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TESS

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 HOT SATURN ORBITING AN OSCILLATING LATE SUBGIANT DISCOVERED BY TESS
Author: Daniel Huber, William J Chaplin et al.
First Author’s Institution: Institute for Astronomy, University of Hawai’i
Status: Submitted to AAS Journals

NASA’s space mission TESS is currently hunting for new exoplanets in the southern hemisphere sky. But while its primary aim is to find 50 small (radii less than 4 Earth radii) planets with measurable mass, there is a lot of other interesting science to do. Today’s paper presents the discovery of a new exoplanet that is quite precisely characterised thanks to the complementary technique of asteroseismology used on the same data.

Meet TESS

TESS will survey stars over the entire sky, studying 26 strips for 27 days each. Data for selected bright stars is downloaded to provide data points every 2 minutes (i.e., a 2-minute cadence) and then processed through a pipeline to produce light curves. Another pipeline detects transit-like signals in these lightcurves — and it recently identified TOI-197.01 as a planet candidate (see Figure 1a). 

Is It an Exoplanet?

The authors used high-resolution imaging by the NIRC2 camera on the Keck telescope to rule out companion stars that could produce a similar light curve. An intense spectral monitoring campaign of 111 spectra from 5 different instruments in a seven-week period let them search for periodic Doppler shifts in the stellar spectrum caused by the mass of another object tugging on the star. The mass they calculated from these radial velocities (seen in Figure 3) confirmed that TOI-197.01 is an exoplanet.

Stellar Pulsations

Photometry from space is not only useful for finding exoplanets: Kepler could detect the periodic changes in stellar brightness caused by stellar pulsations or ‘star quakes’. Asteroseismology, the study of these pulsations, allows astronomers to investigate the inner structure of bright stars and calculate their key properties, including radius and mean density, very precisely. Astronomers expected they could also study stellar pulsations using TESS data.

After removing the transit signal from the TESS light curves (giving Figure 1b), the light curve is Fourier transformed from time (days) into frequency (µHz), giving the power spectrum seen in Figure 1c. Modeling the stellar pulsations along with the stellar granulation and white noise (see Figure 1c), the authors then ‘smoothed’ the power spectrum to identify the location of the tallest peak, i.e. the frequency of maximum power at 430 µHz, and its height, or power.  

TESS lightcurve of TOI-197

Figure 1: The TESS lightcurve of TOI-197. a) Raw TESS lightcurve showing two transits marked by grey triangles. b) Corrected TESS lightcurve with transits and instrumental effects removed. c) Power spectrum of the corrected lightcurve, where dashed red lines show the granulation and white noise. The solid red line is a fit to these as well as the stellar pulsations. [Huber et al. 2019]

The authors converted the ‘maximum’ power into amplitude and plotted this against the frequency of maximum power. By comparison against 1,500 stars from the Kepler mission they confirmed it had solar-like oscillations. Another important value is the large frequency separation, found by identifying the difference in frequency between the radial mode peaks. These are marked blue in Figure 2 and have a value of 29.84 µHz.

Power spectrum of TOI-197.01

Figure 2: a) Power spectrum of TOI-197.01 in the region of frequency space showing oscillations. Vertical lines mark identified individual frequencies, with blue showing the radial modes. b) Blue circles represent the radial modes that line up vertically when the difference between them is 28.94 µHz, illustrating the large frequency separation. Figure repeats in the x axis about 0. [Huber et al. 2019]

Modeling Stellar Properties

The authors then used stellar-evolution and oscillation codes to model the stellar properties. The luminosities for the model were calculated by combining the Gaia parallax with photometry from many different catalogues. They also input properties they modeled from the spectra — temperature, surface gravity (log g), and metallicity — and combined them with the individual frequencies and large frequency separation from asteroseismology. This resulted in two preferred models: i) a lower mass, older star (1.15 solar masses, ~6 Gyr old) or ii) a higher mass, younger star (1.3 solar masses, ~ 4 Gyr old). An independent constraint on surface gravity from an autocorrelation analysis of the light curve favours a higher mass model. Thanks to asteroseismology, the final estimates of stellar parameters have small uncertainties: radius (2%), mass (6%), mean density (1%), and age (22%).

Characterising the Planet

TOI-197 light curve

Figure 3: Data for TOI-197 folded on the best period of 14.3 days. Top: the TESS lightcurve. Bottom: radial velocity curve. [Huber et al. 2019]

Using the mean stellar density from asteroseismology, the authors jointly fit the photometric and radial-velocity data to obtain the planet properties, including period, radius, and mass. Figure 3 shows both sets of data folded on the best period of 14.3 days. The mass ratio is calculated from the maximum amplitude of the radial-velocity data. Combining this with the modeled stellar mass gives a minimum planet mass 35% lighter than Saturn. The transit depth gives the radius ratio, which combined with the modeled star radius means TOI-197.01 has the same radius as Saturn.

A Hot Saturn and a Bright Future!

The result is TOI-197.01 is a hot Saturn orbiting a late subgiant/early red giant star. The combination of spectra and the large frequency separation from asteroseismology shows the star has just started ascending the red giant branch. TOI-197.01 represents the starting point before gas giants reinflate due to the strong flux from their evolved stars. TOI-197.01 is significant as the first transiting planet orbiting a late subgiant/early red giant with detected oscillations measured by TESS, and only the 6th ever discovered (with the others found by Kepler). Indeed, fewer than 15 transiting planets are known around red giants in total.

This is an exciting result as it shows that even with only 27 days of data, TESS should allow us to study the oscillations of thousands of bright stars in the 2-minute cadence data. TOI-197.01 is also one of the most precisely characterised Saturn-sized planets, with density constrained to 15%, demonstrating what we can gain when we can ‘listen’ to exoplanet host stars.

About the author, Emma Foxell:

I am a PhD student at the University of Warwick. My project involves searching for transiting exoplanets around bright stars using telescopes on the ground. Outside of astronomy, I enjoy rock climbing and hiking.

Lucy

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: Light Curves of Lucy Targets: Leucus and Polymele
Author: Marc W. Buie, Amanda M. Zangari, Simone Marchi, Harold F. Levison, Stefano Mottola
First Author’s Institution: Southwest Research Institute
Status: Published in AJ

Asteroids, meteoroids, meteors, meteorites. Usually when we talk about these small chunks of debris and rock in the solar system, it’s about another possible apocalypse scenario. Studies of rocky objects that may pass near Earth’s orbit (near-Earth objects, or NEOs) are of obvious importance for the safety of humanity, but they are only one minor subset of the small bodies in our solar system. Most of the asteroids in our neighborhood live in the Asteroid Belt, a region between the orbits of Mars and Jupiter, and they’re referred to as “main-belt asteroids”. There are also large populations trailing Jupiter in its orbit (the Trojan asteroids) and floating out in the outer solar system near Neptune (the Centaur asteroids).

