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Milky Way

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 Mass Inflow and Outflow Rates of the Milky Way
Authors: Andrew J. Fox et al.
First Author’s Institution: AURA for ESA, Space Telescope Science Institute
Status: Accepted to ApJ

Galaxies are so large that it can be hard to imagine them changing over time. However, we believe that galaxies are living and breathing entities, accreting and ejecting mass all throughout their lives. The Milky Way is no exception. Characterizing the rates of mass flow and the mass loading factor for galaxies, though, is crucial to understanding the details of this so-called galactic fountain model. In today’s paper, the authors provide new estimates of these rates for the Milky Way. They also present the first estimate of the mass loading factor (the ratio of material flowing out of the galaxy to the star formation rate) for the outflowing material from the entire Milky Way disk. Essentially, this measures how efficiently the Milky Way recycles the gas it takes from its surroundings. These are very cool results, so let’s break down exactly what they mean.

Why Is Mass Flowing In and Out of a Galaxy?

supernova

Artist’s illustration of a supernova, a type of stellar feedback that can remove mass from our galaxy. [NASA/CXC/M. Weiss]

A galaxy primarily exchanges low-density gas with its surroundings. Over time, some of this gas surrounding the galaxy will begin to clump together, and gravity will cause these clumps to fall back into the galaxy. This allows a galaxy to sustain its star-formation rate for a long period of time. Once these stars form, the most massive ones will start undergoing significant mass loss and exerting strong radiation pressure on the ambient medium. They will then end their lives as supernovae: brilliant explosions that inject more energy and momentum into their surroundings. These processes are collectively known as stellar feedback, and they are responsible for pushing gas back out of the Milky Way. In other words, the Milky Way is not an isolated lake of material; it is a reservoir that is constantly gaining and losing gas due to gravity and stellar feedback.

That Sounds Complicated. How Do the Authors Figure Out Which Gas Is Going In and Out?

Great question! Unfortunately, none of the gas travels with a bumper sticker that says ‘Milky Way Bound’. This means that the authors need to figure out which gas is likely to escape the Milky Way and which is likely to fall back in. They do this by identifying high-velocity clouds (HVCs) of gas that are traveling faster than the rotational speed of the Milky Way’s disk, meaning that they must represent inflowing or outflowing gas. Once they have identified a HVC, they check whether the cloud is moving towards the galactic disk or away from it. Finally, they ignore HVCs that are known to reside in structures (such as the Fermi Bubbles) that don’t trace the inflowing or outflowing gas. The final sample of HVCs is shown in Figure 1.

high velocity clouds

Figure 1: Plot of all HVCs identified in the paper. Inflowing clouds are shown in blue, outflowing clouds are shown in red, and the green regions show areas in which HVCs were ignored as they would not trace the inflowing or outflowing gas well. Black points show observations in which no HVCs were detected. [Fox et al. 2019]

What Were The Results?

The authors estimate the inflow rate to be 0.53 +/- 0.31 solar masses per year and the outflow rate to be 0.16 +/- 0.10 solar masses per year. This means that the Milky Way currently appears to have a net inflow of gas. HVCs only have lifetimes on the order of 100 million years, so it is important to note that this result should not be extended to very long timescales. Furthermore, the outflow rate is a lower limit; the true outflow rate could be higher if other regions like the Fermi Bubbles are included. Nevertheless, this exciting result provides evidence that the Milky Way disk may currently be gaining mass.

The paper also presents an estimate for the mass loading factor of roughly 0.1 using an independent measurement of the Milky Way’s star formation rate. This means that roughly 10% of the mass that forms stars is ejected back out of the galaxy. This result, together with the measurements of the inflow and outflow rates, can all help astronomers get closer to building a realistic model of the Milky Way.

About the author, Michael Foley:

I’m a graduate student studying astrophysics at Harvard University. My research focuses on using simulations and observations to study stellar feedback — the effects of the light and matter ejected by stars into their surroundings. I’m interested in learning how these effects can influence further star and galaxy formation and evolution. Outside of research, I’m really passionate about education, music, and free food.

'Oumuamua

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.

*just to be clear, the aliens I am talking about are rocks and not alive nor intelligent. Sorry 🙁

Title: Hidden Planets: Implications from ‘Oumuamua and DSHARP
Authors: Malena Rice, Gregory Laughlin
First Author’s Institution: Yale University
Status: Accepted to ApJL

What if I told you that we have the opportunity to directly study other solar systems? You’d be like, “guuurrrlll, say whaaaat??” And then I’d say:

Similarly to how we can find chunks of Mars or pieces of the astroid belt on Earth, we have rocks from other solar systems flying around interstellar space — and a few just so happen to enter our solar system. This was only recently proven with the discovery of Interstellar Object (ISO) ‘Oumuamua: ‘Oumuamua was ejected from a different solar system and zoomed right into ours. Slipping between the Sun and Earth, it was detected as it started its journey back outside the solar system. ‘Oumuamua was the first object of its kind to be discovered, and it brings up the question, how many bits of other solar systems may be floating around and near us? The answer to that question can have wide implications in our understanding of solar-system formation, planet formation, and even compositions of other solar systems.

Today’s paper utilizes the ‘Oumuamua detection in addition to a recent high-resolution protoplanetary disk survey, DSHARP, to predict the number of future ISO detections. To put that number into context, the authors predict how many ISOs the new LSST survey might be able to see. To predict the average number density of ISOs (# of ISOs/volume of space) in our galaxy, astronomers have to come up with different possible methods of mass ejection from extrasolar systems. A prime opportunity to dislodge objects from a solar system takes place while the system is forming — and these dislodged objects can become ISOs. A newly forming solar system takes the form of a protoplanetary disk (see the figure below). The images below are individual protoplanetary disks shining in ~millimeter wavelengths. At these wavelengths we are most sensitive to dust of a similar size, so millimeter-sized dust grains. Each millimeter-sized dust grain is a candidate ISO; they can be flung out of their system by a newly forming massive planetesimal. These millimeter sized grains are much smaller than ‘Oumuamua, but still a good place to start in predicting how many ISOs are out there.

DSHARP disks

Three protoplanetary disks from the DSHARP survey. These images are sensitive to millimeter-sized dust grains, which show some real neat substructure like gaps (dark regions between bright regions) and rings (super bright regions, usually located next to a gap). [DSHARP collaboration]

The DSHARP images above show incredible substructure; we see gaps and rings that we are pretty sure are caused by newly forming Neptune-to-Jupiter-mass exoplanets. The authors show that the planets with the greatest ability to fling material outside their systems are those that are located far from the central star. The three disks pictured in the figure above show strong evidence for multiple planets farther than 5 AU from their central star (1AU is the distance from the Sun to Earth), so they are great examples of systems that can eject objects that become ISOs, like ‘Oumumama. For this reason, the authors use these particular disks as models in their work.

