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Robo-AO

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

Title: Robo-AO Kepler Planetary Candidate Survey IV: The effect of nearby stars on 3857 planetary candidate systems
Author: Carl Ziegler, Nicholas Law, Christoph Baranec, et al.
First Author’s Institution: University of North Carolina at Chapel Hill
Status: Published in AJ

Introduction

In the 1970s and 80s, scientists working for the U.S. Department of Defense developed a secret technology for imaging Soviet spy satellites from the ground. One of the consultants, Claire Max, realized the technology could benefit astronomy and pushed for its declassification. The concept of adaptive optics with laser-powered guide stars was finally released to the public in 1991.

Adaptive optics (AO) involves the rapid deformation of a mirror to remove distortions from an image. Imagine seeing a rock at the bottom of a clear but fast-moving stream of water. Inverting the jittery, garbled image into a true image of the rock is a significant engineering and computational challenge. First, we need to observe a simple point source behind the same distorting medium.

This is where laser guide stars come in. One type of laser lights up a thin layer of sodium at about 90 km altitude. This creates a “guide star” that experiences much of the distortion seen in a true star. Using this information, a deformable mirror can correct the true star’s image in real-time.

But large AO systems are extremely unwieldy. They require lots of money and manpower, and lots of observing overhead — it can take several minutes to slew to a target, lock onto a guide star, and initialize a correction loop for deforming the mirror. And yet, in today’s era of “big data” astronomy, AO imaging has become ever more relevant for rapidly-growing datasets. There’s a niche for fast, robotic AO. Recently, the optical scientist Christoph Baranec has done just that by building… Robo-AO.

improvement from Robo-AO

Figure 1: Left: An example image of Kepler’s view of a KOI. The large pixels hide an unknown number of stellar companions. Right: The same view, using Robo-AO. [Ziegler et al. 2017]

Today’s Paper

The Kepler space telescope has detected thousands of possible exoplanets transiting in front of their host stars. But the Kepler pixels are huge — about 4 arcseconds across — and there’s always a risk that multiple stars are lurking in a single pixel (Figure 1). This can lead to false positives (like in eclipsing binary systems) or can dilute real planet signals (where the light from another star will make a transiting planet’s radius seem smaller than it actually is). This calls for AO follow-up.

Before Robo-AO, AO follow-up of Kepler objects of interest (KOIs) has been a heterogeneous and incomplete effort using different instruments, reduction pipelines, and analyses. To establish a consistent, complete, and unbiased analysis, Robo-AO has targeted Kepler stars from Palomar Mountain in California and Kitt Peak in Arizona. (Check out an introductory video about the project here, and a time-lapse of Robo-AO hammering targets with a UV laser here.) The most recent paper to be published on the accumulating Robo-AO Kepler data reports on 3857 KOI observations, taken at a rapid-fire cadence of 20 targets per hour.

Robo-AO KOI images

Figure 2: A beauty parlor gallery of Robo-AO KOI images taken at Kitt Peak. [Ziegler et al. 2018]

Within their ranges of sensitivity, the authors found that about 17% of the stars had stellar companions within 4″. In total, they found 610 stellar companions to 559 KOI stars. The authors calculate that if the candidates orbit the target star, then the planet radii have to be multiplied, on average, by a factor of 1.08. If they orbit a bound stellar companion, their radii increase by a factor of 3.29! A total of 35 supposedly rocky planets have newly revised radii of >1.6 Earth radii in either scenario, meaning that they are gaseous giant planets, not rocky ones.

rate of stellar companions

Figure 3: Rate of stellar companions based on separation. Unassociated stars would be expected to increase roughly like a parabola (dashed line), but the observed number is greater, meaning that some of the stellar companions must be gravitationally bound and possibly influence exoplanet types which emerge in the system. [Ziegler et al. 2018]

Planets in Multistellar Systems?

Models suggest that stellar companions could severely perturb planets’ orbits or fling planets out of a system entirely. To determine the effect of stellar companions on planet formation, we first have to determine which of the KOI companions are gravitationally bound with each other, and how many are unbound but are just along close lines of sight.

The authors argue that if companions were unbound, then we would expect a field of view twice as large to lead to about four times as many found companions. But in fact, found companions increase linearly, suggesting that some of the stars are indeed bound (Fig. 3). The authors are preparing another paper that will take a deeper dive into the nature of these companions, which will bring us closer to understanding the effect of multiple stars on planetary systems.