But apart from the potential threat posed by NEOs, why study these plentiful, seemingly uninteresting hunks of rock and metal that we will likely never encounter on Earth? It turns out that they actually serve as an important window into the formation of the solar system, providing us with information on how the planets formed and what our early solar system was made of. Since we have the chance to get up close and personal with the planets and asteroids nearest to us with rovers and other probes, scientists use this information to infer how other planetary systems form as well. In recent history, we’ve visited most of the major planets with satellites, such as Voyager or Cassini, or rovers, such as Curiosity on Mars; however, the smaller debris is still largely unexplored. The New Horizons mission provided a glimpse into icy debris in the outer solar system when it imaged Pluto and a Kuiper-Belt object (2014 MU69) in detail for the first time, and both NASA’s OSIRIS-REx and JAXA’s Hayabusa missions are working on returning samples from near-Earth asteroids.

A new asteroid mission has begun preparation as well, targeting multiple asteroids in the further-out Trojan group near Jupiter. The Lucy Discovery mission plans to visit multiple Trojans (actually, the largest number of independently orbiting objects ever visited by a single probe), including Leucus and Polymele, whose flybys are scheduled for September 2027 and April 2028 respectively. Until that date, though, astronomers are busy preparing for the mission and trying to gather all the data on these objects that we can from Earth. The authors specifically investigate Leucus and Polymele, using their light curves to tease out information about their color, composition, orbit, and reflectivity.

Lucy's orbital path

Figure 1: Lucy’s planned orbital path, illustrating the location of the Trojans in Jupiter’s orbit. [SwRI]

A light curve traces the variation in the light we receive from an object over time, and for asteroids, we’re mostly seeing light reflected from the Sun. One of the key parameters, then, is how reflective the asteroid’s surface is – its albedo. Tracing the variations in intensity and finding periodic patterns can also determine the rotation period of an asteroid; imperfections in the surface and any non-spherical shape can lead to bumps and wiggles in the light curve, and by tracking how long it takes to see the same imperfection again, we find how long the asteroid takes to rotate around its own axis. By collecting light in different wavelengths, astronomers can also derive colors, comparisons of how much light we get at one wavelength versus another.

For Leucus and Polymele, this research group used telescopes in the Las Cumbres Global Telescope Network (LCOGT), specifically two telescopes at Cerro Tololo in Chile and one at MacDonald Observatory in the United States. These images were taken in the red part of the spectrum of visible light, since asteroids tend to be brighter at longer wavelengths. After taking multiple data images over time, the results of the brightness of the asteroid vs. time are plotted into a light curve, as shown in Figure 2.

Leucus light curve

Figure 2: A light curve for Leucus, clearly showing its variability. [Buie et al. 2018]

Through their observations of Leucus, the team determined that it has a very long rotation period, and it may actually be a binary system. Future observations from the ground will be needed to determine if it is or not. If it is a binary, this can provide scientists with even more information about when it formed; in the early solar system, when more debris was flying around, it would have been easier to form a binary than it is now. From its colors, Leucus is also determined to be a “primitive” asteroid; this type of asteroid is very dark (even darker than coal!), and may be relevant to the question of how life began on Earth because they are thought to carry organic, carbon-rich material. Unfortunately, this paper reports that Polymele is still not well-understood — likely because it is so small and might be nearly spherical, providing very little variation in its light curve. It’s also extremely dark, though not as dark as Leucus.

Although these may seem like small steps at first — determining characteristics of one or two rocks in the vast solar system — they are actually stepping stones (literally!) to understanding the population of asteroids that surrounds us. Asteroids may be what brought life to Earth, and they are intact remnants of the story of planet formation. The key to a successful space mission is minimizing risk, and a large component of that is knowing what you’re getting into when you’re millions of miles away in space; studying these asteroids will prevent the spacecraft from encountering physical hazards (like collisions), and will inform what data we need to take in-situ to better understand them. By studying the future targets of the Lucy mission now, the lander, and the humans running the mission, will be prepared for its eventual encounter with them.

About the author, Briley Lewis:

Briley Lewis is a first-year graduate student and NSF Fellow at the University of California, Los Angeles studying Astronomy & Astrophysics. Her research interests are primarily in planetary systems — both exoplanets and objects in our own solar system, how they form, and how we can create instruments to learn more about them. She has previously pursued her research at the American Museum of Natural History in NYC, and also at Space Telescope Science Institute in Baltimore, MD. Outside of research, she is passionate about teaching and public outreach, and spends her free time bringing together her love of science with her loves of crafting and writing.

Fornax dwarf

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

Title: The Binary Fraction of Stars in Dwarf Galaxies: the Cases of Draco and Ursa Minor
Author: Meghin Spencer et al.
First Author’s Institution: University of Michigan, Ann Arbor
Status: Published in AJ

Disclaimer: My advisor is an author on this paper, but somehow I didn’t realize that until after I’d finished writing the entire post. Hopefully you’ll forgive my compromised journalistic integrity! –Mia de los Reyes

Introduction

Stars aren’t usually only children. In fact, we think most stars are born in binary or multiple systems. But just how many binary systems are out there?

Understanding the fraction of binary stars is important in studying galaxies. For example, the number of binaries can affect some estimates of global galaxy parameters like star formation rates, which depend heavily on models of stellar populations. Binary stars can also lead to events like Type Ia supernovae (the thermonuclear explosions of some white dwarf stars with binary companions), so knowing the fraction of binary stars can help us figure out the rates of these events.

Segue 1

Two views of the ultra-faint dwarf galaxy Segue 1, a close neighbor and satellite of the Milky Way. Click to enlarge. [Sloan Digital Sky Survey (left) and M. Geha (right)]

Binary stars might be even more important in the smallest and faintest of galaxies, called ultra-faint dwarf galaxies (UFDs). UFDs are strange systems. They seem to be hybrids between globular clusters and dwarf galaxies, but they’re mostly classified as “galaxies” instead of stellar clusters. This classification is, in part, because UFDs (like other galaxies) appear to be dominated by dark matter based on observations of the velocities of their stars.

How does this work? The velocity dispersion (a measure of how much the stars’ velocities differ from the average motion of the galaxy) is high for a UFD. This suggests that there’s a lot of mass in the galaxy, making the stars orbit quickly around the galaxy’s center of mass. The velocity dispersions are even high enough to imply that there’s more matter in UFDs than just the visible matter: hence, dark matter! This could make UFDs promising targets to probe the physics of dark matter.

But binary stars could mess this all up. As the stars in binaries move around their companions, they can increase the velocity dispersion of a galaxy and make it seem like the galaxy has more mass than it really does. If UFDs have high fractions of binary stars, they might not have as much dark matter as we think!