In order to come up with a mass ejection rate (the rate at which mass is lost from the system), the authors set up simulations that had the same initial conditions as the three disk systems pictured above, and for each system they created 3 random populations of dust — the locations and sizes of dust particles were randomly distributed throughout the disk. They then let these 9 total simulations run for a week on a super computer, simulating about 20 million years of the protoplanetary disks’ lives. They then determined how much mass had left the system after that time.

The authors came up with a function of mass ejected over time for millimeter-sized grains, and from that, one can calculate an average number density of these particles in and around our galaxy (you also then need to assume a certain density of stars). The authors found that, on average, for every star there is about 0.09 Earth masses worth of millimeter-sized dust. They used their data from these simulations to extrapolate up to a broader range of ISO sizes. After all, ‘Oumuamua and any interstellar interloper that we can hope to find in our solar system is going to be significantly larger than a few millimeters. If you assume some sort of power-law distribution (put very simply, the larger the ISO is the less there is of it) you can then estimate the total mass ejected from systems similar to the three protoplanetary disks for any ISO size. In this paper, the authors found that over the disks’ lifetimes, about 24 Earth masses worth of material would be ejected from these systems as ISOs with sizes ranging from a few millimeters to a few kilometers.

LSST

Photo of the LSST site taken in May 2019. Full science operations are expected to begin in 2023. [LSST Project/NSF/AURA]

So how do we then make a guess as to how many of these ISOs the LSST mission will see over its lifetime? LSST will be looking at huge swatches of the sky every night for 10 years, and its main purpose is to look at faraway things like galaxies. The authors make an estimate of how many ISOs LSST will detect that are at least 5 AU away from us, taking into account many factors like the reflectivity, size, and distance of the ISO. Their results suggest that LSST will observe several ‘Oumuamua-sized objects (greater than ~15 m) and hundreds of interstellar friendos visiting our solar system with radii of at least 1 m each year! That’s so many! It’s a much higher estimate than other papers — many of which were much more pessimistic, predicting LSST will see none at all. What this paper did differently is to utilize brand-new high-resolution images of these early systems in which ISOs form.

LSST’s main goals are to search for dark matter and answer questions about the formation and composition of our universe. But in this process, it will also be able to answer questions related to more Earthly subjects — not just answering questions like “How did the universe form?”, but also questions like “Is our solar system unique?”.

About the author, Jenny Calahan:

Hi! I am a second year graduate student at the University of Michigan. I study protoplanetary disk environments and astrochemistry, which set the stage for planet formation. Outside of astronomy, I love to sing (I’m a soprano I), I enjoy crafting, and I love to travel and explore new places. Check out my website: https://sites.google.com/umich.edu/jcalahan

NGC 1559

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: Hubble Space Telescope Observations of Mira Variables in the Type Ia Supernova Host NGC 1559: An Alternative Candle to Measure the Hubble Constant
Authors: Caroline D. Huang, Adam G. Riess, Wenlong Yuan, Lucas M. Macri, Nadia L. Zakamska, et al.
First Author’s Institution: The Johns Hopkins University
Status: Submitted to ApJ

Disclaimer: The author was not involved in this work in any way.

If you want to figure out the fate of our universe, the value of the Hubble Constant (H0) would be handy to have. H0 tells us how fast the universe is expanding right now… I mean now… actually now — you get the picture. The Hubble Constant isn’t constant over time. Taken with other quantities, its current value can tell us a lot about the universe, such as its age and ultimate fate.

As great as H0 is, though, it’s a bit tricky to measure. And to complicate things, the measured value of H0 changes with the measurement method. Currently, Planck measurements of the cosmic microwave background (CMB) return H0  = 67.4 ± 0.5 km/s/megaparsec (km/s/Mpc). This value is significantly smaller than the measurement obtained by using the distances and redshifts/velocities of distant galaxies, which is H0 = 74.03 ± 1.42 km/s/Mpc. The difference between these two measurements has been increasing since the 1990s as the measurements have been refined (see Figure 1), leading astronomers on both sides to scrutinize their methods for unaccounted errors.

H0 measurements over time

Figure 1: Measured values of H0 over time, showing how the CMB (black points) and Cepheid (blue points) measurements have been diverging. The red points come from H0 measurements using the Tip of the Red Giant Branch (TRGB). [Freedman et al., 2019]

The method that uses galaxy distances and velocities relies heavily on how those distances are measured. Currently, distance measurements for the purposes of determining H0 are closely tied to variable stars called Cepheids. To double-check the Cepheid-based distances, we need other objects to use as distance indicators.

One of these objects could be Mira variable stars (Miras). In this paper, the authors search for Miras in NGC 1559 using Hubble Space Telescope (HST) observations. NGC 1559 has hosted another, better understood distance indicator — a Type Ia supernovae — making it a good place to test how Miras can perform as extragalactic distance indicators.

O, See the Miras!

Miras are Asymptotic Giant Branch stars, meaning that they’ve run out of helium to burn in their cores. Their cores are inert and contain oxygen and carbon, and their outer shells consist of still-burning hydrogen. The outer shell puffs out as the star grows hotter, then cools down and shrinks. This is what causes the periodic brightness variations in a Mira: it gets bigger and brighter, then smaller and dimmer. Miras are named for their archetype, Mira, which is also known as O Ceti since it’s located in the constellation of Cetus.

Mira

Figure 2: The eponymous Mira, also known as O Ceti, as seen in different wavelengths by the HST. [M. Karovska (Harvard-Smithsonian CfA)/ NASA/ESA]

Miras have periods ranging over 100–3000 days, though they’re typically less than 400 days. In addition to having distinctive periods, Miras distinguish themselves from other variable stars with relatively dramatic changes in brightness in optical and infrared light. Miras can dredge up material from their core to their surface, so they’re often classified by their surface carbon-oxygen ratio as oxygen-rich (O-rich) or carbon-rich (C-rich).

Like Cepheids, Miras have a period–luminosity relation (PLR) that gives them their power as distance indicators. Mira PLRs are particularly distinct in the infrared. O-rich Miras with periods less than 400 days follow PLRs most tightly, so they’re currently the most reliable Mira distance indicators.

Pulling Miras Out of the Mire

To find Miras in NGC 1559, the authors use infrared observations taken by the HST’s Wide Field Camera 3. They identified the objects that were most likely to be genuinely variable. Then they determined the most likely periods of those objects, testing periods between 100 and 1000 days (since Mira periods typically lie within that range).