In the meantime, Robo-AO is continuing to pursue many different science cases. And a southern Robo-AO unit at Cerro-Tololo is under development, as is a Robo-AO 2 instrument in Hawaii. Soon we can observe most of the sky with Robo-AO’s automated gaze. Unless, that is, the robots finally rise against us.

About the author, Eckhart Spalding:

I am a graduate student at the University of Arizona, where I am part of the LBT Interferometer group. I went to college in Illinois, was a secondary-school physics and math teacher in Kenya’s Maasailand for two years, and got an M.S. in Physics from the University of Kentucky. My out-of-office interests include the outdoors, reading, and unicycling.

magnetar

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

Title: Sites That Can Produce Left-Handed Amino Acids in the Supernova Neutrino Amino Acid Processing Model
Author: Richard N. Boyd, Michael A. Famiano, Takashi Onaka, and Toshitaka Kajino
First Author’s Institution: The Ohio State University
Status: Published in ApJ

Scientists are enamored with the search for life. They’ve scoured spectra for hints of life-supporting gases in the atmospheres of exoplanets. They’ve assessed the friendliness of galaxies near and far, and found the universe to be an unforgiving place. They’ve plumbed the depths of the oceans and studied pristine Antarctic lakes to understand the harsh conditions life might be able to withstand elsewhere in the cosmos.

The search for life on other worlds has been guided by what we know about life on Earth. Life as we know it depends on amino acids to survive. Today’s paper explores the effects of exotic astrophysical settings on amino acids, which could tell us something about how life came to be on Earth — and where else in the universe life like Earth’s might be found.

The Stuff of Life

Amino acids — important components of proteins — have a property called chirality or handedness. Much like left and right hands, which are mirror images of each other, chiral molecules come in left- and right-handed pairs. These pairs of molecules contain the same atoms and the same chemical bonds, but no amount of turning, bending, or wiggling can make them look exactly the same, as Figure 1 shows.

alanine

Figure 1. A simple amino acid, alanine. The solid triangle indicates that that part of the molecule sticks out of the plane of the page, while the dashed triangle indicates that that part of the molecule is directed backward, into the page. The two forms of alanine, left-handed (left-most illustration) and right-handed (center illustration) alanine, are a chiral pair. Right-handed alanine can’t be converted to left-handed alanine just by turning the molecule over (as illustrated in the right-most illustration).

Right-handed amino acids are rare in nature, and all multicellular Earth life depends on amino acids that are left-handed (with the exception of glycine, which is the same as its mirror image). This is weird. If you whip up a batch of your favorite amino acid in a lab (such as in the famous Miller-Urey experiment and subsequent experiments that demonstrated that lightning could kick off the formation of amino acids in the primordial soup), the molecules will be roughly 50-50 left- and right-handed — so why does life have a preference for left-handed amino acids?

While many scientists believe that the preference for left-handed amino acids arose naturally on Earth, the how is still unclear. Another option is that the bias toward left-handed molecules was introduced from afar — through amino-acid-bearing meteorites crashing to Earth, for example. Many meteorites contain a small excess of left-handed amino acids, which tells us that some process in space can create an excess of left-handedness in chiral molecules.

Where Does Left-Handedness Come From?

The authors of today’s paper suggest that a preference for left-handed amino acids can be caused by a combination of a strong magnetic field and a source of electron antineutrinos.

First, assume that amino acids are orbiting an astrophysical object that emits lots of antineutrinos and has a strong magnetic field, such as an expanding supernova, a massive Wolf-Rayet star, or a newly born neutron star. These amino acids could be present on the surface of dust grains or embedded within meteoroids or planets. Then, as the molecules are pummeled with antineutrinos (\bar{\nu} _{e}), some nitrogen atoms are converted to carbon atoms following this process: \bar{\nu} _{e} +\, _{ }^{14}\textrm{N} \rightarrow e^{+} +\, _{ }^{14}\textrm{C} .

magnetic field of a neutron star

Figure 2. An illustration of the magnetic field of a neutron star. The magnetic field orientation (B) and the antineutrino and nitrogen spins (Sν and SN) are shown with light blue arrows. [richardboydastro.com]

If the nitrogen atom is converted to a carbon atom, the molecule will no longer be an amino acid, since amino acids are defined as having an amine (NH2) and a carboxyl (COOH) group. The likelihood of this process occurring depends on how the spins of the antineutrino and the nitrogen atom are aligned; if the spins are parallel, as shown on the left-hand side of Figure 2, the process is much less likely to happen than if the spins are misaligned.