Today’s Paper: Methods

To see if UFDs actually have lots of dark matter, we want to know if UFDs have lots of binaries. Unfortunately, there aren’t many measurements of the velocities of stars in UFDs. So today’s paper does the next best thing: the authors study the cousins of UFDs, called dwarf spheroidal (dSph) galaxies. These galaxies aren’t quite as puny as the ultra-faint dwarf galaxies, but they still have low masses compared to big systems like our Milky Way.

Lots of stellar velocities have been measured in dSph galaxies at different times, and Spencer et al. take advantage of these data. They come up with a model for the distribution of stellar velocities in a galaxy.  This model takes lots of inputs, including the fraction of binary stars, as well as various parameters that describe binary systems. Using Bayesian techniques, the authors fit the model to the observed velocity distributions of different dSph galaxies. The best-fitting models (shown in Figure 1) then provide estimates of the input parameters, including the fraction of binary stars in each galaxy.

Figure 1. The distribution of changes in velocity (β) for seven different dSph galaxies (different panels). Black line marks the observed distribution and blue shaded region is the best-fit model. For comparison, the red shaded region is a model without binary stars. Most of the seven galaxies appear to have a nonzero fraction of binary stars. [Spencer et al. 2018]

Today’s Paper: Results

The best-fit models give lots of information about the binaries in each dwarf galaxy, which the authors describe and compare to previous literature. For simplicity, we’ll just focus on the binary fraction.

Spencer et al. present the first measurements of the binary fractions of the Draco and Ursa Major dSphs, and they check that their binary fraction measurements for five other dSphs agree with literature values. They then compare the binary fractions for all seven dSphs, and they find that the chances of all dSphs having the same binary fraction are incredibly low! This suggests that we can’t just assume a constant binary fraction for all dwarf galaxies.

Next, the authors go a step further to try to figure out what properties in dSphs affect the binary fraction. They find that the dSphs with smaller velocity dispersions seem to have lower binary fractions (Figure 2)! If this trend extends to UFD galaxies (which have low velocity dispersions), this could mean that UFDs don’t have that many binary stars. That’s good news for dark matter lovers — it means that the velocity dispersions of UFDs might not be heavily contaminated by binary stars, so UFDs could indeed have lots of dark matter.

Figure 2. The stellar velocity dispersion σ of 7 dSph galaxies as a function of their binary fractions f. This suggests that dSph galaxies with higher velocity dispersions may have higher fractions of binary stars. The authors made lots of other plots like these, but this parameter had the most convincing correlation with binary fraction. [Spencer et al. 2018]

It’s hard to make any definitive claims based on only seven dSph galaxies, but these potential results open up lots of questions about binary stars. What physical mechanism causes dSphs to have different binary fractions? Do the trends that Spencer et al. presented for dSphs still hold for ultra-faint dwarf galaxies?

As usual, an interesting scientific result leads to more questions than answers.

About the author, Mia de los Reyes:

I’m a grad student at Caltech, where I study the chemical composition of stars in nearby dwarf galaxies. Before coming to sunny California, I spent a year as a postgrad at the University of Cambridge, studying star formation in galaxies. Now that I’ve escaped to warmer climates, my hobbies include rock climbing and finding free food on campus.

SDSS image of MaNGA galaxy

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

Title: Anomalously low metallicity regions in MaNGA star-forming galaxies: Accretion caught in action?
Author: Hsiang-Chih Hwang et al.
First Author’s Institution: Johns Hopkins University
Status: Accepted to AJ

Looking at a galaxy, the first thing we are likely to notice is its stars. All stars — whether they are massive, bright, short-lived blue stars or small, dim, long-lived red stars — form in regions called stellar nurseries, which are pockets of cold, dense molecular gas. Given the correct conditions, this gas will collapse and begin to form stars. Consequently, the abundance of gas within a galaxy can be treated as a measure of its ability to form stars. A problem arises though: given the rate of star formation observed in the nearby universe (0.3–1 solar masses per year), most galaxies should run out of gas quite quickly and, once this fuel is depleted, should stop forming stars completely. Obviously these galaxies are somehow acquiring gas, but it is very difficult to observe accretion, the gravitationally induced collection of gas by a galaxy (or other objects). Thus, there are many remaining questions regarding how galaxies accrete gas and at what rate. The authors of today’s paper examine galaxies for signs of recent gas accretion and examine correlations with galaxy properties and apparent instigators of accretion.

It’s Pronounced MaNGA: Data and Metrics

In this study, the authors start with a specific assumption: That gas observed to have unusually low metallicity, or metal content, is evidence that the galaxy has recently accreted metal-poor gas from some external gas reservoir. But to distinguish the metallicity of the gas from the metallicity of the galaxy itself, the authors need to have spatially resolved observations to work with. To accomplish this, the study utilizes data from the Mapping Nearby Galaxies at Apache Point Observatory (MaNGA) survey, which uses Integral Field Units (IFUs) to observe galaxies in the Sloan Digital Sky Survey (SDSS)-IV (read more about how MaNGA and IFUs work). Generally, an individual IFU obtains the spectrum of a small region within a galaxy and the resultant spectral pixel is called a spaxel. When all spaxels are mapped out (see the right two panels in Figure 1), astronomers can examine varying spectral properties over the surface of an entire galaxy.

Using the information from each spaxel, the authors calculate the expected metallicity for a region based on the measured stellar surface mass density (the number of stars in a specific area), and compare it to the observed metallicity of the same region. They identify gas that deviates more than 0.14 dex from expectations to be anomalously low metallicity (ALM) gas, and investigate how the presence of ALM gas correlates with several global galaxy properties, among them the stellar mass, NUV-r color, and the asymmetry. The NUV-r color describes the difference in brightness between the near ultraviolet (NUV) and red (r) light emitted by the galaxy, and roughly measures whether a galaxy is dominated by recently-formed, blue stars (a low NUV-r value) or old, red stars (a high NUV-r value). This color can also be used to calculate the specific star formation rate (sSFR) which indicates how quickly a galaxy is forming stars. The asymmetry of a galaxy is determined by comparing an image of a galaxy with the same image rotated by 180 degrees. A galaxy that is highly asymmetric is likely to be gravitationally interacting with another nearby galaxy, and therefore appears to be “strongly disturbed” in shape.

Figure 1: Example measurements from a galaxy showing ALM gas. Left: Galaxy in optical light from SDSS. Middle: Maps of Hα brightness, which is an indicator of star formation. Right: Deviation from the anticipated metallicity based on the stellar surface mass density. Dark blue and purple pixels indicate ALM gas. [Hwang et al. 2019]

Deviations from Normal Star-Forming Galaxies

Are galaxies with ALM gas unusual compared to other star forming galaxies? The answer is…yes! The ALM-containing galaxies are bluer in NUV-r color, more asymmetric, and have lower overall stellar masses than the rest of the sample of star-forming MaNGA galaxies. Although each of these results are important, the asymmetry is perhaps the most interesting. While ALM galaxies are more asymmetric on average, the majority of galaxies with ALM gas are not asymmetric. In other words, selecting an asymmetric galaxy will probably find you one with ALM gas, but the opposite will not be true. Nonetheless, this relationship suggests a connection between galaxy asymmetry and recent accretion of ALM gas (Figure 2).