The authors then applied cuts based on the amplitude of the objects’ variations in brightness to select the O-rich Miras from the sample. The authors use techniques from other studies to estimate the degree of C-rich Mira contamination.

The authors end up with sample of 115 O-rich Miras. Since their sample is small, the authors draw on PLRs determined from the Large Magellanic Cloud (LMC) while fitting the NGC 1559 PLR (see Figure 3).

NGC1559 Miras

Figure 3: PLRs for the NGC 1559 Miras obtained using two different observed PLRs of LMC Miras from the OGLE Project (left) and Yuan et al. 2017b (right). The x-axis is the log of the period in days and the y-axis is magnitude in an infrared filter used on the HST. n = number of Miras; σ = scatter or spread in the relation; μ = distance modulus or the relation between apparent magnitude and absolute magnitude. [Huang et al. 2019]

Another Way Out

Before coming up with a measurement of H0, the authors compare the NGC 1559 PLR to the Mira PLR they obtained for NGC 4258 in a previous study. NGC 4258 hosts another reliable distance indicator: a water megamaser (a maser produces radiation by using particles that are stimulated by long wavelengths of light). The authors calibrate the NGC 1559 Miras using the megamaser distance to NGC 4258.

Using the distances to the LMC, NGC 4258, and NGC 1559 with a sample of Miras with consistent periods  gives — *drumroll* — H0 = 73.3 ± 3.9 km/s/Mpc. This value is consistent with the Cepheid-based value of H0 = 74.03 ± 1.42 km/s/Mpc within reasonable expectations on measurement errors.

With this study and Huang et al. (2018) the authors have shown that Miras have great potential as extragalactic distance indicators. As tensions between measurements of H0 increase, independent distance indicators like Miras only grow in importance.

About the author, Tarini Konchady:

I’m a third-year graduate student at Texas A&M University. Currently I’m looking for Mira variables in optical to help calibrate the extragalctic distance ladder. I’m also looking for somewhere to hide my excess yarn and crochet hooks (I’m told I may have a problem).

Pulsar

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: LOFAR Discovery of a 23.5 s Radio Pulsar
Authors: C. M. Tan et al.
First Author’s Institution: Jodrell Bank Centre for Astrophysics, University of Manchester, UK
Status: Published in ApJ

Pulsar Rotation Rates

Neutron stars are formed from massive stars that undergo violent supernova explosions after they run out of nuclear fuel and collapse under their own gravity. Radio pulsars are highly magnetized, rotating neutron stars that emit beams of radiation from their magnetic poles. When these beams of radio emission sweep across our line of sight, they generate radio pulses that can be detected with radio telescopes on Earth. The surface magnetic field strength, age, and internal structure of these objects can be studied through measurements of their rotational rates. Astronomers have now discovered more than 2,700 pulsars in our galaxy, and they’re constantly on the lookout for rare breeds. In today’s astrobite, we cover the discovery of the slowest known spinning radio pulsar, PSR J0250+5854, which has a rotational period of 23.5 s. This exciting finding demonstrates that radio pulsars can rotate much slower than expected and still produce radio pulsations.

LOFAR Superterp

Figure 1: An aerial view of the LOFAR Superterp, part of the core of the extended telescope located in the Netherlands. [LOFAR / ASTRON]

PSR J0250+5854: A Record-Setting Slow-Spinning Radio Pulsar

The authors discovered PSR J0250+5854 on 2017 July 30 using the LOw Frequency ARray (LOFAR) radio telescope (see Figure 1) as part of the LOFAR Tied-Array All-Sky Survey (LOTAAS). Additional follow-up radio observations were performed using the Green Bank, Lovell, and Nançay radio telescopes. Pulsations were detected between 120 and 168 MHz with LOFAR and at 350 MHz using the Green Bank Telescope (GBT), but no pulsed emission was detected at ~1.5 GHz using the Lovell and Nançay telescopes. The pulsar’s radio spectrum (spectral index of α = -2.6 ± 0.5, assuming its flux density follows a power-law as a function of frequency) is remarkably steep compared to the average pulsar population (<α> ≈ -1.8). This suggests that its radio emission is significantly brighter at lower frequencies (see Figure 2).

Radio spectrum of PSR J0250+5854

Figure 2: Radio spectrum of PSR J0250+5854 using LOFAR and GBT observations. The black line shows the fitted spectral index, with 1-σ uncertainties indicated by the shaded gray region. The circle corresponds to the measured flux density from LOFAR Two-meter Sky Survey imaging observations, and the triangles correspond to upper limits on the flux densities from LOFAR Low Band Antenna, Nançay, and Lovell radio telescope observations, respectively. [Tan et al. 2018]

Based on measurements of the pulsar’s rotation spanning more than 2 years, PSR J0250+5854 has an inferred surface dipole magnetic field strength of 26 trillion Gauss, characteristic age of 13.7 million years, and a spin-down luminosity of 8.2 x 1028 erg s-1, assuming a dipolar magnetic field configuration. PSR J0250+5854’s radio beam is very narrow according to the measured width of its pulse profile (the pulse duty cycle is < ~1% below 350 MHz, see Figure 3). Individual single pulses were routinely detected from the pulsar at low radio frequencies, except during brief periods of “pulse nulling” when the pulsar stopped emitting radio pulses. This occurred 27% of the time on average. The pulsar’s slow rotation period of 23.5 s is similar to other classes of pulsars. In particular, magnetars have high magnetic fields, spin periods ranging between roughly 2 and 12 s, and often produce X-ray emission, and X-ray Dim Isolated Neutron Stars (XDINs) have spin periods ranging between 3.4 and 11.3 s. However, no X-ray emission was detected from PSR J0250+5854 during follow-up observations with the Neil Gehrels Swift Observatory X-ray Telelescope.

pulse profiles of PSR J0250+5854

Figure 3: Integrated pulse profiles of PSR J0250+5854 at observing frequencies of 350 MHz (GBT), 168 MHz (LOFAR), and 129 MHz (LOFAR). Here, only 5% of the rotational phase is shown. The inset shows the pulse profile across the whole LOFAR HBA band over a full rotation period. [Tan et al. 2018]

A Needle in a Haystack or a Haystack Full of Needles?