Here’s where the magnetic field comes in: combined with the motion of the molecules around the star, the magnetic field works to align the nuclear spins of the nitrogen atoms. For left-handed amino acids, the nuclear spin is parallel to the antineutrino spin — so left-handed amino acids are more likely to survive the onslaught of neutrinos. The effect isn’t huge, since most neutrinos pass through without interacting, but the authors estimate that this process could cause a 1% excess of left-handed amino acids — comparable to the few percent excess seen in meteorites. Enough, perhaps, to imprint a bias toward left-handed molecules on the young Earth.

Are We All Aliens, Then?

Does life on Earth owe its origins to meteorites processed by antineutrinos and magnetic fields? Maybe, maybe not. There are many hypotheses for how life acquired its taste for left-handed amino acids, and they don’t have to be mutually exclusive. One thing is for sure, though: we have a lot to learn about chiral molecules — and amino acids in particular — in space. While glycine, an achiral amino acid, has been discovered everywhere from the interstellar medium to the atmospheres of comets, the first chiral molecule in space was discovered only in 2016. Perhaps the first chiral amino acids will be discovered in the tumultuous region around a newborn neutron star. If so, Earthlings can look on from afar and give them a wave. Left-handed, of course.

About the author, Kerrin Hensley:

I am a third year graduate student at Boston University, where I study the upper atmospheres and ionospheres of Venus and Mars. I’m especially interested in how the ionospheres of these planets change as the Sun proceeds through its solar activity cycle and what this can tell us about the ionospheres of planets around other stars. Outside of grad school, you can find me rock climbing, drawing, or exploring Boston.

red dwarf flare

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

Title: The First Naked-Eye Superflare Detected from Proxima Centauri
Author: Ward S. Howard, Matt A. Tilley, Hank Corbett, Allison Youngblood, R. O. Parke Loyd, et al.
First Author’s Institution: University of North Carolina at Chapel Hill
Status: Submitted to ApJL

Proxima Centauri is the closest known star to the Sun at just 4.246 light-years (1.302 parsecs) away. It’s a red dwarf of spectral type M6 with about 12% of the Sun’s mass, 1.2 times the diameter of Jupiter, and 0.17% of the Sun’s luminosity. It hosts the closest known exoplanet to us, Proxima Centauri b, which was discovered in 2016 as covered in this Astrobite. Like our Sun, it’s on the main sequence, steadily fusing hydrogen into helium in its core. Yet this tiny star is way more active than the Sun is!

Red dwarfs like Proxima Centauri have interiors that are fully convective, meaning that the energy generated by fusion in their cores is transported to the surface primarily via convection. Like a pot of boiling water, you can think of it as being one giant ball of boiling plasma. This turnover of ionized gas generates powerful magnetic fields, which are carried to the surface along with the bubbles of hot plasma. When these bubbles reach the surface the energy contained in the magnetic fields can be violently released in the form of stellar flares, which can grow as large as Proxima Centauri itself and reach temperatures of up to 27 million K! (Normally its effective surface temperature is around 3,000 K.) These flares from Proxima Centauri have been observed frequently in the past (for instance in this recent Astrobite).

Figure 1: The light curve of Proxima Centauri as seen by the Evryscope around the time of the superflare. Three weaker (but still strong) flares were detected in the aftermath of the superflare, marked by arrows. [Howard et al. 2018]

Erupting With (Super)Flair

In this paper, the authors report the discovery of the first-known superflare from Proxima Centauri (see Figure 1 for the light curve), a flare roughly ten times more powerful than any seen before. Normally Proxima Centauri sits at a visual magnitude of 11.13, approximately 100 times fainter than the human eye can see. But during the superflare the authors calculated that it would have reached an apparent visual magnitude of 6.8 for a few minutes, just bright enough to be seen with the naked eye in extremely dark skies! (No accounts of anyone actually seeing it by eye at the time are known, though.)

