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Astrophysics of Red Supergiants

Latest AAS Nova Highlights - Wed, 2018-01-03 12:00

The American Astronomical Society recently launched a new partnership with IOP to produce a series of ebooks about astronomy and astrophysics. The first book in this line, Astrophysics of Red Supergiants, is authored by Dr. Emily Levesque, assistant professor in the astronomy department at the University of Washington, and it’s now available for download with an institutional IOP ebook subscription.

What is Astrophysics of Red Supergiants about, and why might you want to check it out? Dr. Levesque held a webinar last month (which was recorded and can be accessed here) to share more about the content of her new ebook.

What is a Red Supergiant?

A red supergiant occurs when a moderately massive star — perhaps 8–40 solar masses in size — exhausts its hydrogen fuel, evolves off of the main sequence, and transitions to fusing helium within its core. As this occurs, the star’s radius expands, causing its temperature to plummet. Red supergiants are among the coldest and most physically massive stars known.

Why Do We Care About Red Supergiants?

Studying red supergiants can help us to expand our knowledge in a broad range of astrophysical fields. This includes:

  1. Gravitational waves
    The colliding neutron stars that produce gravitational waves likely evolved from red supergiants in binaries. We can therefore use such mergers to learn about red supergiants in the final stages of their lives — as well as use what we know about red supergiants to constrain expected gravitational wave signals.
  2. Supernovae
    Red supergiants are the progenitors that produce some types of supernovae. For this reason, it’s critical that we understand red supergiant evolution so that we can better model the moments leading up to supernova explosion, and better interpret pre-explosion observations of supernovae.
  3. Strange and variable stars
    Many red supergiants show photometric and spectroscopic variability, and we’re still working to understand why. The long list of possible mechanisms that produce variability includes large-scale convection, radial pulsation, sporadic mass loss, changes in the amount and distribution of circumstellar dust, hydrostatic instabilities, and binary companions (which can produce variability via eclipses, mass transfer, wind interactions, etc.). There may also be new physics that we don’t yet know about!

Cover of the new AAS/IOP ebook by Dr. Emily Levesque, Astrophysics of Red Supergiants.

What Can You Learn from Astrophysics of Red Supergiants?

Dr. Levesque’s compact book — only 100 pages long — is written at an advanced graduate-student level and provides a complete primer on the current state of red supergiant astronomy. Chapters in the book include:

  • An Introduction to Red Supergiants
  • Inside a Red Supergiant
  • Physical Properties of Red Supergiants
  • Mass Loss and Dust Production in Red Supergiants
  • Red Supergiants in Binaries
  • Red Supergiants in and beyond the Milky Way
  • Variability in Red Supergiants
  • Red Supergiants and Supernovae
  • The Future of Red Supergiant Research
More Information

Astrophysics of Red Supergiants ebook download:

Dr. Levesque’s webinar:

If you plan to be at AAS 231, come by to meet Dr. Levesque and celebrate the launch of the new AAS/IOP ebook series with us at the AAS booth (#315) on Wednesday, 10 January at 5:30 p.m. during the poster session!

To learn more about the new AAS/IOP ebook partnership and current and upcoming titles, visit

How Fast Is Dark Matter?

Latest AAS Nova Highlights - Tue, 2018-01-02 12:00

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

Title: Empirical Determination of Dark Matter Velocities using Metal-Poor Stars
Authors: Jonah Herzog-Arbeitman, Mariangela Lisanti, Piero Madau, Lina Necib
First Author’s Institution: Princeton University
Status: Submitted to ApJL

Our galaxy is embedded in a cloud of dark matter, thought to consist of tiny particles traveling along orbits through the halo. These dark matter particles permeate all regions of the galaxy, extending far beyond the edge of the bright central spiral, but also orbiting through our solar system, and even passing right through the Earth. This is why scientists build giant detectors, hoping to trap some of these dark matter particles as they pass by. So far, these experiments have not detected dark matter, but that lack of detection is actually quite interesting. Finding out what dark matter is not, and thereby narrowing down the possibilities, is an important step towards revealing the true nature of these mysterious particles.

In order to really understand what it means when a detecter does not see dark matter, it is important to have a clear prediction for how much dark matter should be detected. For example, if we expect very few dark matter particles to pass through the Earth in a given amount of time, then maybe the lack of detections over a few years doesn’t actually mean those particles don’t exist. One essential piece of information in this prediction is the velocity of dark matter particles as they orbit past our solar system.

So, how can we determine the speed of these particles that we haven’t even directly detected? Well, let’s look back at where these particles actually come from. Dark matter halos grow over time by consuming other dark matter halos. This process is called hierarchical structure formation. The Milky Way is continuously pulling in smaller galaxies and then tearing them apart, thoroughly mixing their stars and dark matter particles into the Milky Way halo (Figure 1).

This understanding of the origin of these particles reveals an important piece of information: when dark matter particles join the Milky Way, they are often accompanied by stars. This is great news, because stars, unlike dark matter particles, are not invisible, and we can directly measure their velocities. If we can confirm that dark matter particles tend to move at similar velocities to their stellar companions, then this problem of determining the local dark matter velocity is much simpler! Finding out if this is in fact the case is exactly the goal of today’s paper.

The tricky thing here is that the Milky Way is continuously forming new stars, so the authors need to find a way to distinguish between the stars formed within the Milky Way and stars that formed in smaller galaxies and were then consumed by the Milky Way along with the corresponding dark matter. This turns out to be fairly straightforward: stars that form in smaller galaxies tend to have a different chemical composition than stars that are currently being formed in the Milky Way. This is because Milky Way stars are forming from materials that have been enriched with heavier elements by generations of star formation, while the stars in smaller galaxies are not. The stars we are interested in are therefore what astronomers call “metal-poor.” The prediction is therefore that metal-poor stars and dark matter particles should have similar velocities.

Figure 2. A simulated Milky Way-like galaxy, from the ERIS simulation used in this paper. [Simone Callegari]

The authors use simulations of Milky Way-like galaxies (Figure 2) to compare the velocities of dark matter and stars, and find that this prediction holds up! Figure 3 shows the distributions of velocities for dark matter and different stellar populations. The black histogram is dark matter, the cyan histogram is all stars, and the orange histogram is only metal-poor stars. The black and orange histograms line up pretty well, meaning the velocity of metal-poor stars does tend to match that of the dark matter. This means that by observing the velocities of these stars near the Sun, we can improve our understanding of the dark matter velocity. This will improve our interpretation of the results of dark matter experiments. In particular, based on preliminary calculations, the authors show that the velocity is lower than previously thought. They suggest that this may weaken the significance of non-detections at smaller dark matter particle masses.

Figure 3. Velocity histograms of different components of the Milky Way, as seen in the ERIS simulation. The black histogram shows the velocity distribution of dark matter. The cyan histogram illustrates the velocity of all stars, and has a much larger central peak than the dark matter distribution. The orange histogram, however, which includes only metal-poor stars, is very similar to the dark matter velocity distribution. [Herzog-Arbeitman et al. 2018]

This is a really exciting result. Previous estimates of the dark matter velocity all came from simulations and theoretical predictions, so this new method, which uses observations of our actual galaxy, rather than a simplified model, should really improve the accuracy of these calculations. Furthermore, current experiments like Gaia are greatly improving our understanding of the local stellar velocity distribution, which will continue to increase the power of this method to determine the local dark matter velocity.