The P–Ṗ diagram is a key diagnostic tool for characterizing how pulsars evolve in time. Using pre-discovery LOTAAS data of PSR J0250+5854 from 2015, the authors measured a spin period derivative of Ṗ = 2.7 x 10-14 s s-1. The pulsar’s rotational parameters place it in the right region of the P–Ṗ diagram (see Figure 4) — an area where few pulsars have been found to reside. In particular, PSR J0250+5854 falls near/below many of the so-called “pulsar death lines,” beyond which pulsars are not expected to emit coherent radio emission. These models are based on assumptions about the conditions in the pulsar’s magnetosphere, such as pair production, which is thought to be essential for the generation of radio emission. Since the radio-emission mechanism in pulsars is not fully understood, searching for additional pulsars near these death regions will help to inform us about how pulsars produce radiation.

P–Ṗ diagram of pulsars

Figure 4: P–Ṗ diagram of pulsars derived from their measured rotational periods and rotational-period derivatives. The positive sloped gray lines indicate characteristic ages of 1 kyr, 100 kyr, 10 Myr, and 1 Gyr. The negative sloped gray lines correspond to inferred surface magnetic-field strengths of 10 GG, 100 GG, 10 TG, and 100 TG. Magnetars (green), XDINSs (orange), RRATs (yellow), and the 8.5-s radio pulsar PSR J2144–3933 are indicated on the plot. The colored lines show the various death-line models, where pulsars below these lines are not expected to produce radio emission. [Tan et al. 2018]

The discovery of PSR J0250+5854 begs the question: Is this a special kind of pulsar, or are there more to be found? The authors argue that more of these slow-rotating pulsars may be lurking around our galaxy, but we simply haven’t been sensitive to detecting them because commonly used Fast Fourier Transform (FFT)-based periodicity search algorithms are not well-suited to detecting slow pulsars with small duty cycles. The authors also point out that the radio emission observed from PSR J0250+5854 was much more erratic at higher frequencies. Therefore, if other slow rotating pulsars are similar to PSR J0250+5854, then this suggests that low-frequency radio telescopes, like LOFAR, may prove to be excellent observatories for searching for these slow rotators.

About the author, Aaron Pearlman:

I am a Ph.D. candidate in Physics at Caltech. My research focuses on searching for new pulsars near the center of the Galaxy using JPL’s Deep Space Network radio dishes in the southern hemisphere. I am also interested in studies of magnetars, fast radio bursts, gravitational-wave searches, and high-energy observations of compact objects. When I’m not hunting for pulsars, I can usually be found hanging out with my dogs or trying the latest vegetarian cuisine Los Angeles has to offer!

planet formation

Editor’s note: AAS Nova is on vacation this week. Normal posting will resume next week; in the meantime, we hope you enjoy this post from Astrobites, a graduate-student-run organization that digests astrophysical literature for undergraduate students. The original can be viewed at astrobites.org.

Title: On the Terminal Rotation Rates of Giant Planets
Authors: Konstantin Batygin
First Author’s Institution: California Institute of Technology
Status: Published in AJ

The rotation periods of Jupiter and Saturn are 9.93 hours and 10.7 hours, respectively. Now, compared to our tiny Earth that lazes around on a 24-hour rotational period, you might think, “wow, those are some zoomy-bois.” However, our best theories of planet formation tell us that, based on how massive they were when they formed, they should really be doin’ a faster spin.

Fun fact alert: While the sun holds most of the solar system’s mass, Jupiter and Saturn hold the majority of our solar system’s angular momentum.

How Do You Form a Jupiter?

So let’s say you want to make a Jupiter, just for the heck of it. If you follow the rules of our understanding of general planet formation, there are three main steps. You start inside of a protoplanetary disk. There is some sort of gravitational instability where heavy metals can gravitationally collapse and start to form a metallic core. This core acquires a gaseous envelope which can then feed the newly forming planet. Once that gaseous envelope is about the size of the initial core, the planet enters a stage called runaway accretion. That just means that material around the planet falls quickly and efficiently, adding mass rapidly. And BAM — you have a Jupiter-like planet (technically called a Jovian planet). But, following this simple model, once the runaway process begins, the planet is accreting so much mass that our new Jupiter spins faster and faster and has no way to let go of any of its angular momentum. In this simple model, the surface of the planet can reach speeds that equal the escape velocity, which means that the planet breaks apart. That’s not great for planet formation. Plus, when we observe Jupiter and Saturn (and now that we’re gathering more and more data of Jovian planets outside of our solar system), we continue to see rotational velocities well below the planets’ escape velocities. So how in the heck do we slow down a young energetic planet? We turn to the answer that all astronomers look to in times of need: magnetic fields.

Setting Up the Problem of Slowing Down a Chonker Like Jupiter

Today’s paper attempts to lay the groundwork for solving this angular-momentum problem in Jovian-planet formation using magnetohydrodynamics. Big (scary) word, yes, but put more simply, this paper creates a semi-analytic model of a newly forming Jovian planet with a strong magnetic field, and it then explores how the field might slow the planet down. The model breaks the problem into two parts: the circumplanetary disk and the planet itself. Each part of this problem has equations that describe key parameters, such as the temperature, density, and abundance of metals in the surrounding envelope. For the planet part, the author calculates a magnetic field strength based on a typical luminosity of young exo-Jovian planets and uses these properties to calculate the electric conductivity and magnetic induction of the system, which would produce the forces that affect the speed of planet rotation. “Running” this model consists of calculating each of these equations over a series of time steps so that one can further understand how each of these factors change and affect each other as the planet forms.

How the Giant Chonker Was Slowed Down

The results of the model are illustrated in Figure 1 below. The finding of this paper is that if we consider the Jovian protoplanet to have a significant magnetic field, that field will invoke a force in the opposite direction of the rotation of both the circumplanetary disk and the planet itself. Basically, the magnetic field couples to the surrounding disk. Since there is now a force in the opposite direction of the original motion, the planet slows its spin. Angular momentum leaves the system as material feeding the planet gets kicked out of the system and back into the surrounding protoplanetary-disk environment.

planet formation

Figure 1: An illustrative view of planet formation and the effect of magnetic fields (red lines). We are taking a look inside a protoplanetary disk, with the host star to the left, zooming in on a Jupiter-like planet being formed. The planet has its own circle of influence, the edges of which correspond to the purple regions. We can see that material flows onto the planet from above, and that material can only fall onto the planet if it is very nearly falling directly down. Material that falls just off to the side gets added to the de-cretion disk and thus shucked off into the gaseous nebula. The planet slows down via magnetic-field induction that invokes a force in the opposite direction of the original Keplerian rotation, which is the same direction as the planet is rotating. [Batygin 2019]

This paper set up a simple semi-analytic model that did the job of adding magnetic fields to our picture of planet formation. And this model has shown that with a strong magnetic field, is it not only possible to slow the spin of the planet down to speeds that we observe, but also to slow it down quickly. Of course, there are more details that could be added to this model, and there are assumptions made that are difficult to back up with observations. Planet formation, in general, seems to happen relatively fast and early in a solar system’s lifetime, so it is hidden from view and hard to catch. But even with this “simple” model, we can see that magnetic fields are certainly a key factor in the mystery of the slowly spinning Jovian planets.