Figure 2: Relationships between the ALM gas in MaNGA galaxies. Left panel: The fraction of galaxies with ALM gas increases as the asymmetry measure increases. Right panel: The fraction of galaxy spaxels with ALM gas (for individual galaxies) increases as asymmetry measure of the galaxy increases. [Hwang et al. 2019]

Since asymmetry is related to galaxy interactions, one may wonder how ALM gas is related to different types of interactions. The authors group the entire sample of star-forming galaxies into three categories: mergers, close-pairs, and isolated galaxies. Of these, mergers are found to be the most likely to contain ALM regions (52%) while close-pairs and isolated galaxies are less likely (30% and 23% respectively). Galaxies in close-pairs also sometimes show an interesting feature: azimuthal asymmetry in the ALM distribution. The tendency of the gas to be aligned with the angle to the companion galaxy may suggest that the ALM material has somehow been introduced into the system by the companion (Figure 3).

Figure 3: Top row: Optical SDSS images of two MaNGA galaxies with a “close-pair” companion. Bottom row: Spatial deviation from the expected metallicity, where dark blue or purple indicates ALM gas. Arrows show the direction to the companion galaxy. [Hwang et al. 2019]

Lifetime of ALM Gas

In addition to the association with companion galaxies, the authors find a clever way to determine how long an ALM region can last within a galaxy. The oxygen-based metallicity measurements will be altered once very massive O-type stars, greater than 8 solar masses, go supernova and begin enriching the surrounding interstellar medium with oxygen they created after leaving the main sequence. Using the short lifetimes (less than 30 million years) of these stars, the authors are able to calculate that an ALM region should be polluted by the stars it forms within a few hundred million years of the onset of star formation. Further, by estimating the mass of ALM material available in each spaxel of the MaNGA images, it is calculated that these star-forming galaxies likely undergo an accretion event roughly once every billion years, accumulating one billion solar masses of ALM gas for every event.  Whether the accreted gas stems from a merger or removal of gas from a satellite galaxy, this averages out to 1 solar mass of gas accumulated every year, which accounts perfectly for the 0.3–1 solar masses per year of star formation rate observed in our local universe. Thus, this study shows that nearby galaxies are accreting a feasible amount of gas and suggests that mergers play an important — but not all-encompassing — role in sustaining star formation in galaxies.

About the author, Caitlin Doughty:

I am a fourth year graduate student at New Mexico State University. I use cosmological simulations to study galaxy evolution during the epoch of reionization, with a focus on metal absorption in the circumgalactic medium.

solar system

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

Title: Col-OSSOS: Color and Inclination are Correlated Throughout the Kuiper Belt
Author: Michaël Marsset, Wesley C. Fraser, et al.
First Author’s Institution: Queen’s University Belfast, UK
Status: Accepted to AJ

The outer reaches of our own solar system remain a mystery. Astronomers are only just beginning to shine (colored) light on the distant region of our solar system called the Kuiper Belt. But this region has a lot to tell us about the history of the solar system — N-body simulations predict the types of objects we should find and what their orbits should look like. Are they locked into an orbital resonance with Neptune? Have they been flung out of the plane of the solar system by a past interaction with another object? Other studies also predict the types of molecules we should see based on where the objects formed and how they have been flung around the solar system.

From Grayscale to Color

Figure 1. Demonstration of spectroscopy vs. broad-band filter imaging. The spectrum (of a galaxy, for this plot) is shown in black, while the filter acceptance by wavelength for the BViz filters are shown in color. The flux from all wavelengths spanned by a filter is added according to that filter’s response to produce the data points in the top panel. [STSci and Dan Coe]

Using spectroscopy to learn about the compositions of Kuiper Belt objects (KBOs) has typically been impossible because these objects are generally so faint (due to their great distances from Earth of 30–40 astronomical units or more). One solution to this problem is to take “broad-band” filter measurements — instead of separating the object’s light into individual wavelengths as in spectroscopy, astronomers take images using filters that select wider ranges of wavelengths (see Figure 1). While this technique sacrifices detailed wavelength information, it increases photon counts, making even faint KBOs measurable. The difference in flux between images in two filters gives a “color.” Unfortunately, many KBO surveys have taken images in only one filter. Thus, many of the ~2,100 currently known KBOs don’t have associated colors. Today’s paper details results from ongoing Col-OSSOS, or the Colors of the Outer Solar System Origins Survey, which uses the Gemini-North telescope in Hawaii to measure the colors of select objects discovered by OSSOS. Today’s authors compiled the largest KBO sample to date with well-measured colors — 229 KBOs in three different filters.

Today’s authors were specifically interested in how an object’s color correlates with its orbital inclination. Since color and orbital properties like inclination can tell us about an object’s dynamical history, considering both together could potentially place stronger constraints on our solar system’s complicated dynamical past than either alone. The authors selected their sample from Col-OSSOS itself and from previous surveys according to a few criteria:

  1. Previous surveys considered must have published their telescope pointing history and taken observations in filters comparable to the Col-OSSOS filters.
  2. Objects must have an orbital inclination greater than 5º, such that they are “dynamically excited.”
  3. Objects must be smaller than ~440 km, to avoid the range of sizes in which KBOs transition from large and ice-rich to small and depleted of ices. The authors were only interested in colors due to rock composition, not in colors due to the presence of ices.
  4. Objects must not belong to known families with distinct compositions/colors (like the icy collisional family of Haumea) or pass too closely to Jupiter.

When all was said and done, the authors had a sample of 229 KBOs whose colors fell into two distinct populations that the authors termed “gray” and “red.” They then examined the orbital inclination distributions of the gray and red KBOs in turn.

Colorful Results

Figure 2. The orbital inclination vs. spectral slope for the 229 gray and red KBOs, where the spectral slope is a measure of how an object’s reflectance changes with wavelength — in other words, it is another measure of color. The blue shading represents the smoothed density of data points. The red KBOs have a significantly lower inclination distribution in general than the gray KBOs. [Marsset et a. 2019]

Marsset et al. find that the inclination distributions of the two color populations are significantly different, as measured by a variety of statistical tests. Specifically, they find that the red population of dynamically excited KBOs have smaller inclinations in general than the gray KBOs (see Figure 2). This suggests that the red KBOs have experienced less disruption than the gray KBOs over our solar system’s history. Moreover, when the gray and red populations are categorized further into specific dynamical classes (e.g. objects in nearly circular orbits or objects that are actively scattering off of Neptune, for example), the same trend emerges. This means that the overall trend is not biased by any single subpopulation of objects.

