP 65426 Is a High-Frequency Delta Scuti Pulsator in Plausible Spin–Orbit Alignment with Its Directly Imaged Exoplanet
Authors: Aldo G. Sepulveda et al.
First Author’s Institution: University of Hawaiʻi at Mānoa
Status: Published in AJ

What Is HIP 65426?

HIP 65426 is a star relatively close to Earth, and it has a giant planet called HIP 65426b orbiting around it that has been directly imaged. You might recall HIP 65426b from a JWST early science release, as it was the first exoplanet directly imaged by JWST.

The star itself is part of a group of young stars called the Lower Centaurus–Crux (LCC) moving group, which is around 10–23 million years old, but scientists estimate HIP 65426 to be around 14 million years old using different methods. This star rotates very quickly and shows signs of potential pulsations in its brightness. Confirming these pulsations, known as δ Scuti pulsations, could help determine the star’s age more precisely. Determining ages of stars is actually surprisingly difficult, so any method that can accurately predict ages is very intriguing to astronomers.

Now switching gears briefly, planet HIP 65426b is located relatively far from the star, between 62 and 120 times the distance between Earth and the Sun. Its orbit is tilted at a significant angle relative to our line of sight. This is particularly interesting because the alignment between a star and its orbiting companions, like planets or brown dwarfs, can tell us more about how these systems formed and evolved.

A recent work revealed that misalignments are common with brown dwarfs, but the orbits of giant planets tended to be aligned or nearly aligned with the spins of their host stars. Understanding whether planets like HIP 65426b are aligned with their stars helps us understand planet formation and the history of these systems.

Observing with and Using Data from TESS

Time-series photometry from the Transiting Exoplanet Survey Satellite (TESS) has provided a lot of data about the rotation of stars and any variations in brightness caused by features on their surfaces or by orbiting objects passing in front of them. Time-series photometry also probes for other phenomena, including stellar pulsations and transit events. In this article, the authors use this data, along with some data from direct imaging of the HIP 65426 system, to investigate the orbital inclination of the exoplanet HIP 65426b. They aim to determine whether there is evidence for misalignment between the planet and its host star.

The star was observed by TESS in three different time periods called sectors (Figure 1). These sectors spanned from April 2019 to May 2019, April 2021 to May 2021, and April 2023 to May 2023. Data was collected from the star every 2 minutes during these time periods. The data was analyzed using a software called lightkurve, which helps process and analyze the light curves of stars. To ensure the data are clean and free from contamination, the authors first removed any unusual or outlier data points from the light curves. Then, they examined a region around the star within a radius of 80 arcseconds to see if any nearby objects were affecting the measurements. This is important because contamination from other sources can affect the accuracy of the analysis.

TESS time-series photometry of HIP 65426

Figure 1: TESS time-series photometry of HIP 65426 for Sectors (a) 11, (b) 38, and (c) 64. [Adapted from Sepulveda et al. 2024]

Identification of the δ Scuti pulsations for Mass and Age Estimations

Several pulsation modes, spanning 28–131 cycles per day, were identified in the star. This is consistent with a high-frequency Scuti pulsator. The presence of these high-frequency Scuti pulsations confirms the young age of HIP 65426 and may even provide an opportunity to estimate its age through detailed asteroseismic modeling, which is beyond the scope of the article.

The authors also investigated the possibility of pulsation timing variations caused by mutual gravitation with an orbital companion. This is typically measurable only for sufficiently massive planets with long enough periods. No such variations were detected, which places an upper limit of 12.8 Jupiter masses on the mass of HIP 65426b.