About the author, Jenny Calahan:

Hi! I am a second-year graduate student at the University of Michigan. I study protoplanetary disk environments and astrochemistry, which set the stage for planet formation. Outside of astronomy, I love to sing (I’m a soprano I), I enjoy crafting, and I love to travel and explore new places. Check out my website: https://sites.google.com/umich.edu/jcalahan

soho image of sun

Editor’s note: AAS Nova is on vacation this week. Normal posting will resume next week; in the meantime, we hope you enjoy this post from Astrobites, a graduate-student-run organization that digests astrophysical literature for undergraduate students. The original can be viewed at astrobites.org.

Title: Was the Sun a Slow Rotator? — Sodium and Potassium Constraints from the Lunar Regolith
Authors: Prabal Saxena, Rosemary M. Killen, et al.
First Author’s Institution: NASA Goddard Space Flight Center
Status: Published in ApJL

Journey to the Sun’s Past

Throughout the solar system’s history, the frequency of flares and eruptive events from the Sun have had a strong effect on the development of the inner planets, from the top of their atmospheres right down to their surfaces. The number of eruptive events the Sun produces just so happens to be closely related to the rate at which it rotates. Therefore, to understand how planets like the Earth came to be, it is incredibly important to understand the Sun’s rotation during the early stages of our solar system’s development. Previous studies have attempted to do so by considering other Sun-like stars. However, today’s authors have found answers by looking much closer to home.

The Moon, Earth’s only natural satellite, is a surprisingly ideal place to look for clues about the history of solar activity. The lack of a thick atmosphere causes solar eruptions that reach the Moon to strip material from its surface, leaving behind an imprint that can be used to understand the Sun’s tumultuous past (but more on that later).

A Model for the Early Sun

Before the authors of today’s paper dove into how the Moon is an ideal place to look for evidence of past solar activity, their first challenge was to model the Sun’s activity over its entire lifetime. As mentioned previously, the primary cause for depletion of material from the lunar surface is from space weather events — most notably coronal mass ejections (CMEs), which occur when large volumes of material are ejected from the Sun during a solar eruption. A cartoon depicting this is shown in Figure 1.

rotation rates

Figure 1: Cartoon showing the relationship of solar rotation rate with the amount of material lost from the surface of the Moon. [Saxena et al. 2019]

The authors considered three rotation classes for their model of the early Sun: slow rotators, medium rotators, and fast rotators, which correspond to rotation rates observed for Sun-like stars in a previous study. To construct a flare/CME relation, they looked at data from both the Kepler Space Telescope and Earth’s geological record. The Kepler Space Telescope observed several Sun-like stars in a single patch of sky over the span of four years and was able to characterize the activity of Sun-like stars with respect to their rotation. An approximately linear flare–rotation relation was found, with faster rotators being more active than slow rotators. CMEs are also always associated with a flare, however not every flare produces a CME — especially at low energies. The authors consider only the most energetic flares, and therefore assume a 100% CME–flare association.

The authors’ fully constructed CME frequency for the entire Sun’s lifetime is shown in Figure 2. Regardless of initial rotation rate, all scenarios converge to the same CME/flare rate, as shown in the figure.

CME frequency vs. time

Figure 2: Plot showing CME frequency versus time for three initial solar rotation classes. Different colored lines indicate different flare energies over time from different data sources (Kepler and Earth’s geological record), while solid, dashed, and dotted lines indicate the fast, medium, and slow rotator model, respectively. [Saxena et al. 2019]

Moon Rocks Rock

With their model CME frequency history in hand, the authors could now dig deeper into how solar activity could have affected the present-day composition of the Moon. The Moon is a surprisingly ideal place study past solar activity due to the cataclysmic event that formed the Earth–Moon system.  The most widely accepted theory for our Moon’s formation involves a large Mars-sized object, Theia, which crashed into the primordial Earth some four billion years ago. At the time of the Moon’s formation, the Earth and Moon had the same surface composition, having been formed from the same mass of rock. Thanks to our thick atmosphere and magnetic field, Earth has been able to hold on to a lot of the material on its surface since its formation. The Moon, however, is far too small to have an atmosphere. Therefore, material on the surface is constantly being stripped off due to many factors, the most effective being space-weather events. To be able to accurately assess the difference between material on the Earth and Moon, the authors focused on two volatile elements on the lunar surface, sodium and potassium. These elements have moderately lower abundances on the Moon than on Earth, but they are abundant enough on the Moon to be accurately measured.

Based on the amount of sodium and potassium currently present on the Moon, the authors then determined how fast the Sun had to be rotating in order to account for the difference relative to the abundance on Earth. They found that a fast-rotating Sun would have depleted the Moon’s sodium and potassium far more than the present-day values suggest. For the medium rotator case, the authors found that this model would account for the present-day values of sodium, but the potassium values would not have lined up. That leaves the slow rotator model. An initially slowly rotating Sun would account for the difference of both sodium and potassium between the Moon and the Earth.

A Solar-System Scale Puzzle

Understanding the initial rotation rate of the Sun is necessary for understanding the evolution of planets in the inner solar system. Many other mechanisms were used to try to explain the degree of sodium and potassium depletion, namely the amount of exposed vs. buried material in the Moon’s surface, meteorite impacts, volcanism, and magnetism (both from the Earth and the Moon itself). However, none of them would fully account for the amount of depletion observed. In today’s work, the authors found that a slow rotator model for the Sun best explains the current amounts of volatile elements present on the surface of the Moon and puts yet another piece into the billions-year long puzzle of our solar system’s history.

About the author, Ellis Avallone:

I am a first-year graduate student at the University of Hawaii at Manoa Institute for Astronomy, where I study the Sun. My current research focuses on how the solar magnetic field triggers eruptions that can affect us here on Earth. In my free time I enjoy rock climbing, painting, and eating copious amounts of mac and cheese.

M80

Editor’s note: AAS Nova is on vacation this week. Normal posting will resume next week; in the meantime, we hope you enjoy this post from Astrobites, a graduate-student-run organization that digests astrophysical literature for undergraduate students. The original can be viewed at astrobites.org.