But what if the observed trend between color and orbital inclination in the gray and red KBO populations is simply due to biases in the surveys? Previous studies have shown that redder objects tend to be more reflective, making them brighter and more readily detected. The authors also note that few surveys target higher inclinations and that those surveys tend to use redder filters. They use both analytical calculations and a survey simulation code to estimate the effects of these factors. They find that the potential biasing factors would actually result in more red KBOs detected with high orbital inclinations — exactly opposite of the trend they find in the data! Furthermore, their survey simulations show that they find many fewer red objects than their models predict. This implies that the color-inclination trend observed is an intrinsic feature rather than one produced by survey bias.

So why does this trend between color and inclination exist? Prior to today’s paper, two hypotheses competed for the top spot: (1) all KBOs were originally similar, but collisions and other resurfacing processes altered both their colors and inclinations, and (2) the two color populations originally formed in different locations in the protoplanetary disk from different materials, and the gray KBOs were flung outward into the Kuiper Belt. Since collisions affect both orbital inclination and eccentricity, the authors would expect a color-eccentricity trend as well if hypothesis (1) were correct. However, no such trend exists in the data, suggesting that the two color populations did, in fact, originally form in different regions of our solar system. The results from today’s paper are suggestive of hypothesis (2), yet 229 KBOs is only a tiny fraction of all the KBOs waiting to be discovered and studied. Col-OSSOS is still taking data, the Large Synoptic Survey Telescope (LSST), which will turn on in 2023, is expected to detect ~40,000 KBOs with well-measured colors. And that will still only be a fraction of the predicted number of KBOs (possibly more than 100,000 larger than 100 km, and even more smaller than that). There is still a lot of solar system to explore!

About the author, Stephanie Hamilton:

Stephanie is a physics graduate student and NSF graduate fellow at the University of Michigan. For her research, she studies the orbits of the small bodies beyond Neptune in order learn more about the Solar System’s formation and evolution. As an additional perk, she gets to discover many more of these small bodies using a fancy new camera developed by the Dark Energy Survey Collaboration. When she gets a spare minute in the midst of hectic grad school life, she likes to read sci-fi books, binge TV shows, write about her travels or new science results, or force her cat to cuddle with her.

composite image of a complex-structure spherical bubble of emitting gas of different colors

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: Formation of carbon-enhanced metal-poor stars as a consequence of inhomogeneous metal mixing
Author: Tilman Hartwig and Naoki Yoshida
First Author’s Institution: The University of Tokyo, Japan
Status: Submitted to ApJL

“Star Light, [Supernova] Bright”

Though the Big Bang and the birth of the universe as we know it — or, at least, *think* we know it — all happened way before any of us were born, we can still piece together the universe’s history from the starlight we observe today.

Scientists believe that the very first stars in our universe were born a long, long, long, long, long time ago, when the universe was “just” a few hundred million years old (much younger than the universe’s current age of nearly 14 billion years). These first stars were huge — scientists believe they might have been a hundred or so times more massive than the Sun. They were born of gas containing only hydrogen, helium, and tiny traces of lithium — the only three elements that were even around after the Big Bang. All elements heavier than hydrogen and helium in the universe, which astronomers refer to collectively as “metals”, were forged later, after these first stars exploded into brilliantly-bright supernovae and expelled the first heavier elements out into space. These first metals can be traced in the “second-generation” stars, which are the extremely metal-poor stars that were born after the first stars went supernovae. Scientists study second-generation stars in our Milky Way to learn more about how they formed and how the first stars led to their birth.

In today’s astrobite, we consider the story told by a special class of second-generation star: the carbon-enhanced, metal-poor (CEMP) stars. CEMP stars are metal-poor but have relatively high carbonicity, which means they have enhanced amounts of carbon compared to their iron content. Specifically, we look at CEMP-no stars, which are CEMP stars that also have relatively little barium with respect to iron. These CEMP-no stars are believed to directly represent the chemical composition of the environment they formed in.

At this time, however, we’re still not sure how these carbon-enhanced stars formed. One theory says that CEMP-no stars were born after faint supernovae. Since faint supernovae are known to expel relatively less iron than more “normal” supernovae, and since CEMP-no stars have carbon that’s enhanced relative to their iron content, it’s possible that CEMP-no stars show carbon enhancements because they were born after faint supernovae. However, it’s not clear what percentage of the universe’s first stars may have exploded as faint supernovae. It’s also not clear if that percentage was enough to explain all of the CEMP-no stars we expect there to be in the universe.

Today’s authors consider a different perspective. They question if the carbon enhancements observed for these CEMP-no stars might be explained in part by inhomogeneous metal mixing, an uneven distribution of metals in the environment where they formed. So far, not much research has been done on the effects of inhomogeneous mixing of elements in the early universe. So today’s authors used theory and modeling to test their scenario, in which inhomogeneous metal mixing leads to the formation of a CEMP-no star.

To Mix and Make a Star

We can break down the authors’ proposed scenario for forming a CEMP-no star into four crucial steps, which are illustrated in Figure 2:

  1. One of the universe’s first stars explodes into a supernova.
  2. The explosion eventually leads to overdensities in the surrounding gas, such that some parts of the gas are ‘clumpier’ than others. Due to inhomogeneous mixing after the explosion, these clumps have differing elemental abundances from each other.
  3. A clump with higher carbonicity relative to another nearby clump collapses and forms stars.
  4. The newly-formed stars send out energetic photons. These photons pierce the other nearby clump, break apart the molecules contained in that nearby clump, and thus stop that clump from collapsing and making its own stars as well.
inhomogeneous mixing schematic

Figure 2: A graphic illustrating the authors’ scenario. In the first panel on the left, a first star explodes into a supernova that has a typical carbon abundance. In the second panel we see how, due to inhomogeneous mixing, the supernova leads to a clump of gas that has higher carbonicity (along the top row) and a clump that has less carbonicity (along the bottom row). Then in the third and fourth panels, we see that the clump with higher carbonicity produces CEMP stars. These stars send out energetic photons that prevent the clump with less carbonicity from producing stars as well. [Hartwig & Yoshida 2019]

The authors used oodles of theory to build and test a model of this scenario. Here are just a few of the many aspects of the scenario that they explored in detail:

  • How quickly the clump with higher carbonicity would need to collapse
  • How various cooling methods for the surrounding gas would affect the clump’s timescale of collapse
  • How long it would take the newly formed stars to send out energetic photons

The authors’ work culminated in an analytical, closed set of equations that related the carbonicity of the clump to the difference in carbonicity (and thus the level of inhomogeneity) between that clump and its neighboring clump. They found that this relationship depended most strongly on the difference in carbonicity and the physical distance between the two clumps.