Stellar Inclination of the Host Star

Using a known relation between the star’s rotation period, its radius, and a measure of its rotational velocity, one can constrain the angle between the star’s rotational axis and our line of sight, also known as stellar inclination. This article uses a Bayesian framework that properly computes the inclination using these parameters. Based on their analysis using values of these parameters from literature (radius from isochrones and rotational velocity from spectroscopy) and TESS measurements (rotation period), the authors place statistical limits on the inclination difference between the star and the planet, the median value being 105 (+7/-9) degrees.

plot of sky-projected orbits for HIP 65426 b

Figure 2: A sample of 100 sky-projected orbits used for fitting the orbit of HIP 65426b. The cyan star represents the position of HIP 65426 and the orange dots represent the relative astrometry of HIP 65426b. [Adapted from Sepulveda et al. 2024]

Orbital Inclination of the Giant Planet

The orbit of the planet was measured out using astrometric measurements from various sources, including high-precision measurements from VLTI/GRAVITY.  From MCMC fitting of Keplerian orbits using the Python package orbitize, the median orbital inclination is estimated to be 108 (+6/-3) degrees, consistent with recent studies of the system although different input measurements were used in this work. Orbits drawn from the fitting process are shown in Figure 2.

Is There a Misalignment?

Figure 3 says no! Here the authors compared the inclination of HIP 65426b with the inclination of its host star. As the plot shows, the stellar and planetary orbital inclinations line up within their uncertainties, and hence there’s a lack of evidence for a misalignment, just a small star–planet obliquity as suggested by the roughly 3-degree difference in inclination.

plot of normalized probability density as a function of inclination angle

Figure 3: The normalized orbital and stellar inclination posteriors for the HIP 65426 system. The purple histogram corresponds to the orbital inclination of the planet and the gray plot represents the stellar inclination of the host star. [Sepulveda et al. 2024]

This seems to be in line with the general trend of alignment where directly imaged long-period giant planets appear aligned with their host stars, as shown by the plot in Figure 4, where the orbital and host-star inclinations for six directly imaged exoplanet systems are being compared. This type of perfect alignment also extends to debris disks, which are analogous to our solar system’s Kuiper Belt.

plot of host star inclination versus orbital inclination

Figure 4: Comparison of orbital inclinations and host-star inclinations for six directly imaged exoplanet systems comprising 11 total companions. [Sepulveda et al. 2024]

If the observed trend of relatively aligned orbits between stars and their imaged giant planets continues, it goes against recent understanding from a 2023 work that suggests misalignments are common in brown-dwarf systems. These differences between giant planets and brown dwarfs could extend to other key characteristics, like their orbital shapes, which might indicate that they form through different processes.

Now, What Can We Tell About the Formation of HIP 65426b?

There are two key models that explain how planets could form: core accretion and disk instability. Core accretion does not really explain how this planet is born because it is farther away from the host star than the region where core accretion would take place. The lack of evidence for misalignment also disfavors the core-accretion scenario. Given the large orbital eccentricity, planet–planet scattering could be a possible mechanism. This scenario suggests that the planet formed closer to its star via core accretion and was then scattered to its current position by the gravitational interactions with other planets in the system. However, planet–planet scattering typically results in orbits being tilted relative to each other, which isn’t the case here, so the lack of significant misalignment between the HIP 65426b’s orbit and its star’s rotation axis doesn’t strongly support this idea.

It is important to note that these theories are not conclusive. The current data don’t provide complete information about the system’s geometry, so it’s still possible that the star’s actual tilt might be larger than what’s currently estimated. Additionally, the orbital eccentricity is not yet concretely determined, so further astrometric measurements can change our current geometric understanding of the system.

The Big Picture

This article describes yet another work that combined space-based brightness data and direct imaging data to understand other planetary systems well after they have formed and understand the implications of their obliquity. With new missions and exoplanet surveys, new systems will be discovered that will also usher in more similar studies of inclinations and orbital architecture.

Original astrobite edited by Amaya Sinha.

About the author, Maria Vincent:

Maria is a PhD candidate in astronomy at the Institute for Astronomy, University of Hawai’i at Manoa. Her research focuses on adaptive optics and high-contrast imaging science and instrumentation with ground-based telescopes. Driven by a fascination with planet formation and the intricate processes shaping our solar system, she uses the Subaru Coronagraphic Extreme Adaptive Optics suite to observe and study morphological features of protoplanetary disks in near-infrared wavelengths, aiming to understand disk structure and processes governing planet formation. On the instrumentation side, she is working on designing and constructing an optical testbed to test and characterize a new deformable mirror as part of the upcoming High-order Advanced Keck Adaptive Optics upgrade. Outside of work, she enjoys blogging, mystery, historical and science fiction literature and cinemedia, photography, hiking, and travel.