Title: New s-process Site in Rapidly-Rotating Massive Pop II Stars
Authors: Projjwal Banerjee, Alexander Heger, Yong-Zhong
First Author’s Institution: Indian Institute of Technology Palakkad, India; Shanghai Jiao Tong University, China
Status: Submitted to ApJ

One of the main goals of nuclear astrophysics is to understand and explain the composition of the universe. Starting out with hydrogen, helium, and a teeny bit of lithium, the universe evolved to have an entire periodic table worth of chemical elements. How did this happen? We know that stars and supernovae played a key role in this chemical enrichment. However, exactly how and where different elements are produced, and in what quantities, remains a topic of vigorous ongoing research. Heavy element nucleosynthesis is a key piece of this puzzle and has received a lot of attention recently in the context of neutron star mergers.

Heavy elements — i.e., elements heavier than iron — are mainly formed through the s-process and the r-process. The names describe the speed of the process relative to the decay time of the isotopes involved: s-process involves slow neutron capture and the r-process involves rapid neutron capture.

Although both these processes make roughly equal overall contributions to the total abundance of heavy elements, the s-process does not get the same hype as its cool twin, the r-process. This is partly due to the fact that the site of the r-process was a huge mystery until very recently, when neutron star mergers were identified as one of the sites where the process occurs. It still remains to be seen whether they are the only site of the r-process.

The s-process, on the other hand, is known to occur inside asymptotic giant branch (AGB) stars. This is the final stage of evolution for long-lived, low-mass stars between 1–3 solar masses. The AGB stars can produce elements up to 209Bi, forming what’s called the “main” component of the s-process. However, a weaker version of the s-process also happens in massive stars (>10 solar masses), producing elements up to atomic mass number A ~ 90. Today’s paper shakes things up by introducing a new site for the main s-process: in rotating metal-poor massive stars!

The authors find that above a critical rotation speed, massive metal-poor stars evolve in a quasi-chemically-homogeneous (QCH) manner. This means the stars are spinning so fast that the mixing caused by rotation becomes very efficient. At the end of core hydrogen-burning, which produces helium, these stars look like helium stars. We can see this in panel (a) of Figure 2. Now starts the story of the s-process, which goes like this:

  1. The star in the QCH state starts burning helium in the center, producing 12C. Its core becomes convective.
  2. The convective core grows in size. Some of the 12C is mixed outward into the radiative region of the star. In this region, there are still some protons present, along with the right thermodynamic conditions to allow 12C to react with protons. This produces 13C.
  3. Some 13C is mixed back into the convective He-burning core. In regions that are hot enough, 13C reacts efficiently with the 4He, producing oxygen, as well as neutrons. This leads to high neutron densities that allow the s-process to happen!

We can see this play out in panels (b) through (d) of Figure 1.

Figure 1. Isotopic composition of the star during different stages of its evolution. The y-axis gives the mass fraction of different isotopes and the x-axis indicates the mass coordinate, i.e., how much mass of the star we’re looking at as we move away from the center of the star. We can see the mass fraction of 13C growing as 12C gets mixed into and reacts with protons in the outer layers. This 13C gets mixed inward and reacts with 4He, producing both 16O and neutrons. [Banerjee et al. 2019]

In Figure 2, we can see the amount of heavy elements present during different stages of the star’s evolution. There is a clear and strong s-process pattern leading all the way up to the element lead!

Figure 2. Time evolution of the s-process yield pattern for a 25-solar-mass star. Number yields of heavy isotopes inside the star are plotted as functions of mass number. The different lines correspond to different stages in the star’s evolution. [Banerjee et al. 2019]

Apart from being interesting in its own right, this new site may also be important for explaining the abundance patterns seen in very metal-poor (VMP) stars. These are old stars thought to reflect the composition of the interstellar medium at  ~1 Gyr after the Big Bang. This is much too early for low-mass stars to contribute any s-process elements (they evolve slowly), implying that the heavy-element abundances seen in VMP stars must come from the r-process. However, if a strong s-process is possible in massive stars as well, we cannot be so sure! Massive stars live fast and die young, which would allow for an earlier onset of s-process enrichment. Figure 3 shows s-process yield patterns from the authors’ calculations, compared to abundances observed in two VMP stars. The fits are quite good, presenting a potential explanation for VMP observations. 

Figure 3. Heavy-element abundances from this work compared to VMP stars. The abundances are from the wind ejecta (left) and the wind ejecta combined with outer stellar ejecta (right) for a 25-solar-mass star. The stars shown here are CEMP stars. The one on the left is a CEMP-s star while the one on the right is a CEMP-r/s star. [Adapted from Banerjee et al. 2019]

Of course, we should remember that this is an initial exploration of a new idea, though it seems promising. Stay tuned to see where the research leads!

About the author, Sanjana Curtis:

I’m a grad student at North Carolina State University. I’m interested in extreme astrophysical events like core-collapse supernovae and compact object mergers.

M101

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: Untangling the Galaxy I: Local Structure and Star Formation History of the Milky Way
Authors: Marina Kounkel, Kevin Covey
First Author’s Institution: Western Washington University
Status: Accepted to AJ

Despite our home planet being embedded in it, the Milky Way and its immediate environment remain an enigma to astronomy. Once thought to have few satellite neighbors, The Milky Way has been found to have many dwarf galaxies orbiting it. New stellar streams are being uncovered as well, likely remnants of past gravitational interactions with dwarf galaxies, in which the Milky Way pulled rivers of stars from its now-dissipated partners. This burst of discoveries of new nearby and entangled structures are thanks to advancements in technology allowing astronomers to observe dimmer objects and to track stars with greater precision.

Today’s paper utilizes one of these advancements, the much lauded Gaia mission, in tandem with machine learning methods to identify new substructures within the Milky Way and, in so doing, learn about its murky past.

Re-Clustering the Star Clusters

To begin, the authors are presented with the challenge of identifying stellar structures within the enormous Gaia dataset. In order to group stars together the authors use a clustering algorithm, which is a series of steps designed to isolate populations of objects with similar characteristics; the characteristics in question here are the stars’ coordinates within the Milky Way, their parallaxes, and their proper motions. A data sample of over 19 million stars are selected from the Gaia catalog, chosen to isolate stars for which the above characteristics are measured with high certainty. After much testing of the algorithmic parameters, the model returns over 1,900 star clusters, many of which have been independently identified in other studies. However, they also identify new structures that appear to have eluded other investigations (Figure 1).

star clusters on sky map

Figure 1: Map projection of the portion of the sky considered in today’s paper, with algorithm-identified star clusters marked in blue. Yellow markings indicate star clusters previously identified using different methods. Galactic coordinates are indicated with b and l. [Kounkel & Covey 2019]

In order to learn about our galaxy’s past, the authors must gain more information about these clusters to construct a star formation history. The star formation history of a galaxy is exactly what it sounds like: a combination of all star-forming events in a galaxy’s past that contribute to the current picture seen by astronomers. However, one can’t fully understand the history by only knowing the what and the where of star formation; also important is the when.