formation of CEMP-no stars

Figure 3: Predictions of how well the authors’ inhomogeneous metal mixing scenario explains the formation of 64 CEMP-no stars that have been observed. The x-axis shows the distance between the two clumps in parsecs (pc). The y-axis represents the minimum difference in carbonicity between the two clumps (where higher numbers mean a larger difference) that would allow this scenario to produce a CEMP-no star. The black line is the 50% line. So for example, if we pick a spot along the black line, then 50% of the observed CEMP-no stars in the survey could be explained by the corresponding distance and difference-in-carbonicity values, while another 50% would require a larger difference in carbonicity. The red and green areas explain 0% and 100% of the observed CEMP-no stars, respectively. So if all of the clumps resulting from the first stars’ supernovae fell into the green region, then this scenario would explain 100% of the CEMP-no stars observed in the survey. [Hartwig & Yoshida 2019]

Figure 3 predicts how well this scenario could explain the formation of 64 CEMP-no stars that have been observed. The authors find that for their standard model, with a clump distance of 30 pc and a difference in carbonicity of about 1 unit, about 11% of observed CEMP-no stars can be explained by this scenario.

They stress how they’re not saying that all CEMP-no stars in the universe formed through this inhomogeneous pathway. They’re merely proposing that this is how a certain proportion of the CEMP-no stars we observe today may have formed. They look to future 3D simulations to dive deeper into inhomogeneous mixing, and investigate how efficiently the process might have occurred in the early universe. But in the meantime, if we couple this inhomogeneous pathway with the faint-supernova pathway we discussed at the beginning of this astrobite, then we may not need so many faint supernovae after all to tell the story of how these CEMP-no stars came to be.

About the author, Jamila Pegues:

Hi there! I’m a 3rd-year grad student at Harvard. I focus on the evolution of protoplanetary disks and extra-solar systems. I like using chemical/structural modeling and theory to explain what we see in observations. I’m also interested in artificial intelligence; I like trying to model processes of decision-making and utility with equations and algorithms. Outside of research, I enjoy running, cooking, reading stuff, and playing board/video games with friends. Fun Fact: I write trashy sci-fi novels! Stay tuned — maybe I’ll actually publish one someday!

Sunspot

Editor’s note: This article, written by AAS Media Fellow Kerry Hensley, was originally published on Astrobites.

Are All Sun-like Stars the Same?

We refer to stars with approximately the same spectral type as the Sun as “Sun-like,” but how similar are they really? One way to gauge this is by studying the stars’ magnetic activity, like their starspots (relatively cool areas of the stellar photosphere where magnetic flux bubbles out of the surface) or stellar flares (sudden releases of energy in the form of lots and lots of photons — all the way from X-ray to radio).

sunspots

Figure 1: The starspots studied in this paper are generally much larger than a typical sunspot. A particularly large sunspot, spanning 80,000 miles, is shown here. [NASA/SDO]

Some Sun-like stars have been observed to unleash so-called superflares, which are thought to arise from processes similar to garden-variety solar flares but have 10,000 times the energy. Has the Sun ever set loose a superflare? Could it do so in the future? It’s not clear yet, but it’s an important question to ask, since a superflare could seriously disrupt the satellite networks we’ve come to rely on. By studying flares on other Sun-like stars, we can get a better sense of the similarities and differences between the Sun and the Sun-like stars scattered across the universe.

Superflares can also tell us something about how magnetic fields are generated and configured on other stars; superflares (and solar flares) seem to be linked to starspots (see Figure 1), which are a visible manifestation of a star’s coiled and twisted magnetic field. By studying the starspots that superflares are linked to, we can gain a better understanding of the magnetic dynamos of other stars.

However, our telescopes don’t have the resolution necessary to directly image starspots on other stars. How do we study activity on distant stars?

Kepler: Not Just for Planets!

Led by Kosuke Namekata (Kyoto University, Japan), the authors of today’s paper used Kepler space telescope (may it orbit in peace!) light curves for over 5,000 stars to study starspots on Sun-like stars. In order to identify starspots, the authors searched for repeated dips in the Kepler light curves — signaling the spots transiting the visible face of the stars as they rotate. In total, they were able to track 56 sunspots as they formed and faded (see Figure 2).

Kepler light curve

Figure 2: Example Kepler light curve (a), along with the residual between the data (black) and the fit (red) in panel (b), the phase of the starspots (c), and the depth of the minima as a function of time (d) for a star from this study. [Namekata et al. 2018]

For each of the starspots, the authors calculated the area (from the depth of the brightness dip), the lifetime (from how long they were able to track the presence of the brightness dips), and the rate at which it emerged and decayed (from how the starspot area changed over time).

The authors found that starspots tended to emerge and decay at rates consistent with what we expect from studying spots on our own Sun, which hints that starspots on stars near and far are governed by the same processes. They also found that the lifetimes of the individual spots (10–350 days) tended to be shorter than expected given their area (0.1–2.3% of the stellar surface), but cautioned that the starspot lifetimes could be underestimated because of the difficulty of detecting the spots just as they are emerging and fading. Figure 3 shows a comparison of the areas and lifetimes of sunspots and starspots.

Starspot lifetime versus area

Figure 3: Starspot lifetime versus area for both Sun-like stars (filled circles) and the Sun (black and grey crosses). Sunspots tend to follow the Gnevyshev-Waldmeier (GW) law, while starspots on other stars tended to have shorter lifetimes for a given area. [Namekata et al. 2018]

The lifetimes of the largest starspots — those with areas of about 10,000 millionths of the solar hemisphere (about 30 billion square kilometers) — tended to be about a year. The rate of superflare occurrence also seems to be about once a year, suggesting that the presence of a large starspot is a strong indicator that a superflare will be released.

We still have a long way to go toward understanding magnetic activity, starspots, and superflares on Sun-like stars, but today’s paper gets us one step closer. Hopefully, the wealth of Kepler data will continue to provide discoveries like this for many years to come!

Citation

“Lifetimes and Emergence/Decay Rates of Star Spots on Solar-type Stars Estimated by Kepler Data in Comparison with Those of Sunspots,” Kosuke Namekata et al 2018 ApJ, in press. https://arxiv.org/abs/1811.10782

TRAPPIST-1

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 written by a guest author; the original can be viewed at astrobites.org.

Title: Planet–Planet Tides in the TRAPPIST-1 System
Author: Jason T. Wright
First Author’s Institution: The Pennsylvania State University
Status: Published in RNAAS

In May 2016, the world was struck with sudden excitement over the discovery of the Trappist-1 system. At just 12 parsecs away, the system is host to several Earth-sized planets inside the habitable zone, which makes said planets prime candidates for harbouring life (see this bite and this one for more). The discovery of this neighbouring exoplanet system ignited the curiosity not only of astronomers and exoplanet scientists who had a new system to study, but also of the general public, who were excited to follow the search for possible signs of extraterrestrial beings.