About the author, Nora Shipp:

I am a 2nd year grad student at the University of Chicago. I work on combining simulations and observations to learn about the Milky Way and dark matter.

Selections from 2017: The Age of a 4-Star System

Latest AAS Nova Highlights - Fri, 2017-12-29 12:00

Editor’s note: In these last two weeks of 2017, we’ll be looking at a few selections that we haven’t yet discussed on AAS Nova from among the most-downloaded papers published in AAS journals this year. The usual posting schedule will resume in January.

The Age of the KIC 7177553 System Published January 2017


Main takeaway:

Two scientists from the University of Delaware, James MacDonald and Dermott Mullan, recently derived the age of the quadruple star system KIC 7177553. The system appears to be younger than originally thought — it’s best modeled as being 32–36 million years old.

Based on stellar models and the observed radii of the stars, their ages are likely between 32 and 36 million years. [MacDonald & Mullan et al. 2017]

Why it’s interesting:

The KIC 7177553 system is intriguing because of its complex structure: it consists of two binaries (one of which is eclipsing) orbiting each other in a hierarchical structure. Observations of KIC 7177553 can teach us how hierarchical systems like this one form and evolve, but first we need to determine how old the system is so we know what stage of its evolution we’re seeing. The authors’ estimate of 32–36 million years is relatively young for stars; this age places them in the pre-main-sequence phase.

The additional intrigue of KIC 7177553:

KIC 7177553 is of further interest to astronomers because it might host a super-Jupiter-sized planet in an eccentric orbit around the system. If true, this system may provide an excellent opportunity to learn more about how planets in hierarchical star systems are born and evolve. Having an accurate determination of the age of the system is therefore especially important so that we can constrain possible planet formation scenarios.


James MacDonald and D. J. Mullan 2017 ApJ 834 99. doi:10.3847/1538-4357/834/2/99

Selections from 2017: Hubble Survey Explores Distant Galaxies

Latest AAS Nova Highlights - Thu, 2017-12-28 12:00

Editor’s note: In these last two weeks of 2017, we’ll be looking at a few selections that we haven’t yet discussed on AAS Nova from among the most-downloaded papers published in AAS journals this year. The usual posting schedule will resume in January.

CANDELS Multi-Wavelength Catalogs: Source Identification and Photometry in the CANDELS COSMOS Survey Field Published January 2017


Main takeaway:

A publication led by Hooshang Nayyeri (UC Irvine and UC Riverside) early this year details a catalog of sources built using the Cosmic Assembly Near-infrared Deep Extragalactic Legacy Survey (CANDELS), a survey carried out by cameras on board the Hubble Space Telescope. The catalog lists the properties of ~38,000 distant galaxies visible within the COSMOS field, a two-square-degree equatorial field explored in depth to answer cosmological questions.

Why it’s interesting:

Illustration showing the three-dimensional map of the dark matter distribution in the
COSMOS field. [Adapted from NASA/ESA/R. Massey
(California Institute of Technology)]

The depth and resolution of the CANDELS observations are useful for addressing several major science goals, including the following:

  1. Studying the most distant objects in the universe at the epoch of reionization in the cosmic dawn.
  2. Understanding galaxy formation and evolution during the peak epoch of star formation in the cosmic high noon.
  3. Studying star formation from deep ultraviolet observations and studying cosmology from supernova observations.
Why CANDELS is a major endeavor:

CANDELS is the largest multi-cycle treasury program ever approved on the Hubble Space Telescope — using over 900 orbits between 2010 and 2013 with two cameras on board the spacecraft to study galaxy formation and evolution throughout cosmic time. The CANDELS images are all publicly available, and the new catalog represents an enormous source of information about distant objects in our universe.


H. Nayyeri et al 2017 ApJS 228 7. doi:10.3847/1538-4365/228/1/7

Selections from 2017: Discoveries in Titan’s Atmosphere

Latest AAS Nova Highlights - Wed, 2017-12-27 12:00

Editor’s note: In these last two weeks of 2017, we’ll be looking at a few selections that we haven’t yet discussed on AAS Nova from among the most-downloaded papers published in AAS journals this year. The usual posting schedule will resume in January.

Carbon Chain Anions and the Growth of Complex Organic Molecules in Titan’s Ionosphere Published July 2017


Main takeaway:

Graphic depicting some of the chemical reactions taking place in Titan’s atmosphere, leading to the generation of organic haze particles. [ESA]

In a recently published study led by Ravi Desai (University College London), scientists used data from the Cassini mission to identify negatively charged molecules known as “carbon chain anions” in the atmosphere of Saturn’s largest moon, Titan.

Why it’s interesting:

Carbon chain anions are the building blocks of more complex molecules, and Titan’s thick nitrogen and methane atmosphere might mimic the atmosphere of early Earth. This first unambiguous detection of carbon chain anions in a planet-like atmosphere might therefore teach us about the conditions and chemical reactions that eventually led to the development of life on Earth. And if we can use Titan to learn about how complex molecules grow from these anion chains, we may be able to identify a universal pathway towards the ingredients for life.

What we’ve learned so far:

Cassini measured fewer and fewer lower-mass anions the deeper in Titan’s ionosphere that it looked — and at the same time, an increase in the number of precursors to larger aerosol molecules further down. This tradeoff strongly suggests that the anions are indeed involved in building up the more complex molecules, seeding their eventual growth into the complex organic haze of Titan’s lower atmosphere.


R. T. Desai et al 2017 ApJL 844 L18. doi:10.3847/2041-8213/aa7851

Selections from 2017: Image Processing with AstroImageJ

Latest AAS Nova Highlights - Tue, 2017-12-26 12:00

Editor’s note: In these last two weeks of 2017, we’ll be looking at a few selections that we haven’t yet discussed on AAS Nova from among the most-downloaded papers published in AAS journals this year. The usual posting schedule will resume in January.

AstroImageJ: Image Processing and Photometric Extraction for Ultra-Precise Astronomical Light Curves Published January 2017


The AIJ image display. A wide range of astronomy specific image display options and image analysis tools are available from the menus, quick access icons, and interactive histogram. [Collins et al. 2017]

Main takeaway:

AstroImageJ is a new integrated software package presented in a publication led by Karen Collins (Vanderbilt University, Fisk University, and University of Louisville). It enables new users — even at the level of undergraduate student, high school student, or amateur astronomer — to quickly start processing, modeling, and plotting astronomical image data.

Why it’s interesting:

Science doesn’t just happen the moment a telescope captures a picture of a distant object. Instead, astronomical images must first be carefully processed to clean up the data, and this data must then be systematically analyzed to learn about the objects within it. AstroImageJ — as a GUI-driven, easily installed, public-domain tool — is a uniquely accessible tool for this processing and analysis, allowing even non-specialist users to explore and visualize astronomical data.