star-forming molecular gas

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: Blowing Star Formation Away in AGN Hosts (BAH) – I. First Observation of Warm Molecular Outflows with JWST MIRI
Authors: J.H. Costa-Souza et al.
First Author’s Institution: Federal University of Santa Maria
Status: Published in ApJ

One of the key questions in galaxy evolution is why big galaxies are so rare. We see lots of medium-sized galaxies (galaxies about the size of our Milky Way, with about 100 billion stars) but very few truly enormous ones (five or ten times bigger). We believe the answer to this question is feedback. As galaxies get bigger, physical processes occur that shut down further star formation. In the case of big galaxies, the most likely sources of feedback are active galactic nuclei: the supermassive black holes at the centers of galaxies. These objects can produce a truly astonishing amount of energy, and if some of that energy can act on the gas in the galaxy that is trying to form new stars (heating it up, moving it around, or expelling it from the galaxy entirely), it could interrupt star formation enough to explain why we don’t see many big galaxies.

In order to tell if this is happening, we need to study this star-forming gas. Stars are mainly formed from molecular hydrogen gas (H2). This gas comes in different phases: a cold (less than 100K) phase, a warm (100 to 1000K) phase, and a rare hot (more than 1000K) phase. It’s also not just enough to see that the gas is there — we need to see how it’s moving, in all three dimensions, because active galactic nucleus feedback can manifest itself as a large-scale outflow of gas. This is possible with specially designed instruments known as integral field units, which measure a full spectrum of light in each spatial pixel of an image. Provided the gas we’re trying to study emits some sort of spectral line, the integral field unit can measure its velocity towards or away from us using the Doppler shift. This type of analysis is known as galaxy kinematics.

In today’s article, the authors target specifically the warm phase of molecular gas, which thankfully emits a whole series of spectral lines. These lines are mostly rotational lines of the H2 molecule, and they emit in the mid-infrared, which is perfect for targeting with the Mid-Infrared Instrument (MIRI), an integral field unit on JWST. The authors are looking at one specific active galactic nucleus host: UGC 8782. The active galactic nucleus in this galaxy is a low-ionization nuclear emission region, or LINER (astrobites has a full guide on active galactic nucleus classification here), and it’s only about 200 megaparsecs (650 million light-years) away, which, by galaxy standards, is very close. From other optical and radio imaging, the authors figured that UGC 8782 had outflows in at least some phases of gas, which made it likely that it would have a warm molecular gas outflow as well.

What the authors found from their JWST observations was pretty much exactly what they expected: a large-scale outflow in the warm molecular gas of the galaxy. Figure 1 breaks down the emission into components that come from the main disk of the galaxy (which is behaving pretty normally — just doing regular rotation) and components that come from a large-scale outflow from the center of the galaxy. This is mostly apparent in the bulk velocity of the gas (the bottom-center panel), where there are negative velocities where the normal disk rotation has positive velocities, and in the velocity dispersion (the bottom-right panel), which is more than double the typical dispersion of the galaxy in the region where the outflow is occurring. This means that this gas has a lot more energy than the rest of the gas in the galaxy, another sign that it’s interacting with the active galactic nucleus. Not shown is a second outflow that is faster but smaller.

plots showing the gas kinematics of the galaxy UGC 8782

Figure 1: The kinematics of the warm molecular gas in UGC 8782. The gas is broken down into a disk component (top), tracing the regular rotation of the host galaxy, and an outflow component (bottom) of gas being pushed out of the center of the galaxy by the active galactic nucleus. The flux distribution (left), gas velocity (center), and velocity dispersion, or scatter in the velocity (right) are shown for each component. [Adapted from Costa-Souza et al. 2024]

This is great information — it’s good to know that these outflows are happening in the warm molecular gas phase! However, that’s not all that can be found from the H2 data from MIRI. The authors detect several different rotational H2 lines, which means that the different lines can be compared to determine the temperature of the gas and to get a more accurate measurement of the mass of the gas. This information can then be combined to measure how fast the active galactic nucleus is pushing mass out of the center of the galaxy (the “mass outflow rate”) and how much energy that requires (the “kinetic power”). The authors do this calculation for gas at different distances away from the active galactic nucleus. The results are shown in Figure 2.