To discover this superflare the paper authors used data from the Evryscope, which we’ve covered in this Astrobite. Despite the name it’s not actually a single giant telescope formed out of every telescope on Earth (sadly), but is instead a unique collection of twenty-seven small telescopes all mounted on a single German Equatorial mount in Chile, one of its goals being to catch and record these short-duration transient events. It pans across the sky throughout the night taking images of 8,000 square degrees of the southern night sky simultaneously every two minutes, all night long.

On March 18, 2016, at 8:32:10 UT the Everyscope detected a superflare that lasted for over an hour, though the bulk of the energy was emitted in the first ten minutes. The authors estimate that the total energy radiated at all wavelengths was 1033.5 ergs, ten times more than any previously seen flare. However, based on the many other, less powerful flares observed by the Evryscope, the authors estimate that flares with an energy release of 1033 or more ergs probably occur around 5 times per year.

Ozone? More Like NO-zone

The authors also investigated the effects of so many flares on a hypothetical atmosphere of Proxima Centauri b by running a 1D atmospheric simulation in which the planet is assumed to have an Earth-like atmosphere.  Strong proton fluxes from coronal mass ejections associated with flares can destroy ozone by first breaking nitrogen (N2) apart into nitrogen atoms that react with oxygen (O2) to form NO and O. The NO then reacts with ozone in a catalytic reaction to form NO2, depleting the ozone (O3) layer in a very efficient manner.

The simulation generated a series of flares with a range of energies compatible with what has been observed in the past, which interacted with the model atmosphere over a simulated five-year period. Each flare had an 8% chance to have a strong proton flux associated with it (based on other work). Even this low chance of producing strong proton fluxes, however, depleted the ozone layer by 90% within five years (as shown in Figure 2). Thus it seems highly probable that Proxima Centauri b has no ozone layer to speak of.

Figure 2: The depth of the ozone column in the simulation performed in the paper. The two dashed lines denote one year and five years after starting the simulation. Flares were stopped after five years in the simulation which leads the solid line to recover back up to full, but the authors note that the dashed line is more likely in reality where flares continue. [Howard et al. 2018]

The amount of ultraviolet light reaching the surface in the absence of any ozone in the atmosphere spells bad news for any living thing unlucky enough to be in its path. The superflare over its duration would have deposited an estimated 3.6 J/cm2 of the most dangerous UV-C light to Proxima Centauri b, which is some 65 times greater than the amount needed to kill off the most radiation resistant organism known, the bacterium Deinococcus radiodurans.

Summary

Proxima Centauri is a very active star, and with the Evryscope up and running we’re in a good position to catch the next superflare it gives off (along with any regular flares). And if you were planning a beachside vacation to Proxima Centauri b, you may want to hold off until you find a sunscreen with an SPF of a million or so.

About the author, Daniel Berke:

I’m a first-year grad student at Swinburne University of Technology in Melbourne, where I search for variation in the fine-structure constant on the Galactic scale. When I’m not at uni I enjoy a variety of creative enterprises including photography, blogging, and video editing, or just relaxing with a good video game or some classical music.

Earth-like exoplanet

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

Title: A Revised Exoplanet Yield from the Transiting Exoplanet Survey Satellite (TESS)
Author: Thomas Barclay, Joshua Pepper, Elisa V. Quintana
First Author’s Institution: NASA Goddard Space Flight Center
Status: Submitted to AAS Journals

Exoplanet hunters around the world held their breath while NASA’s Transiting Exoplanet Survey Satellite (TESS) launched last Wednesday. Thankfully the launch was a success, and after 60 days of orbit manoeuvring and engineering tests, TESS is expected to begin its initial two years of science observations. The question is: how many planets do we expect TESS to find?

How To Count Chickens Before They Hatch (or Planets Before They Are Detected)

The TESS mission will observe 90% of the sky to find nearby unknown planets. However, to get mission funding, astronomers need to predict how many planets they expect to identify.

The authors of today’s paper took on this challenge with a three-step modelling plan: 1) predict which stars would be observed, 2) randomly assign planets around them and 3) test if they are detected.