Some features of AstroImageJ:

(as reported by Astrobites)

  • Image calibration: generate master flat, dark, and bias frames
  • Image arithmetic: combine images via subtraction, addition, division, multiplication, etc.
  • Stack editing: easily perform operations on a series of images
  • Image stabilization and image alignment features
  • Precise coordinate converters: calculate Heliocentric and Barycentric Julian Dates
  • WCS coordinates: determine precisely where a telescope was pointed for an image by PlateSolving using
  • Macro and plugin support: write your own macros
  • Multi-aperture photometry with interactive light curve fitting: plot light curves of a star in real time

Karen A. Collins et al 2017 AJ 153 77. doi:10.3847/1538-3881/153/2/77

Selections from 2017: Atmosphere Around an Earth-Like Planet

Latest AAS Nova Highlights - Thu, 2017-12-21 12:00

Editor’s note: In these last two weeks of 2017, we’ll be looking at a few selections that we haven’t yet discussed on AAS Nova from among the most-downloaded papers published in AAS journals this year. The usual posting schedule will resume in January.

Detection of the Atmosphere of the 1.6 M ⊕ Exoplanet GJ 1132 b Published March 2017


Main takeaway:

An atmosphere was detected around the roughly Earth-size exoplanet GJ 1132 b using a telescope at the European Southern Observatory in Chile. A team of scientists led by John Southworth (Keele University) found features indicating the presence of an atmosphere in the observations of this 1.6-Earth-mass planet as it transits an M-dwarf host star. This is the lowest-mass planet with a detected atmosphere thus far.

Why it’s interesting:

M dwarfs are among the most common stars in our galaxy, and we’ve found many Earth-size exoplanets in or near the habitable zones around M-dwarf hosts. But M dwarfs are also more magnetically active than stars like our Sun, suggesting that the planets in M-dwarf habitable zones may not be able to support life due to stellar activity eroding their atmospheres. The detection of an atmosphere around GJ 1132 b suggests that some planets orbiting M dwarfs are able to retain their atmospheres — which means that these planets may be an interesting place to search for life after all.

How the atmosphere was detected:

The measured planetary radius for GJ 1132 b as a function of the wavelength used to observe it. [Southworth et al. 2017]

When measuring the radius of GJ 1132 b based on its transits, the authors noticed that the planet appeared to be larger when observed in some wavelengths than in others. This can be explained if the planet has a “surface radius” of ~1.4 Earth radii, overlaid by an atmosphere that extends out another few tenths of an Earth radius. The atmosphere, which may consist of water vapor or methane, is transparent to some wavelengths and absorbs others — which is why the apparent size of the planet changes across wavelength bands.


John Southworth et al 2017 AJ 153 191. doi:10.3847/1538-3881/aa6477

Selections from 2017: Mapping the Universe with SDSS IV

Latest AAS Nova Highlights - Wed, 2017-12-20 12:00

Editor’s note: In these last two weeks of 2017, we’ll be looking at a few selections that we haven’t yet discussed on AAS Nova from among the most-downloaded papers published in AAS journals this year. The usual posting schedule will resume in January.

Sloan Digital Sky Survey IV: Mapping the Milky Way, Nearby Galaxies, and the Distant Universe Published June 2017


Main takeaway:

The incredibly prolific Sloan Digital Sky Survey has provided photometric observations of around 500 million objects and spectra for more than 3 million objects. The survey has now entered its fourth iteration, SDSS IV, with the first public data release made in June 2016. A publication led by Michael Blanton (New York University) describes the facilities used for SDSS IV, its science goals, and its three core programs.

Why it’s interesting:

Since data collection began in 2000, SDSS has been one of the premier surveys providing imaging and spectroscopy for objects in both the near and distant universe. SDSS has measured spectra not only for the stars in our own Milky Way, but also for galaxies that lie more than 7 billion light-years distant — making it an extremely useful and powerful tool for mapping our universe.

What SDSS IV is looking for:

SDSS image of an example MaNGA target galaxy (left), with some of the many things we can learn about it shown in the right and bottom panels: stellar velocity dispersion, stellar mean velocity, stellar population age, metallicity, etc. [Blanton et al. 2017]

SDSS IV contains three core programs:

  1. Apache Point Observatory Galactic Evolution Experiment 2 (APOGEE-2) provides high-resolution near-infrared spectra of hundreds of thousands of Milky-Way stars with the goal of improving our understanding of the history of the Milky Way and of stellar astrophysics.
  2. Mapping Nearby Galaxies at Apache Point Observatory (MaNGA) obtains spatially resolved spectra for thousands of nearby galaxies to better understand the evolutionary histories of galaxies and what regulates their star formation.
  3. Extended Baryon Oscillation Spectroscopic Survey (eBOSS) maps the galaxy, quasar, and neutral gas distributions at redshifts out to z = 3.5 to better understand dark matter, dark energy, the properties of neutrinos, and inflation.

Michael R. Blanton et al 2017 AJ 154 28. doi:10.3847/1538-3881/aa7567

Selections from 2017: Hostile Environment Around TRAPPIST-1

Latest AAS Nova Highlights - Tue, 2017-12-19 12:00

Editor’s note: In these last two weeks of 2017, we’ll be looking at a few selections that we haven’t yet discussed on AAS Nova from among the most-downloaded papers published in AAS journals this year. The usual posting schedule will resume in January.

The Threatening Magnetic and Plasma Environment of the TRAPPIST-1 Planets Published July 2017


Main takeaway:

Models of the magnetic environment surrounding the seven planets of the TRAPPIST-1 system suggest that this is not a pleasant place to be for life. In particular, the simulations run by Cecilia Garraffo (Harvard-Smithsonian Center for Astrophysics) and collaborators indicate that all planets in the system are bombarded by a stellar wind with a pressure that’s 1,000 to 100,000 times the pressure of what we experience on Earth.

Why it’s interesting:

Simulations of the magnetic environment around the planet TRAPPIST-1 f, for a variety of different assumed planetary magnetic fields. Red field lines are those that have connected between the star and the planet. [Garraffo et al. 2017]

The discovery of seven Earth-sized planets in the nearby TRAPPIST-1 system — particularly given many of the planets’ apparent location in the star’s habitable zone — gave us hope that these planets might be an interesting place to look for life. But the issue of habitability is more complicated than whether or not the planets can support liquid water. Garraffo and collaborators’ models suggest that these planets likely have their atmospheres eroded or completely stripped by the stellar wind, rendering prospects for life on these planets low.

Why the TRAPPIST-1 system is still awesome:

We may be bummed that the magnetically active host star impedes chances for life on the TRAPPIST-1 planets, but the environment it produces is still pretty awesome. According to the authors’ models, the planets pass through wildly changing wind pressure changes as they orbit. In the process, their magnetospheres are compressed, and their magnetic field lines connect with the stellar field lines over much of the planets’ surfaces, causing the stellar wind particles to funnel directly onto the planets’ atmospheres. The result is an exciting and dynamic environment definitely worth studying further.


Cecilia Garraffo et al 2017 ApJL 843 L33. doi:10.3847/2041-8213/aa79ed

Selections from 2017: Computers Help Us Map Our Home

Latest AAS Nova Highlights - Mon, 2017-12-18 12:00

Editor’s note: In these last two weeks of 2017, we’ll be looking at a few selections that we haven’t yet discussed on AAS Nova from among the most-downloaded papers published in AAS journals this year. The usual posting schedule will resume in January.

Machine-Learned Identification of RR Lyrae Stars from Sparse, Multi-Band Data: The PS1 Sample Published April 2016


Main takeaway:

A sample of RR Lyrae variable stars was built from the Pan-STARRS1 (PS1) survey by a team led by Branimir Sesar (Max Planck Institute for Astronomy, Germany). The sample of 45,000 stars represents the widest (three-fourths of the sky) and deepest (reaching 120 kpc) sample of RR Lyrae stars to date.