plots of mass outflow rate and energy required to expel that amount of mass

Figure 2: The rate at which mass is being pushed out of the center of the galaxy by the active galactic nucleus (top) and the energy required to push that mass out (bottom), as a function of distance from the active galactic nucleus. Three phases of gas are shown: the warm molecular gas being studied in this article (light blue), the hotter molecular gas (orange), and the ionized gas (dark blue). [Costa-Souza et al. 2024]

What the authors find is that the warm molecular gas is dominating the outflow both in terms of its mass outflow rate and its kinetic power. It’s so strong, it could push all the warm molecular gas available in the center of UGC 8782 away in only about a million years. Between 2% and 5% of the energy the active galactic nucleus is outputting as light has to go into the molecular gas to create an outflow this powerful.

An outflow this strong and powerful is fantastic evidence for feedback from an active galactic nucleus acting strongly on the star-forming gas in a galaxy, which means we’re one step closer to understanding the mystery of giant galaxies in the universe — it could be active galactic nucleus feedback causing them not to get made! Still, this is only one galaxy. We’ll have to study many others in the future to see how common this is, but JWST’s MIRI is more than up to the task.

Original astrobite edited by Storm Colloms.

About the author, Delaney Dunne:

I’m a PhD student at Caltech, where I study how galaxies form and evolve by mapping their molecular gas! I do this using COMAP, a radio-frequency line-intensity mapping experiment based in California’s Owens Valley.

two simple line drawings of the sun with sunspots

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: Analyses of Johannes Kepler’s Sunspot Drawings in 1607: A Revised Scenario for the Solar Cycles in the Early 17th Century
Authors: Hisashi Hayakawa et al.
First Author’s Institution: Nagoya University
Status: Published in ApJL

Solar Cycles and the Maunder Minimum

A typical solar cycle lasts around 11 years. Each cycle begins with a solar minimum, characterized by quiet solar activity and few visible sunspots. Around the middle of the cycle, the Sun’s magnetic field flips, causing a solar maximum — a spike in magnetic activity that manifests on the Sun’s surface as an increased number of sunspots and solar flares. Then the magnetic fields settle, ending the cycle with another solar minimum, and the cycle repeats. In general, sunspots appear at high absolute latitudes during the solar maximum and drift towards the Sun’s equator as the cycle winds down, making the latitude of these sunspots an approximate indicator of how far a solar cycle has progressed (see Figure 1).

Schematic of sunspot latitude and frequency during a solar maximum and a solar minimum

Figure 1: Schematic of sunspot latitude and frequency during a solar maximum and a solar minimum. [Annelia Anderson]

However, solar cycles are not always perfectly regular; we have around 400 years of telescopic sunspot observations, during which there have been several irregular periods. Most significantly, during the Maunder Minimum from 1645 to 1715, sunspots all but disappeared. Understanding and predicting solar cycles and such grand minima remains an open problem in astronomy. In the case of the Maunder Minimum, there is an ongoing debate around how and when solar cycles transitioned from regular cycles to a prolonged grand minimum, and specifically whether or not cycle durations changed.

Besides telescopic observations, past solar activity can be estimated from the amount of carbon-14 in tree rings. Some of the carbon-14 in Earth’s atmosphere is created by cosmic rays interacting with atmospheric nitrogen. When the Sun is especially active, its enhanced magnetic field shields Earth from cosmic rays, which results in less carbon-14 in the atmosphere for trees to absorb. Results can be hard to interpret, though, because other factors like weather have a greater effect on carbon-14 production than solar activity does. Some carbon-14 solar cycle reconstructions have suggested extremely short solar cycles before the Maunder Minimum, while others have found solar cycles with regular to slightly long durations.

Understanding the onset of the Maunder Minimum is further complicated by the fact that telescopic sunspot observations only began in 1610 (just after the invention of telescopes). Observations began sometime during Solar Cycle −13, making it difficult to determine exactly when the cycle began — and therefore, difficult to determine whether the duration of Solar Cycle −13 was anomalous. Luckily for the authors of today’s article, a bit of data exists from the time before telescopes — drawings made by Johannes Kepler, the highly influential German astronomer best known for his laws of planetary motion, as he observed sunspots via camera obscura.