The authors determine the ages of their identified clusters testing two separate methods: analysis by a convolutional neural network (CNN) and isochrone fitting. Training the CNN using both known real clusters and a multitude of artificial ones, they only reproduce the accepted ages of clusters in 44% of cases. Similarly, using isochrones alone is only successful in a minority of cases. Using the CNN age estimate as an input to their isochrone model, however, increases the success rate to 77%, so this methodology is used to obtain ages for the remainder of the work.

Finding Loose Strings

While investigating the distribution of their identified star clusters, the authors noticed that they tended to be distributed in long, narrow structures. These strings, as the authors call them, are about 200 parsecs in length and lie parallel to the plane of the Milky Way. They appear similar to stellar streams, but are these simply new streams, or something new entirely? The answer lies in a peculiar trend noticed by the authors: although these strings act very similarly to normal clusters in terms of their motion, they are markedly younger than the population of clusters as a whole (Figure 2).

star cluster age distribution

Figure 2: Histogram of the age distribution of the star clusters (called “groups” here) compared to the strings. Notice how the distribution of string ages appears to have lower ages. [Kounkel & Covey 2019]

Now, one might intuitively think that the strings were formed by tidal stretching, i.e., that the stars formed in a roughly spherical cloud that was then stretched out by tidal interactions with other structures. However, many of the strings don’t show any evidence of a residual core of stars, leading the authors to conclude that they just formed this way. This interpretation is supported by previous observations of molecular filaments within the Milky Way, long string-like structures of the dense, molecular gas that is so crucial to forming stars. The authors suggest that the strings formed from these very same molecular filaments.

string subsample

Figure 3: 3D plot of a subsample of the strings, where the thick lines represent the “spine” of the string and the thin lines perpendicular to the spine indicate the velocities of the stellar components of the string. Color indicates age, and a redder string is a younger string. Check out an interactive version of this plot on the Dr. Kounkel’s website. [Kounkel & Covey 2019]

Further, analysis of the global distribution of strings (Figure 3) indicates that strings of different ages seem to lie close together, coagulating into four coherent streams of structure. Due to a correlation between the position of the youngest stream and the Local Arm of the Milky Way, the authors contend that these collections of strings may correspond to past star formation in old spiral arms within the Milky Way that have become less visible after losing their star-forming gas.

If so, deeper analysis of these strings might provide a way of studying the past structure and star formation history of our home galaxy.

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.

Centaurus A

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

Title: Positive and Negative Feedback of AGN Outflows in NGC 5728
Authors: Jaejin Shin, Jong-Hak Woo, Aeree Chung, Junhyun Baek, Kyuhyoun Cho, Daeun Kang, Hyun-Jin Bae
First Author’s Institution: Seoul National University, Republic of Korea
Status: Accepted to ApJ

One of the many mysteries of galaxy evolution is how the formation of stars is affected by a process called feedback. Unlike comments coming from a teacher on an essay, in the galactic context, feedback is coming from powerful sources of energy such as active galactic nuclei (AGN). Star formation in galaxies requires a lot of dense gas (also called the interstellar medium, or ISM), so any feedback processes that disrupt the presence or the denseness of said gas can affect the ability of a galaxy to form stars. Simulations have shown that AGN are theoretically capable of providing negative feedback by heating up the ISM or blowing it away. However, they might also provide positive feedback by compressing the ISM with their winds, making it denser and triggering bursts of star formation.

Each of these options have theoretical merit and are observed in simulations, but it can be hard to observe the effects in the wild. Today’s paper takes advantage of a particularly well-situated Seyfert 2 galaxy, NGC 5728, to enhance our understanding of AGN feedback processes. The Seyfert 2 designation is used to describe galaxies containing AGN that are similar to quasars, but that have visible host galaxies while most quasars do not.

Positive Feedback from Outflows?

The authors use observations of NGC 5728 in the optical wavelength range, the range visible to humans, to target light from stars and several emission lines generated by ionized (i.e. heated) gas. Targeting emission from a molecular transition (the carbon monoxide CO (J=2–1) transition, to be specific) also helped them trace out the distribution of molecular gas within NGC 5728, which is useful for examining how much material is available to form stars.

NGC 5728 Halpha

Figure 1: Emission map of NGC 5728 in hydrogen alpha, where the color indicates the amount of flux in a given pixel. The position of a star-forming ring and spiral arms are noted with grey dashed lines, while a biconical outflow is traced in white dashed lines. Note the black square, region A, that indicates an intersection between the AGN outflow and the star-forming ring. [Shin et al. 2019]

From these observations, the authors noted a few prominent structures. First, there are two spiral arms (only faintly visible in Figure 1). Second, there is a ring of star formation about 1 kiloparsec from the center. Lastly, there are prominent biconical outflows made up of ionized gas and full of high-energy radiation, like X-rays. Most importantly, there is an apparent intersection (labeled “A” in the figure) between the star forming ring and the northwest (i.e. the upper right in Figure 1) cone of the AGN outflow. Luckily, this intersection provides an ideal scenario for testing whether the AGN is helping or hindering star formation.

The authors define three other regions in the star forming ring (B, C, and D in Figure 2) that are located well away from the northwest biconical outflow, and can therefore serve as controls when looking for peculiarities in the star-forming characteristics of region A. Using a BPT diagram, the authors were able to calculate the percentage of flux contributed by stars in each pixel of the image and from this calculate the star formation rate in their selected regions.

AGN fraction

Figure 2: Fraction of emission in each pixel from AGN contributions (take 1 minus the AGN fraction to find the stellar contribution). A very blue color corresponds to a low AGN fraction, and thus a pixel containing gas whose hydrogen-alpha emission is dominated by stellar light. [Shin et al. 2019]

While region A has more solar masses of stars formed per year than the combined average of regions A–D, it is not particularly unusual in this respect. However, the brightness of the emission from molecular gas at region A is quite low compared to the other regions, meaning that it has an unusually high star formation efficiency (Figure 3). Indeed, it is a factor of 3–5 higher in star formation efficiency than the control regions — a significant difference! This result seems to indicate that the presence of the AGN feedback had a positive influence on the star formation, boosting it significantly and consuming a large amount of molecular gas.

star formation efficiency

Figure 3: The star formation efficiency of the galaxy, which is the ratio between the star formation rate and the available mass of molecular gas to form stars. [Adapted from Shin et al. 2019]

This seems like a pretty good indicator that an AGN should always significantly alter a galaxy’s star forming ability, right? Not quite! While this factor of 3–5 appears pretty large, when comparing to the calculated star formation rate in the entire galaxy, region A only accounts for a miniscule <10% of the total.