Why it’s interesting:

It’s challenging to understand the overall shape and behavior of our galaxy because we’re stuck on the inside of it. RR Lyrae stars are a useful tool for this purpose: they can be used as tracers to map out the Milky Way’s halo. The authors’ large sample of RR Lyrae stars from PS1 — combined with proper-motion measurements from Gaia and radial-velocity measurements from multi-object spectroscopic surveys — could become the premier source for studying the structure, kinematics, and the gravitational potential of our galaxy’s outskirts.

How they were found:

The black dots show the distribution of the 45,000 probable RR Lyrae stars in the authors’ sample. [Sesar et al. 2017]

The 45,000 stars in this sample were selected not by humans, but by computer. The authors used machine-learning algorithms to examine the light curves in the Pan-STARRS1 sample and identify the characteristic brightness variations of RR Lyrae stars lying in the galactic halo. These techniques resulted in a very pure and complete sample, and the authors suggest that this approach may translate well to other sparse, multi-band data sets — such as that from the upcoming Large Synoptic Survey Telescope (LSST) galactic plane sub-survey.


Branimir Sesar et al 2017 AJ 153 204. doi:10.3847/1538-3881/aa661b

More Planets in the Hyades Cluster

Latest AAS Nova Highlights - Fri, 2017-12-15 12:00

A few weeks ago, Astrobites reported on a Neptune-sized planet discovered orbiting a star in the Hyades cluster. A separate study submitted at the same time, however, reveals that there may be even more planets lurking in this system.

Thanks, Kepler

Artist’s impression of the Kepler spacecraft and the mapping of the fields of the current K2 mission. [NASA]

As we learn about the formation and evolution of planets outside of our own solar system, it’s important that we search for planets throughout different types of star clusters; observing both old and young clusters, for instance, can tell us about planets in different stages of their evolutionary histories. Luckily for us, we have a tool that has been doing exactly this: the Kepler mission.

In true holiday spirit, Kepler is the gift that just keeps on giving. Though two of its reaction wheels have failed, Kepler — now as its reincarnation, K2 — just keeps detecting more planet transits. What’s more, detailed analysis of past Kepler/K2 data with ever more powerful techniques — as well as the addition of high-precision parallaxes for stars from Gaia in the near future — ensures that the Kepler data set will continue to reveal new exoplanet transits for many years to come.

Image of the Hyades cluster, a star cluster that is only ~800 million years old. [NASA/ESA/STScI]

Hunting in the Young Hyades

Two studies using K2 data were recently submitted on exoplanet discoveries around EPIC 247589423 in the Hyades cluster, a nearby star cluster that is only 800 million years old. Astrobites reported on the first study in October and discussed details about the newly discovered mini-Neptune presented in that study.

The second study, led by Andrew Mann (University of Texas at Austin and NASA Hubble Fellow at Columbia University), was published this week. This study presented a slightly different outcome: the authors detect the presence of not just the one, but three exoplanets orbiting EPIC 247589423.

New Discoveries

Mann and collaborators searched through the K2 light curves of young stars as part of the ZEIT (Zodiacal Exoplanets in Time) Survey. Using these data, they identified the presence of three planets in the EPIC 247589423 system:

  1. a roughly Earth-sized planet (~1.0 Earth radii) with a period of ~8.0 days,
  2. the mini-Neptune identified in the other study, with a size of ~2.9 Earth radii and period of ~17 days, and
  3. a super-Earth, with a size of ~1.5 Earth radii and period of ~26 days.

Light curve of EPIC 247589423 from K2, with the lower panels showing the transits of the three discovered planets. [Mann et al. 2018]

The smallest planet is among the youngest Earth-sized planets ever discovered, allowing us a rare glimpse into the history and evolution of planets similar to our own.

But these planetary discoveries are additionally exciting because they’re orbiting a bright star that’s relatively quiet for its age — making the system an excellent target for dedicated radial-velocity observations to determine the planet masses.

Since most young star clusters are much further away, they lie out of range of radial-velocity follow-up, rendering EPIC 247589423 a unique opportunity to explore the properties of young planets in detail. With more discoveries like these from Kepler’s data, we can hope to soon learn more about planets in all their stages of evolution.


Andrew W. Mann et al 2018 AJ 155 4. doi:10.3847/1538-3881/aa9791

Star-Forming Clouds Feed, Churn, and Fall

Latest AAS Nova Highlights - Wed, 2017-12-13 12:00

Molecular clouds, the birthplaces of stars in galaxies throughout the universe, are complicated and dynamic environments. A new series of simulations has explored how these clouds form, grow, and collapse over their lifetimes.

This composite image shows part of the Taurus Molecular Cloud. [ESO/APEX (MPIfR/ESO/OSO)/A. Hacar et al./Digitized Sky Survey]

Stellar Birthplaces

Molecular clouds form out of the matter in between stars, evolving through constant interactions with their turbulent environments. These interactions — taking the form of accretion flows and surface forces, while gravity, turbulence, and magnetic fields interplay — are thought to drive the properties and evolution of the clouds.

Our understanding of the details of this process, however, remains fuzzy.  How does mass accretion affect these clouds as they evolve? What happens when nearby supernova explosions blast the outsides of the clouds? What makes the clouds churn, producing the motion within them that prevents them from collapsing? The answers to these questions can tell us about the gas distributed throughout galaxies, revealing information about the environments in which stars form.

A still from the simulation results showing the broader population of molecular clouds that formed in the authors’ simulations, as well as zoom-in panels of three low-mass clouds tracked in high resolution. [Ibáñez-Mejía et al. 2017]

Models of Turbulence

In a new study led by Juan Ibáñez-Mejía (MPI Garching and Universities of Heidelberg and Cologne in Germany, and American Museum of Natural History), scientists have now explored these questions using a series of three-dimensional simulations of a population of molecular clouds forming and evolving in the turbulent interstellar medium.

The simulations take into account a whole host of physics, including the effects of nearby supernova explosions, self-gravitation, magnetic fields, diffuse heating, and radiative cooling. After looking at the behavior of the broader population of clouds, the authors zoom in and explore three clouds in high-resolution to learn more about the details.

Watching Clouds Evolve

Ibáñez-Mejía and collaborators find that mass accretion occurring after the molecular clouds form plays an important role in the clouds’ evolution, increasing the mass available to form stars and carrying kinetic energy into the cloud. The accretion process is driven both by background turbulent flows and gravitational attraction as the cloud draws in the gas in its nearby environment.

Plots of the cloud mass and radius (top) and mass accretion rate (bottom) for one of the three zoomed-in clouds, shown as a function of time over the 10-Myr simulation. [Adapted from Ibáñez-Mejía et al. 2017]

The simulations show that nearby supernovae have two opposing effects on a cloud. On one hand, the blast waves from supernovae compress the envelope of the cloud, increasing the instantaneous rate of accretion. On the other hand, the blast waves disrupt parts of the envelope and erode mass from the cloud’s surface, decreasing accretion overall. These events ensure that the mass accretion rate of molecular clouds is non-uniform, regularly punctuated by sporadic increases and decreases as the clouds are battered by nearby explosions.