Kepler’s 1607 Sunspot Drawings

On 28 May 1607, Kepler made two sunspot drawings and recorded his activities and observations throughout the day. According to his book Phaenomenon singulare seu Mercurius in Sole (Kepler originally interpreted these sunspots as a transit of Mercury), his afternoon went like this:

Around 4:00 PM, Kepler noticed the clouds were clearing. There was a sunspot group large enough to be seen by the naked eye, so he headed home to observe the Sun. His house was on the bank of the Vltava River in Prague, and inside he had converted a room into a camera obscura — by only allowing the Sun’s light to enter through a pinhole, he was able to project an image of the Sun onto a sheet of paper. He traced this image and the large visible sunspot group. Next, he headed to the workshop of his friend Jost Bürgi, a Swiss clockmaker and mathematician. On his way there, he passed the Old City Hall, which had an astronomical clock that measured time since the previous sunset. The clock read 21 ⅓ hours. Once in Bürgi’s workshop, Kepler repeated his camera obscura observation, traced the Sun again, and noted that the Sun was setting when he finished. See Figure 2 for a depiction of his observations.

two drawings of the Sun and sunspots

Figure 2: Kepler’s 28 May 1607 sunspot drawings. Left: Observation at Kepler’s house. Right: Observation at Bürgi’s workshop. [Adapted from Hayakawa et al. 2024]

Diagram of a camera obscura

Figure 3: Diagram of a camera obscura. As the light travels through the pinhole, the projected image is inverted. [Fizyka z 1910 via Wikimedia Commons; Public Domain]

From Kepler’s account the authors were able to piece together that the observation times were around 5:30 PM at his house and 7:40 PM at Bürgi’s workshop. Next was the problem of orientation. Kepler oriented his drawings to match the Sun as it appeared in the sky, except they were upside down as a result of the camera obscura pinhole projection (see Figure 3). Finally, to overlay heliographic coordinates on the drawings, the authors aligned the vertical axes of the drawings toward the local zenith and ground in Prague at the time of the observations, as is shown in Figure 4.

Kepler’s sunspot drawings overlaid with heliographic coordinates

Figure 4: Kepler’s sunspot drawings overlaid with heliographic coordinates after reorientation. The Sun’s equator is the line that passes through the midpoint of each circle. Left: Observation at Kepler’s house. Right: Observation at Bürgi’s workshop. [Hayakawa et al. 2024]

In both drawings, the large sunspot group appears near or on the Sun’s equator. The small difference in sunspot location between the drawings isn’t surprising due to a number of possible errors — either in the rudimentary observation technique (although Kepler was meticulous) or the large uncertainties from interpreting the times of observations. In either case, the drawings are qualitatively similar and point to one important conclusion — the sunspot group is near the equator, so Kepler was observing the end of a solar cycle in 1607.

Regular Solar Cycle Durations

Because many sunspots were visible at high latitudes in the years following 1610, the authors were able to place the beginning of Solar Cycle −13 (and end of Solar Cycle −14) somewhere between 1607 and 1610. Solar Cycle −13 ended around 1620, meaning it had a regular duration of 11–14 years. As an end date for Solar Cycle −14, these results also agree with carbon-14 solar cycle models in which Solar Cycle −14 lasts around 14 years.

In recent years, the Sun’s activity appeared to be decreasing and discussion arose around the possibility that we could be approaching another Maunder-like event. Though not a cause for concern, the possibility highlights the importance of studying and predicting changes in the Sun’s activity. Using Kepler’s pre-telescope drawings to show that previously contentious solar cycle durations were typical before the Maunder Minimum adds another piece to this unsolved puzzle.

Original astrobite edited by Caroline von Raesfeld.

About the author, Annelia Anderson:

I’m an astrophysics PhD student at the University of Alabama, using simulations to study the circumgalactic medium. Beyond research, I’m interested in historical astronomy and hope to someday write astronomy children’s books. Beyond astronomy, I enjoy making music, cooking, and my cat.

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