The jury is still out, then, on whether AGN will invariably cause galaxies to have significantly different star formation rates. This scenario is even further complicated by the fact that the biconical outflows may be simultaneously expelling accreted molecular gas from the spiral arms of the galaxy, preventing star formation from occurring there. Regardless, NGC 5728 is providing a rich test case to examine theories of AGN feedback and star formation.

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.

gas-giant transit

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 Intrinsic Temperature and Radiative-Convective Boundary Depth in the Atmospheres of Hot Jupiters
Authors: Daniel P. Thorngren, Peter Gao, Jonathan J. Fortney
First Author’s Institution: University of California, Santa Cruz
Status: Submitted to ApJL

HAT-P-7b

Artist’s impression of HAT-P-7b, an inflated hot Jupiter. [NASA, ESA, and G. Bacon (STScI)]

Jupiter-sized gas-giant exoplanets in close orbits around their stars, commonly referred to as hot Jupiters, have been the prime targets for probing planetary atmospheres beyond our solar system. One of the many mystifying features of hot Jupiters — which, ironically, also makes them easier to detect and characterize — is their inflated radii. A good fraction of known hot Jupiters have sizes larger than those predicted by evolutionary models that take into account the properties of the system like temperature, age, and metallicity of the system. What could be causing these hot Jupiters to puff up?

A proposed mechanism to explain hot-Jupiter inflation is deposition of energy from stellar irradiation deep into the interiors of the planet. However, in addition to inflating the planet, energy from stellar flux heating up the planetary interiors can also radically alter the thermal structure (temperature variation with altitude) of its atmosphere which has direct consequences on its inferred atmospheric properties. Today’s paper attempts to draw a connection between the stellar irradiation of hot Jupiters and their intrinsic temperature, and how that ultimately affects the observations and our understanding of the atmospheres of these gas giants.

Structuring the Atmosphere of a Gas Giant

The vertical thermal structure — also referred to as the pressure–temperature profile — of a planetary atmosphere is directly related to change in the mode of heat transport (radiation or convection) within the atmosphere at different heights. You can think of this in the context of the Earth’s atmosphere: closer to the surface heat exchange occurs through convection, with hot parcels of air rising up and adiabatically expanding and cooling. This causes the temperature to steadily decrease as you go up until a certain altitude called the tropopause; above this you hit the stratosphere, where the air absorbs most of the heat from ultraviolet radiation from the Sun, causing the temperature to now increase with altitude. Even before this happens convection begins to weaken considerably and radiation takes over as the dominant mode of heat exchange. The altitude or the pressure level at which this happens is called the radiative-convective boundary (RCB; see Figure 1 for example). Such stratification of atmospheres is very commonly seen in planetary atmospheres in the solar system and has been studied extensively from measurements by probes like Galileo and Cassini-Huygens.

hot Jupiter profiles

Figure 1: Pressure-temperature profiles for hot Jupiters at different distances from a Sun-like star, and hence different equilibrium temperatures (Teq). Note that on y-axis, the pressure decreases as you go up, corresponding to going higher up in the atmosphere. The thick parts of the profiles mark the regions of the atmosphere that are convective, and you can see how the radiative–convective equilibrium boundary moves to lower pressures for hotter planets. [Thorngren et al. 2019]

Determining the height of the RCB for gas-giant atmospheres requires an understanding of the heat flux from the planetary interiors, which can be described by the planet’s effective intrinsic temperature (Tint). To give you an idea of the numbers, Jupiter with Tint ~ 100 K has an RCB around the height corresponding to the pressure of 0.2 bars (1 bar = pressure at sea level on Earth). In the case of hot Jupiters, on the other hand — which, given their proximity to the star, receive radiation of thousands of times that received by Jupiter — the atmosphere remains radiative to a much greater depth. Here the RCB can be expected to lie much deeper, at pressures of around 1 kilobar (remember pressure increases with depth). However, this is a good estimate only if you assume Tint ~ 100 K for hot Jupiters as well. As mentioned before, observed radii inflation of hot Jupiters points toward possible heating of their interiors by stellar irradiation (the strength of which is reflected by the equilibrium temperature of the planet Teq). This implies that hot Jupiters can have much higher Tint, which would push the region of convection and hence the RCB to larger altitudes (lower pressures). Since Tint and Teq both affect the height of the RCB, and Tint also depends on Teq, at what height should we expect the RCB for a hot Jupiter with a given Teq?

To answer this question, the authors calculate temperature–pressure profiles from thermal equilibrium atmospheric models of archetypal hot Jupiters with a range of Teq, and they then investigate how the height of the RCB changes with respect to different levels of stellar irradiation (see Figure 1 and 2).

Marking the Boundary

As is evident from Figure 1, the RCB moves to lower pressures (larger altitudes) with higher Teq, similar to how Tint increases with Teq. The surface gravity and metallicity of the planet also affect the RCB height, as seen in Figure 2.

RCB pressure vs Teq

Figure 2: The RCB pressure level with respect to the Teq of the planet, as calculated for different surface gravities and metallicities of the planet. Note that the RCB ends up at higher pressures for higher surface gravity and lower pressures for higher metallicity. [Thorngren et al. 2019]

The variation of RCB height and Tint with respect to Teq of the planet has several significant implications for models and observations of hot Jupiters. When the RCB lies at lower pressures (larger altitudes), this implies that more heat can now be deposited into the convective region of the atmosphere from stellar irradiation, allowing the mechanism of Ohmic dissipation to be even more efficient at inflating the planet. A higher Tint (of the order of few 100 K) would also affect predictions of day–night energy transport and atmospheric circulation predicted by global circulation models. It would also mean that phase curve observations of some hot Jupiters might be able to probe flux from this intrinsic heat of the planet. Moreover, higher Tint means that cloud condensation will occur much higher up in the atmosphere, affecting the observed emission from the day side of the planet.

With more exoplanet discoveries from TESS and exoplanet characterization opportunities from JWST on the horizon, we can hope to obtain a stronger constraint on atmospheric boundary conditions such as these, which would be important for accurate interpretations of exoplanet atmosphere observations.

About the author, Vatsal Panwar:

I am a PhD student at the Anton Pannekoek Institute for Astronomy, University of Amsterdam. I work on characterization of exoplanet atmospheres to understand the diversity and origins of planetary systems. I also enjoy yoga, Lindyhop, and pushing my culinary boundaries every weekend.

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