Lastly, Ibáñez-Mejía and collaborators show that mass accretion alone isn’t enough to power the turbulent internal motions we observe inside molecular clouds. Instead, they conclude, the cloud motions must be primarily powered by gravitational potential energy being converted into kinetic energy as the cloud contracts.

The authors’ simulations therefore show that molecular clouds exist in a state of precarious balance, prevented from collapsing by internal turbulence driven by interactions with their environment and by their own contraction. These results give us an intriguing glimpse into the complex environments in which stars are born.


Check out the animated figure below, which displays how the clouds in the authors’ simulations evolve over the span of 10 million years.

Juan C. Ibáñez-Mejía et al 2017 ApJ 850 62. doi:10.3847/1538-4357/aa93fe

Hunting for the Faintest Galaxies

Latest AAS Nova Highlights - Tue, 2017-12-12 12:00

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

Title: Hunting Faint Dwarf Galaxies in the Field Using Integrated Light Surveys
Authors: S. Danieli, P. van Dokkum, C. Conroy
First Author’s Institution: Yale University
Status: Submitted to ApJ

One marvelous fact about our universe is that at the largest scales, it is fractal. Unlike true fractals, which exhibit exact self-similarity, the universe is only statistically self-similar. If you looked at the most massive objects in the universe, a record held by the gargantuan, invisible dark matter blobs holding clusters of galaxies together, which clock in with masses upwards of 1015 times the mass of the Sun, you’d find that they’re rife with smaller blobs, or “halos” of dark matter. Many of these smaller dark matter halos are inhabited by a galaxy, including giant bright elliptical galaxies, the smaller and fainter spiral galaxies, and hordes of yet smaller, fainter galaxies. Peering closer at, say, one of the dark matter halos of a Milky Way-like spiral galaxy, which clocks in at about 1012 times the mass of the Sun, you’d find that it in turn is surrounded by a similar but down-sized army of even smaller dark matter halos, which may contain even fainter “dwarf” galaxies. And the halos of each of these dwarf galaxies in turn can host their own army of even tinier dark matter halos. If you just looked at the dark matter of a galaxy cluster, a single spiral galaxy, or a dwarf galaxy, it would be hard to tell which was which — they would roughly look like scaled up (or down) versions of each other.

How far down does this fractal structure go? We can search part of the way down by searching for the smallest, faintest galaxies that live within them — which is an incredibly difficult task. To go further down to the smallest dark matter halos, which may be completely dark, and thus unobservable by usual means (i.e. by light), we’ll have to turn to more exotic methods. The faintest dwarf galaxies we’ve found thus far have been discovered by hunting for clusters, or “overdensities,” of stars. This technique can only uncover dwarfs in which we can observe individual stars, which we can distinguish only out to a pitiful distance — just to up to about 5 Mpc away, which is a little beyond the edge of the Local Group of neighborly galaxies.

What about the faint dwarfs that live even further away, far enough that they appear as fuzzy patches of light, and not as collections of stars? The authors of today’s paper discuss our prospects for finding these “integrated light” images of dwarfs (see Fig. 1) as far away as 10 Mpc. To do this, they set out to ask a simple question: how many galaxies could they find, given a telescope with a particular resolution and sensitivity?

Figure 1. Simulated observations of a faint dwarf galaxy at different distances from the Milky Way. If the dwarf is just outside the Milky Way, at about 500 kpc, we can see the individual stars within the galaxy. However, if such a galaxy is farther away, it becomes increasingly difficult to resolve individual stars. At 4 Mpc, it only appears as a fuzzy blob of light, and we can no longer see the individual stars in the galaxy. Detecting such faraway, faint dwarfs requires new search methods. [Danieli et al. 2017]

To carry out this calculation, the authors assume — for lack of data — that the faint galaxies as far as 10 Mpc look like the ones we’ve seen that are close by. Based on these nearby galaxies, they estimate how large and faint the distant dwarfs they’re searching for would be, then determine whether or not we could see them. They also estimate the mass in stars each of these faraway dwarfs have — a key quantity that allows them to guess the mass of the dark matter halos the dwarfs inhabit. It’s as yet unclear how much dark matter a galaxy with a given mass in stars has — a mapping we call the stellar mass-halo mass (SMHM) relation — so the authors adopt two different ones. With the dark matter mass of the dwarf galaxies, it’s simple enough to determine the number of such dwarfs that should exist out to 10 Mpc from simulations of the Milky Way and its surroundings.

Figure 2. The number of dwarfs between 3–10 Mpc that we could see with a telescope of a given resolution and sensitivity. The angular resolution is shown on the horizontal axis, and the sensitivity, here quantified as the surface brightness μ, is shown on the vertical axis. The colors and black contour lines denote the number of dwarfs you can see per square degree in the sky (an area equivalent to five times the Moon’s). The two panels show results from two different SMHM relations (see above paragraph for details). Brighter dwarf galaxies — those with smaller μ and thus at the bottom of the plots — can be seen no matter the resolution of your telescope. Fainter dwarfs — those with larger μ and higher up on the plot — are found in greater abundance, and we need good spatial resolution (fewer arcsecs) to detect them all. [Danieli et al. 2017]

The authors find (see Fig. 2) that, as you might expect, brighter dwarfs can be discovered no matter how good the resolution of your telescope is. However, when attempting to discover fainter dwarfs, the resolution really begins to matter. If, say, you had a telescope with a resolution of 9 arcsec versus one that was twice as good, you could detect up to six times as many of the faintest dwarfs. They also find that the SMHM they assume can affect the number of the faintest dwarfs they expect to find by as much as a factor of five.

The authors calculate that using this “integrated light” method to hunt for faint dwarfs using the Dragonfly Telescope Array, a telescope that was designed for the task, we could find a similar number of galaxies — if not more — as with surveys that rely on the traditional method of finding clusters of individually resolved stars. This is an exciting result. The few smallest, faintest galaxies we’ve found so far currently puzzle astronomers: how many of them are there? Why are they so faint? How did their stars form? We could begin to unravel these mysteries once we find more of these tiny galaxies.

About the author, Stacy Kim:

I am a fourth-year graduate student in The Ohio State University’s Department of Astronomy. On a day-to-day basis, you can typically find me attempting to smash clusters of galaxies together inside big supercomputers with Dr. Annika Peter to see if cluster mergers are good testbeds for dark matter collisionality. As an undergraduate at Caltech, I spent a few years chasing photons where planets are thought to form (or, as they say, performing Monte Carlo radiative transfer calculations of protoplanetary disks) with Dr. Neal Turner of the Jet Propulsion Laboratory. When I’m not sitting in front of a computer trying to translate cosmic thoughts into pithy lines of code, you can find me in the kitchen or on the walls of a climbing gym.

Featured Image: Making Dust in the Lab

Latest AAS Nova Highlights - Mon, 2017-12-11 12:00

This remarkable photograph (which spans only ~10 µm across; click for a full view) reveals what happens when you form dust grains in a laboratory under conditions similar to those of interstellar space. The cosmic life cycle of dust grains is not well understood — we know that in the interstellar medium (ISM), dust is destroyed at a higher rate than it is produced by stellar sources. Since the amount of dust in the ISM stays constant, however, there must be additional sources of dust production besides stars. A team of scientists led by Daniele Fulvio (Pontifical Catholic University of Rio de Janeiro and the Max Planck Institute for Astronomy at the Friedrich Schiller University Jena) have now studied formation mechanisms of dust grains in the lab by mimicking low-temperature ISM conditions and exploring how, under these conditions, carbonaceous materials condense from gas phase to form dust grains. To read more about their results and see additional images, check out the paper below.


