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AIJ example plot

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

 

AIJ

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 Astronomy.net
  • 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

Citation

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

GJ 1132 b

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:

GJ 1132 b radius

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.

Citation

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

SDSS

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:

MaNGA target

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.

Citation

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

TRAPPIST-1

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:

magnetic field lines

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.

Citation

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

Milky Way

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 2017

 

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:

RR Lyrae sample

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.

Citation

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

planetary system

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

Kepler K2

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.

Hyades cluster

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.
K2 light curves

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.

Citation

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

molecular cloud

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.

Taurus Molecular Cloud

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.

cloud simulations

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.

cloud properties

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.

Bonus

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

Citation

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

photograph of a stream of material looping off of the sun's surface

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

flaring dwarf star

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.

Kepler flaring stars

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. rotation influence

    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.

Citation

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

ESO 243-49

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.

metallicity gradients

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). 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.

Note: This post was edited to remove a statement implying that the authors’ results indicate the thin and thick disks have the same radial extent.

Citation

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

jet-cloud interaction simulation

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.

simulation results

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.

star formation rate

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.

star properties

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.

Citation

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

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