However, as we peer more deeply into the dynamics of the system, the once idyllic scene of Trappist-1 is rapidly becoming more complex. The system is unique in that all the planets are very tightly packed, with the furthest out only having an orbital period of 12 days. While the questions of excess radiation and water loss have been well parsed, today’s paper calls attention to the role of planet–planet tides in the system.

Formalism

The tidal strain ϵ on a body p scales inversely to distance cubed, and proportionally to the mass of the interacting object q. We are all familiar with the role of tides on Earth, which cause natural wonders like the Bay of Fundy. However, the tides on Earth are caused by the gravitational influence of the Moon and the Sun on Earth’s oceans (see Figure 1). These two bodies have the greatest effect, because the Sun is the most massive body in our system, and the Moon, while not massive, is very close.

tides on Earth

Figure 1: The main cause of Earth’s two tides is the Moon, but the Sun’s gravitational pull cannot be neglected. As seen above in this infographic, when the pull of the Sun and the Moon align (the blue and the orange arrows), the amplitude of tides on Earth increases, which causes a spring tide. When the gravitational forces are at right angles, the amplitude of tides on Earth is minimized, which is known as a neap tide. [Katie Harris]

While all objects in our solar system (and indeed, everywhere in the universe) gravitationally interact, the tidal effects of the other planets in our system on Earth are negligible. That is not true for Trappist-1, where the planets are much closer together. Despite the insignificant mass of the planets compared to that of the host star, their proximity to one another means that they require further attention.

Wright takes the ratio of the tidal strain of every planet on every other planet in the Trappist-1 system and finds that for every planet, there is at least one other planet where the ratio of the tidal strain of the interacting planet is at least 10% of that of the tidal strain of the star, meaning that planet–planet tides cannot be ignored. In fact, for planet g, the effect of planet f is 2.7 times that of the host star, meaning that the tidal effect of the neighbouring planet is the dominant one for that particular system.

What Does this Mean?

If planet–planet tides are strong forces on the Trappist-1 planets, it could have significant consequences for any hypothetical life on the planet. Lingam & Loeb (2018) suggest that stronger tides could have a positive influence on abiogenesis, biological rhythms, nutrient upwelling, and stimulating photosynthesis. So, while the inclusion of planet–planet tides might initially be a positive thing in terms of the Search for Extraterrestrial Intelligence (SETI) and finding alternative Earths, many important factors for determining the effect of tides, such as the spin states of the planets, are still under investigation — and they may be a cause for pause before planning an interstellar trip.

About the author, Katie Harris:

This astrobites guest post was written by Katie Harris, a Master of Space Studies student at the International Space University in France. She completed her undergraduate degree in Astrophysics at the University of Toronto, where she did research on infrared spectroscopy instrumentation and Bayesian statistics. She is interested in all things space and is currently working towards a career in space medicine and crossover technology development for medicine and astronomy.

pulsar pulses

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 that looks back at a paper from 2006; the original can be viewed at astrobites.org.

Title: Predicting the Starquakes in PSR J0537-6910
Authors: John Middleditch, Francis E. Marshall, Q. Daniel Wang, Eric V. Gotthelf, William Zhang
First Author’s Institution: Los Alamos National Laboratory
Status: Published in ApJ

pulsar

Artist’s illustration of a pulsar, a fast-spinning, magnetised neutron star. [NASA]

Pulsars (rotating, magnetised neutron stars) emit radiation that sweeps periodically over the Earth (like the beam of a lighthouse sweeping across the ocean). We detect this radiation as a sequence of pulses, with the frequency of the pulse corresponding to the frequency of rotation of the star. Pulsars will typically spin down over their lifetime due to electromagnetic braking, but this is a fairly slow process. Occasionally, in some pulsars, we will detect a sudden increase in the frequency of the pulses. This is called a pulsar glitch. Essentially, the mismatch in the rotation of the fluid inside the star and the solid crust on the outside of the star causes a catastrophic event that we see as an increase in the frequency of the pulses.

The question that the paper we’re exploring today — originally published in 2006 — seeks to answer is: can you predict the next glitch in a pulsar? In general, this is a challenging task, with different pulsars exhibiting different glitching behaviours that need to be captured in your model. However, for one particular pulsar, PSR J0537-6910, this can be accomplished fairly straightforwardly, due to the strong correlation between the size of each glitch and the waiting time until the next glitch. The authors of today’s paper exploit this correlation to develop a method to predict the next starquake on PSR J0537-6910.

What Is a Pulsar Glitch?

Glitches are thought to be caused by superfluidity inside a neutron star.  When a substance cools down to a temperature below a critical temperature Tc, it forms a superfluid state, i.e., a state that flows without viscosity. But neutron stars are much hotter than any substances we find on Earth (they run around 106 K). So how can a neutron star be cool enough to contain a superfluid? The matter inside a neutron star is extremely dense, and it has very different properties from terrestrial matter. In particular, the matter inside a neutron star has a high critical temperature — Tc ~ 109 K — and the neutron fluid inside the star can therefore form a superfluid even at high temperatures.

A cartoon of the angular velocity of the crust of a pulsar vs. time during a glitch. The pulsar glitch is characterised by (1) steady spin-down of the star, (2) a step-like jump in frequency and (3) an ensuing gradual relaxation back to the original spin-down rate. [Adapted from van Eysden 2011]

The pulsar spins down due to electromagnetic processes. The pulsar is a rapidly rotating magnetised body — if a rotating magnetic dipole is inclined at some angle from the rotation axis, it emits magnetic dipole radiation at the rotation frequency. The emission of this electromagnetic radiation leads to lost rotational energy. Therefore, the star spins down as a consequence, and we call this magnetic braking.

The crust of the neutron star spins down continuously because the magnetic field lines are locked into the crust. However, the superfluid inside the star is likely to be at least partially decoupled from the spin-down of the crust. Therefore, an angular velocity lag builds up between the crust and the superfluid as the superfluid continues to spin at the same rate for a period of time, uninhibited by the magnetic braking. Eventually, the lag builds up to a critical value. At this stage, there is an angular momentum transfer to the crust from the superfluid which causes a glitch. Because glitches are believed to be intimately connected to the behaviour of the interior superfluid, astronomers believe pulsar glitches offer a rare window into the processes occurring inside the star.

How Do Glitches Occur?

It is still not known for certain exactly why and how glitches occur in neutron stars, but a number of possible mechanisms have been proposed. For example, vortex avalanches are a possible mechanism for glitches. In the superfluid, there are many vortices (i.e. tiny whirlpools) induced by the rotation of the star. Vortices are “trapped” or “pinned” to certain locations in the crust. This just means they are fixed in that location until there is enough force to unpin them. When enough lag builds up between the superfluid and the crust, the force is sufficient to unpin them. As they unpin, they transfer angular momentum to the crust and cause a glitch. Another possible mechanism is starquakes, which mean there is a cracking of the neutron star crust that causes a rearrangement of the matter inside the star.