Daniele Fulvio et al 2017 ApJS 233 14. doi:10.3847/1538-4365/aa9224

Which of Kepler’s Stars Flare?

Latest AAS Nova Highlights - Fri, 2017-12-08 12:00

The habitability of distant exoplanets is dependent upon many factors — one of which is the activity of their host stars. To learn about which stars are most likely to flare, a recent study examines tens of thousands of stellar flares observed by Kepler.

Need for a Broader Sample

Artist’s rendering of a flaring dwarf star. [NASA’s Goddard Space Flight Center/S. Wiessinger]

Most of our understanding of what causes a star to flare is based on observations of the only star near enough to examine in detail — the Sun. But in learning from a sample size of one, a challenge arises: we must determine which conclusions are unique to the Sun (or Sun-like stars), and which apply to other stellar types as well.

Based on observations and modeling, astronomers think that stellar flares result from the reconnection of magnetic field lines in a star’s outer atmosphere, the corona. The magnetic activity is thought to be driven by a dynamo caused by motions in the star’s convective zone.

HR diagram of the Kepler stars, with flaring main-sequence (yellow), giant (red) and A-star (green) stars in the authors’ sample indicated. [Van Doorsselaere et al. 2017]

To test whether these ideas are true generally, we need to understand what types of stars exhibit flares, and what stellar properties correlate with flaring activity. A team of scientists led by Tom Van Doorsselaere (KU Leuven, Belgium) has now used an enormous sample of flares observed by Kepler to explore these statistics.

Intriguing Trends

Van Doorsselaere and collaborators used a new automated flare detection and characterization algorithm to search through the raw light curves from Quarter 15 of the Kepler mission, building a sample of 16,850 flares on 6,662 stars. They then used these to study the dependence of the flare occurrence rate, duration, energy, and amplitude on the stellar spectral type and rotation period.

This large statistical study led the authors to several interesting conclusions, including:

  1. Flare star incidence rate as a a function of Rossby number, which traces stellar rotation. Higher rotation rates correspond to lower Rossby numbers, so these data indicate that more rapidly rotating stars are more likely to exhibit flares. [Van Doorsselaere et al. 2017]

    Roughly 3.5% of Kepler stars in this sample are flaring stars.
  2. 24 new A stars are found to show flaring activity. This is interesting because A stars aren’t thought to have an outer convective zone, which should prevent a magnetic dynamo from operating. Yet these flaring-star detections add to the body of evidence that at least some A stars do show magnetic activity.
  3. Most flaring stars in the sample are main-sequence stars, but 653 giants were found to have flaring activity. As with A stars, it’s unexpected that giant stars would have strong magnetic fields — their increase in size and gradual spin-down over time should result in weakening of the surface fields. Nevertheless, it seems that the flare incidence of giant stars is similar to that of F or G main-sequence stars.
  4. All stellar types appear to have a small fraction of “flare stars” — stars with an especially high rate of flare occurrence.
  5. Rapidly rotating stars are more likely to flare, tend to flare more often, and tend to have stronger flares than slowly rotating stars.

As a next step, the authors plan to apply their flare detection algorithm to the larger sample of all Kepler data. In the meantime, this study has both deepened a few mysteries and moved us a step closer in our understanding of which stars flare — and why.


Tom Van Doorsselaere et al 2017 ApJS 232 26. doi:10.3847/1538-4365/aa8f9a

Exploring Our Galaxy’s Thick Disk

Latest AAS Nova Highlights - Wed, 2017-12-06 12:00

What is the structure of the Milky Way’s disk, and how did it form? A new study uses giant stars to explore these questions.

A View from the Inside

Schematic showing an edge-on, not-to-scale view of what we think the Milky Way’s structure looks like. The thick disk is shown in yellow and the thin disk is shown in green. [Gaba p]

Spiral galaxies like ours are often observed to have disks consisting of two components: a thin disk that lies close to the galactic midplane, and a thick disk that extends above and below this. Past studies have suggested that the Milky Way’s disk hosts the same structure, but our position embedded in the Milky Way makes this difficult to confirm.

If we can measure the properties of a broad sample of distant tracer stars and use this to better understand the construction of the Milky Way’s disk, then we can start to ask additional questions — like, how did the disk components form? Formation pictures for the thick disk generally fall into two categories:

  1. Stars in the thick disk formed within the Milky Way — either in situ or by migrating to their current locations.
  2. Stars in the thick disk formed in satellite galaxies around the Milky Way and then accreted when the satellites were disrupted.

Scientists Chengdong Li and Gang Zhao (NAO Chinese Academy of Sciences, University of Chinese Academy of Sciences) have now used observations of giant stars — which can be detected out to great distances due to their brightness — to trace the properties of the Milky Way’s thick disk and address the question of its origin.

Best fits for the radial (top) and vertical (bottom) metallicity gradients of the thick-disk stars. [Adapted from Li & Zhao 2017]

Probing Origins

Li and Zhao used data from the Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST) in China to examine a sample of 35,000 giant stars. The authors sorted these stars into different disk components — halo, thin disk, and thick disk — based on their kinematic properties, and then explored how the orbital and chemical properties of these stars differed in the different components.

Li and Zhao found that the scale length for the thick disk is roughly the same as that of the thin disk (~3 kpc), i.e., both disk components extend out to the same radial distance. The scale height found for the thick disk is ~1 kpc, compared to the thin disk’s few hundred parsecs or so.

The metallicity of the thick-disk stars is roughly constant with radius; this could be a consequence of radial migration of the stars within the disk, which blurs any metallicity distribution that might have once been there. The metallicity of the stars decreases with distance above or below the galactic midplane, however — a result consistent with formation of the thick disk via heating or radial migration of stars formed within the galaxy.

Orbital eccentricity distribution for the thick-disk stars. [Li & Zhao 2017]

Further supporting these formation scenarios, the orbital eccentricities of the stars in the authors’ thick-disk sample indicate that they were born in the Milky Way, not accreted from disrupted satellites.

The authors acknowledge that the findings in this study may still be influenced by selection effects resulting from our viewpoint within our galaxy. Nonetheless, this is interesting new data to add to our understanding of the structure and origins of the Milky Way’s disk.


Chengdong Li and Gang Zhao 2017 ApJ 850 25. doi:10.3847/1538-4357/aa93f4

Planet Frequencies in the Galactic Bulge

Latest AAS Nova Highlights - Tue, 2017-12-05 12:00

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

Title: Towards a Galactic Distribution of Planets. I: Methodology & Planet Sensitivities of the 2015 High-Cadence Spitzer Microlens Sample
Authors: Wei Zhu, A. Udalski, S. Calchi Novati et al.
First Author’s Institution: Ohio State University
Status: Published in AJ

I don’t know if you’ve heard, but astronomers have found quite a few exoplanets in the last couple of decades. However, most of these are clustered in our tiny corner of the galaxy. For the 2,043 planets with stellar distance listed on today (yes, I know this article will be out of date in a week…) the average distance from to the host star from Earth is 624 pc. The center of the galaxy, meanwhile, is ~8,000 pc away. That’s further than even the furthest known exoplanet, OGLE-05-390L b, which is 6,500 pc from us.

And we’d really like to have a better understanding of the exoplanets in the galactic bulge, because their presence — or lack thereof — helps us to understand planet formation. Planet formation is believed to be affected by several external factors such as the host star’s metallicity, the stellar mass, the stellar multiplicity, and the stellar environment. That final category is what we’re going to consider today: does the presence of a large number of nearby stars interrupt the formation of planets? The galactic bulge, as the part of the galaxy with the highest number density of stars, is an ideal place to test this — if only we could detect enough planets out there…

OGLE telescope at the Las Campanas Observatory in Chile. [Krzysztof Ulaczyk]

Any readers particularly clued-up on exoplanet surveys might have recognised the phrase ‘OGLE’ in the name of planet ‘OGLE-05-390L b’. OGLE is the Optical Gravitational Lensing Experiment, a microlensing project run by Warsaw University. Although the mission was initially designed for dark-matter surveys, it has also made several serendipitous exoplanet discoveries. This astrobite describes microlensing for exoplanet detection in more detail, but for today all we really need to know is that sometimes nearby stars and distant stars happen to be really well aligned on the sky for a short time. In these cases, the nearby star’s gravity bends the light from the faraway star, causing it to be brighter for a short time; this is the process we call microlensing. If the nearby star also has a planet, which is also well aligned with the distant star, then the gravitational influence of the planet plus star system causes the brightness of the microlensing event to vary in a particular way. The planet/star mass ratio can be inferred from the precise shape of that brightness plot. This is, of course, the same physics that produces the stunning, strong-lensing Einstein Rings — but with a slightly weaker requirement for close alignment.

Unlike the radial-velocity, transit or direct-imaging methods for exoplanet hunting, the microlensing technique is able to detect exoplanets at huge distances. Meanwhile, a field with physically more stars is a great place for microlensing experiments, since a large number of stars need to be monitored for a long time so as to catch some of these chance alignments of foreground and background stars. As such, OGLE has been staring at the center of the galaxy for over a decade.

More recently, the microlensing community has become particularly interested in microlensing detections that have been measured by multiple different telescopes simultaneously. In a typical microlensing event, the mass and the distance of the foreground lensing star are degenerate. However, this degeneracy can be broken by comparing several simultaneous observations of the microlensing event with physically separated telescopes. The wider the separation between the different telescopes measuring the microlensing detection, the better — so why not use a telescope in space? The Spitzer telescope is almost 200,000,000 km away, giving an impressive distance baseline for this kind of work.

Figure 1: Sensitivities to planets for a subset of the survey. Red, green, blue, purple and black curves show the depth to which 15, 30, 45, 60 and 75% of planets could be detected; q and s represent the mass ratio and projected separation of the planets. The bottom left corner lists the OGLE catalog number (bold) and the impact parameter, which represents the closest on-sky separation of the two stars during the entire event. [Adapted from Zhu et al. 2017]

Today’s authors carry out a pilot study laying out the methodology for a microlensing survey exploring how the galactic bulge affects planet formation. After data validation, removal of instrumental systematics, and a check that the distance to each star is well defined, the authors use a sample of 41 microlensing events — all of which have been observed by OGLE, Spitzer and a third telescope, KMTNet. Each of these microlensing events consists of a distant and a nearby star — and in this case no planets are detected around the nearby stars.

The authors model each of the lensing events with a variety of planets orbiting the nearby star, so as to determine how sensitive the survey is to exoplanets as a function of mass and separation. Some of these sensitivity curves are shown in Figure 2 above. The authors then carry out a statistical analysis; for this they use a simple parametrised model of the galaxy as a bulge and a disk, a couple of different assumptions about the stellar mass function, the footprint of the survey on the sky, some beastly Bayes calculations and information about their survey’s sensitivity to planets.

On the assumption that planetary frequency is the same in the galactic bulge, the authors find that roughly a third of all planetary detections in a survey like this one should come from bulge events. Since they have no planet detections in this sample, they aren’t yet able to calculate what fraction of detections actually come from the galactic bulge — this is left as future work. If the number turns out to be significantly different from the value of one third calculated here, it will reveal crucial information about planet formation in crowded regions of the galaxy. This work is currently ongoing. And, if they get lucky, maybe OGLE-05-390L b’s record as most-distant-planet will soon be broken!

About the author, Elisabeth Matthews:

I’m a third year PhD student at the University of Exeter, in the south of England, where I’m aiming to detect and characterise extrasolar planets and debris disks via direct imaging. So far this has meant lots of detecting background stars that happen to be well aligned with bright, nearby stars and no detecting of actual planets — but hopefully my luck will change soon!

Smashing a Jet into a Cloud to Form Stars

Latest AAS Nova Highlights - Mon, 2017-12-04 12:00

What happens when the highly energetic jet from the center of an active galaxy rams into surrounding clouds of gas and dust? A new study explores whether this might be a way to form stars.

The authors’ simulations at an intermediate (top) and final (bottom) stage show the compression in the gas cloud as a jet (red) enters from the left. Undisturbed cloud material is shown in blue, whereas green corresponds to cold, compressed gas actively forming stars. [Fragile et al. 2017]

Impacts of Feedback

Correlation between properties of supermassive black holes and their host galaxies suggest that there is some means of communication between them. For this reason, we suspect that feedback from an active galactic nucleus (AGN) — in the form of jets, for instance — controls the size of the galaxy by influencing star formation. But how does this process work?

AGN feedback can be either negative or positive. In negative feedback, the gas necessary for forming stars is heated or dispersed by the jet, curbing or halting star formation. In positive feedback, jets propagate through the surrounding gas with energies high enough to create compression in the gas, but not so high that they heat it. The increased density can cause the gas to collapse, thereby triggering star formation.

In a recent study, a team of scientists led by Chris Fragile (College of Charleston) modeled what happens when an enormous AGN jet slams into a dwarf-galaxy-sized, inactive cloud of gas. In particular, the team explored the possibility of star-forming positive feedback — with the goal of reproducing recent observations of something called Minkowski’s Object, a stellar nursery located at the endpoint of a radio jet emitted from the active galaxy NGC 541.

The star formation rate in the simulated cloud increases dramatically as a result of the jet’s impact, reaching the rate currently observed for Minkowski’s Object’s within 20 million years. [Fragile et al. 2017]

Triggering Stellar Birth

Fragile and collaborators used a computational astrophysics code called Cosmos++ to produce three-dimensional hydrodynamic simulations of an AGN jet colliding with a spherical intergalactic cloud. They show that the collision triggers a series shocks that move through and around the cloud, condensing the gas and triggering runaway cooling instabilities that can lead to cloud clumps collapsing to form stars.

The authors are able to find a model in which the dramatic increase in the star formation rate matches that measured for Minkowski’s Object very well. In particular, the increased star formation occurs upstream of the bulk of the available H I gas, which is consistent with observations of Minkowski’s Object and implicates the jet’s interaction with the cloud as the cause.

The spatial distribution of particles tracing stars that formed as a result of the jet entering from the left, after 40 million years. Color tracks the particle age (in Myr) in the top panel and particle velocity (in km/s) in the bottom. [Adapted from Fragile et al. 2017]

An intriguing result of the authors’ simulations is a look at the spatial distribution of the velocities of stars that form when triggered by the jet. Because the propagation speed of the star-formation front gradually slows, the fastest-moving stars are those that were formed first, and they are found furthest downstream. This provides an interesting testable prediction — we can look to see if a similar distribution is visible in Minkowski’s Object.