Glitching pulsars can be thought of as belonging to two different classes: Crab-like and Vela-like. The Vela pulsar typically has large glitches which occur fairly periodically, while the Crab pulsar has a power law distribution of glitch sizes. Therefore, it is difficult to develop a model that captures the behaviour of these two classes simultaneously. In this paper, the authors focus on a single pulsar (PSR J0537-6910) and use its unique properties to predict when it will next glitch.

Reliable Glitcher: PSR J0537-6910

PSR J0537-6910 is a 62-Hz pulsar in the Large Magellanic Cloud. The authors report on seven years of observation of this pulsar, containing 23 glitches. PSR J0537-6910 is unique among glitching pulsars. Firstly, it is the fastest spinning young pulsar and one of the most actively glitching pulsars we know of. Secondly, its glitching properties are particularly favourable to glitch prediction due to the very strong correlation between the waiting time from one glitch to the next and the amplitude of the first glitch, shown in the figure below. The authors suggest the predictable behaviour of the glitches of this pulsar is associated with the the angular velocity lag build-up causing a “cracking” in the crust as glitches occur, with the smaller glitches that precede a large glitch corresponding to more localised cracks.

Figure 3: Waiting time vs. glitch size for PSR J0537-6910. [Middleditch et al. 2006]

Impressively, we’re able to predict the waiting time for the next glitch of PSR J0537-6910 to within a few days. Predictions of this accuracy have not been achieved with any other pulsar.

About the author, Lisa Drummond:

I am an astrophysics PhD student with interests in compact objects and gravitational waves. I studied neutron star interiors for my Masters thesis at the University of Melbourne, Australia and now I am doing my PhD at MIT.

planet formation

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: In situ formation of icy moons of Uranus and Neptune
Authors: Judit Szulágyi, Marco Cilibrasi and Lucio Mayer
First Author’s Institution: University of Zurich, Switzerland
Status: Accepted to ApJL

With over 100 moons between them, gas giants Saturn and Jupiter host most of our solar system’s satellites. Moons are thought to form in the gaseous circumplanetary disks (CPDs) that surround giant planets during their later stages of formation; the satellites develop from the disks in much the same way as planets themselves are formed.

But what about smaller planets like Neptune and Uranus? Today’s bite delves into the world of radiative hydrodynamical simulations to see whether CPDs — and thus moons — could also form around our ice giants.

The Real Moons

Given that Uranus hosts five major moons in similar, circular orbits, this ice giant’s satellites likely formed in a circumplanetary disk. A debris disk, like the one that may have formed our own Moon, is unlikely; debris-disk satellites would have very little water, which is not what we observe for Uranus’s moons.

Figure 1: Triton, as seen by the Voyager 2 spacecraft. [NASA/Jet Propulsion Lab/U.S. Geological Survey]

Neptune, however, is only home to one major moon, Triton, which has an unusual composition and retrograde orbit. Triton is more than likely a captured Kuiper Belt object that is thought to have severely disrupted the dynamics of the pre-existing Neptunian system. In fact, previous work suggests that without the existence of satellites around Neptune, it wouldn’t have been possible for the system to capture an object like Triton.

Let’s Form Some Disks

Forming a moon isn’t an easy job for a planet. Previous studies have revealed that there are two key planetary properties that determine how likely it is for a gaseous CPD to form around a planet — mass and temperature.

  • Mass: Terrestrial planets like Venus are too small for CPDs to form; any satellites that exist around them are usually captured (as in the case of Mars) or the result of a planet–planet impact (as in the case of Earth).
  • Temperature: CPDs are more likely to form if the planet is cooler, BUT a cooler planet radiates its formation heat faster and has less time to form a disk.

The authors deployed hydrodynamical simulations to recreate the later stages of planet formation for Uranus and Neptune. This involved setting the planets as point masses in the centre of the simulation surrounded by a gas disk, and then letting simulated nature (heat transfer, ideal gas laws, gravity) take over. For more details regarding hydrodynamical simulations, see this post on simulating the entire universe (!!) and this one on gas accretion.

simulated circumplanetary disks

Figure 2: Zooming in to the circumplanetary disk around Uranus (left column) and Neptune (right column). The different rows indicate the planetary surface temperatures: 100 K (top), 500 K (middle) and 1,000 K (bottom). [Szulágyi et al. 2018]

From the gas density plots in Figure 2, in which yellow/white indicates the densest region, we see that once the simulated Neptune and Uranus cooled to below 500 K a circumplanetary disk was able to form. This conclusion is drawn visually from the disk-like structure that has formed at 100 K (top row of Figure 2); this structure is not visible at 500 K and 1,000 K (middle and bottom row of Figure 2). It makes sense that both planets require a similar temperature as they are of almost equal mass. Next, the authors created a synthetic population of satellite-forming seeds within the disk to see if these protosatellites will turn into fully fledged moons by accreting matter.

Simulated Moons vs. Reality

Formation timescale of moons around Uranus

Figure 3: Formation timescale of moons around Uranus (left) with the distribution of their masses on the right. The red vertical lines represent Uranus’s 5 major moons. [Szulágyi et al. 2018]

In the case of the 100-K CPD around Uranus (Figure 2, top left panel), the majority of the synthetic population of moons that developed around Uranus formed over a 500,000-year period, at the location of the disk where the temperature was below the freezing point of water. This means that many of these moons would be icy — just like the actual moon population observed around Uranus. The masses of the moons spanned several orders of magnitude — a range that includes the masses of the satellites we observe today (red lines in Figure 3). Around 5% of the authors’ simulations yielded 4–5 moons between 0.5–2 times the mass of the current Uranian satellites.

formation timescale of moons around Neptune

Figure 4: Like Figure 3, above, the formation timescale of moons around Neptune (left) with the distribution of their masses on the right. The red vertical line represents the moon Triton. [Szulágyi et al. 2018]

Similar trends were also observed for Neptune as, once again, the entire population of moons had temperatures below the freezing point of water — meaning Neptune is also more likely to form icy satellites. Generally, simulated Neptune struggled to make moons as massive as Triton. This isn’t worrying, however, since Triton is likely to be a captured Kuiper Belt object.

So, overall, it is possible to form satellites around ice giants! This is an exciting result for exomoon lovers because Neptune-mass exoplanets are the most common mass category of exoplanet we’ve found so far. Furthermore, icy moons are the main targets for extraterrestrial life in our own solar system; ice-giant satellites elsewhere in the universe could be a similar source of potential in our search for habitable worlds.

About the author, Amber Hornsby:

Third-year postgraduate researcher based in the Astronomy Instrumentation Group at Cardiff University. Currently, I am working on detectors for future observations of the Cosmic Microwave Background. Other interests include coffee, Star Trek and pizza.

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