Fragile and collaborators plan further refinements to their simulations, but they argue that the success of their model to reproduce observations of Minkowski’s Object are very promising. Positive feedback from AGN jets indeed appears to have an important impact on the surrounding environment.


P. Chris Fragile et al 2017 ApJ 850 171. doi:10.3847/1538-4357/aa95c6

A Shifting Shield Provides Protection Against Cosmic Rays

Latest AAS Nova Highlights - Fri, 2017-12-01 12:00

The Sun plays an important role in protecting us from cosmic rays, energetic particles that pelt us from outside our solar system. But can we predict when and how it will provide the most protection, and use this to minimize the damage to both piloted and robotic space missions?

The Challenge of Cosmic Rays

Spacecraft outside of Earth’s atmosphere and magnetic field are at risk of damage from cosmic rays. [ESA]

Galactic cosmic rays are high-energy, charged particles that originate from astrophysical processes — like supernovae or even distant active galactic nuclei — outside of our solar system.

One reason to care about the cosmic rays arriving near Earth is because these particles can provide a significant challenge for space missions traveling above Earth’s protective atmosphere and magnetic field. Since impacts from cosmic rays can damage human DNA, this risk poses a major barrier to plans for interplanetary travel by crewed spacecraft. And robotic missions aren’t safe either: cosmic rays can flip bits, wreaking havoc on spacecraft electronics as well.

The magnetic field carried by the solar wind provides a protective shield, deflecting galactic cosmic rays from our solar system. [Walt Feimer/NASA GSFC’s Conceptual Image Lab]

Shielded by the Sun

Conveniently, we do have some broader protection against galactic cosmic rays: a built-in shield provided by the Sun. The interplanetary magnetic field, which is embedded in the solar wind, deflects low-energy cosmic rays from us at the outer reaches of our solar system, decreasing the flux of these cosmic rays that reach us at Earth.

This shield, however, isn’t stationary; instead, it moves and changes as the strength and direction of the solar wind moves and changes. This results in a much lower cosmic-ray flux at Earth when solar activity is high — i.e., at the peak of the 11-year solar cycle — than when solar activity is low. This visible change in local cosmic-ray flux with solar activity is known as “solar modulation” of the cosmic ray flux at Earth.

In a new study, a team of scientists led by Nicola Tomassetti (University of Perugia, Italy) has modeled this solar modulation to better understand the process by which the Sun’s changing activity influences the cosmic ray flux that reaches us at Earth.

Modeling a Lag

Tomassetti and collaborators’ model uses two solar-activity observables as inputs: the number of sunspots and the tilt angle of the heliospheric current sheet. By modeling basic transport processes in the heliosphere, the authors then track the impact that the changing solar properties have on incoming galactic cosmic rays. In particular, the team explores the time lag between when solar activity changes and when we see the responding change in the cosmic-ray flux.

Cosmic-ray flux observations are best fit by the authors’ model when an 8-month lag is included (red bold line). A comparison model with no lag (black dashed line) is included. [Tomassetti et al. 2017]

By comparing their model outputs to the large collection of time-dependent observations of cosmic-ray fluxes, Tomassetti and collaborators show that the best fit to data occurs with an ~8-month lag between changing solar activity and local cosmic-ray flux modulation.

This is an important outcome for studying the processes that affect the cosmic-ray flux that reaches Earth. But there’s an additional intriguing consequence of this result: knowledge of the current solar activity could allow us to predict the modulation that will occur for cosmic rays near Earth an entire 8 months from now! If this model is correct, it brings us one step closer to being able to plan safer space missions for the future.


Nicola Tomassetti et al 2017 ApJL 849 L32. doi:10.3847/2041-8213/aa9373

Are Spinning Black Holes Louder?

Latest AAS Nova Highlights - Wed, 2017-11-29 12:00

A cloud of gas surrounds the distant quasar SDSS J102009.99+104002.7 in this image from ESO’s Very Large Telescope. The name “quasar” is a shortening of “quasi-stellar radio source”, though we now know that only a small fraction of quasars are radio-loud. [ESO/Arrigoni Battaia et al.]

Some distant active galaxies are louder in radio wavelengths than others. A new study explores whether this difference could be due to how quickly the supermassive black holes at their centers are spinning.

Loud and Quiet Quasars

Quasars, the most luminous type of active galactic nuclei, are powered by the accretion of material onto the supermassive black holes located at the centers of the galaxies. These distant beasts tend to fall into two general categories:

  1. radio-loud quasars, which host powerful relativistic radio jets and make up roughly 10% of the quasar population, and
  2. radio-quiet quasars, which feature only weak core radio emission and make up the remaining 90% of quasars.

What causes this distinction in jet behavior? Many theories have been put forward, but today we’ll explore one potential factor in particular: the spin of the black hole.

Histogram of the [O III] equivalent width for radio-loud (solid red) vs. radio-quiet (dashed blue) quasars, for three different definitions of radio-loudness. [Adapted from Schulze et al. 2017]

In the spin paradigm, it’s postulated that the angular momentum from a black hole’s spin — which can be retrograde, prograde, or nonexistent — is what allows (or doesn’t allow) for the launch of relativistic jets. In this picture, radio-loud quasars should have rapidly spinning supermassive black holes at their centers, whereas radio-quiet quasars should host low-spin black holes.

A Tricky Measurement

Past studies examining the spin paradigm suggest that it doesn’t hold up — several radio-quiet quasars were found to host black holes with apparently high spin. But measuring black-hole spins is notoriously tricky, with each method relying on a number of inferences. It’s possible that the method used to infer the high spins of these radio-quiet quasars might not have yielded accurate results.

A team of scientists led by Andreas Schulze (National Astronomical Observatory of Japan) has now proposed an alternative approach to test the spin paradigm. Schulze and collaborators suggest using the strength of a particular emission line, [O III], to indirectly measure the black holes’ average radiative efficiency — i.e., how much of the energy of the mass accreting onto the black holes is converted into radiation. If the average efficiency for a sample of radio-loud quasars is different than that for a sample of radio-quiet quasars, this would mean a difference in black-hole spins for the two samples.

Counting Spin Back In

Using a sample of nearly 8,000 quasars identified in the Sloan Digital Sky Survey, the authors find that the [O III] line strength is enhanced by a factor of at least 1.5 in a radio-loud sample, compared to a radio-quiet sample matched in redshift, black-hole mass, and accretion rate.

[O III] equivalent width for the radio-loud (solid red) and radio-quiet (dashed blue) samples as a function of redshift. [Schulze et al. 2017]

Schulze and collaborators argue that this suggests the black-hole spins of the radio-loud quasar population are systematically higher than those of the radio-quiet population.

The authors caution that, like other tactics used to learn about black-hole spins, their approach relies on a number of key assumptions — and their results certainly don’t mean that spin must be the only factor differentiating between radio-loud and radio-quiet quasars. The results do suggest, however, that we shouldn’t count spin out of the game: it may play an important role in determining the loudness of these distant accreting monsters.


Andreas Schulze et al 2017 ApJ 849 4. doi:10.3847/1538-4357/aa9181


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