  1. Stars Observed
    Determining which stars TESS is likely to observe is made easier thanks to the Candidate Target List, a ranked list of 3.8 million stars most suitable for detecting small planets (where “small” means a planet with radius smaller than 4 Earth radii). The Candidate Target List contains isolated dwarf stars brighter than TESS magnitude 13, which will be less blended in the giant TESS pixels (each pixel contains 21 arcseconds of sky, compared to 4 arcseconds in Kepler). The authors calculate how long TESS can observe these stars and those most likely to be priority targets. Data for priority targets will be available as observations every two minutes (at a two-minute cadence) whereas other stars will only have data in the full-frame images every 30 minutes.
  2. Planet Assignment
    Each star in their list is assigned 0 or more planets according to a Poisson distribution. Each planet is then given random properties, including inclination, orbital period and radius based on the general trends found by the Kepler Space Telescope. Periods are drawn from distributions between 0.5–85 days for planets orbiting A/F/G/K stars and between 0.5–200 days for planets with M-star hosts. Time of the first transit is then drawn randomly between 0 and the length of the period, which can be after observations finish, meaning no transits will be seen.
  3. Detection test
    Finally, the authors test whether the transit signal is significantly stronger than the noise. The signal strength is determined by considering the number of transits, the transit depth and duration, and the extent of contamination from nearby stars. If the signal is greater than 7.3 times the TESS photometric noise level (7.3 SNR) and at least two transits are seen, this optimistic model claims a detection.

Optimistic Planet Numbers

Figure 1: Planet numbers detected by radius using the optimistic model. Red bars indicate the numbers of planets detected using 2 minute cadence data. Numbers above blue bars show the combined number of planets found in 2 minute cadence or full frame images. Note the log scale of planet numbers. [Barclay et al. 2018]

The optimistic model above identifies ~4,500 planets around stars in the Candidate Target List, shown split into planet radius in Figure 1. For stars with V magnitude brighter than 12, the authors predict the detection of 1,317 small planets. If 20% of these are amenable to radial velocity follow up, this would triple the number of small planets with measured masses and exceed the TESS main science objective of identifying 50 small planets with measurable masses.

Predicting planet numbers means astronomers can plan the number of follow-up observations necessary to confirm planets. Not all transit-like signals will be due to transiting planets; they may be caused by instrumental effects or astrophysical false positives, such as deep eclipsing binary signals blended to give shallower transits, especially with multiple stars on the same pixel. Today’s paper predicts for every true planet found there will be one astrophysical false positive in the 2-minute cadence data, and 5.5 astrophysical false positives in the full-frame images.

More Conservative Planet Numbers

Figure 2: Planet numbers detected by radius using the conservative model. Green bars indicate the numbers of planets detected using 2 minute cadence data. Numbers above orange bars show the combined number of planets found in 2 minute cadence or full frame images. Note the log scale of planet numbers. [Barclay et al. 2018]

Identifying planets based on fewer than three transits and detecting all planets with SNR ≥ 7.3 is very difficult. The Kepler Space Telescope is capable of identifying planets from one or two transits in K2 data, but only with additional investment of limited space-based follow up, or in cases where other planets had already been discovered around that star. Analysis of Kepler data found that below SNR = 8–10, there were many spurious detections, so typically only targets with SNR > 12 were followed up.

In their conservative model, removing planets with fewer than three transits or SNR < 10 reduced the number of planets detected by 60%, as seen in Figure 2. The number of small planets detected around stars brighter than V = 12 halved to 621. The number of habitable-zone planets smaller than 2 Earth radii drops to just 6.

Adding to James Webb Space Telescope Targets

Any small planets detected by TESS may represent new targets for atmospheric characterisation with the James Webb Space Telescope (JWST). Figure 3 shows that the simulated TESS planets greatly increase the number of known small nearby planets, some of which should be amenable to atmospheric characterisation. The authors estimate that on the order of ten super-Earth planets could be found around bright M3 stars in the optimistic habitable zone, adding to JWST’s sample of temperate worlds.

Figure 3: Simulation of small planets TESS may find (orange) as a function of the star’s distance to us. Kepler planet candidates are in blue and planets detected by other telescopes in black. The size of the circle is proportional to transit depth. [Barclay et al. 2018]

Conclusion

Today’s paper will be useful for planning follow up strategies and for identifying potential numbers of planets found in TESS 2-minute cadence data and full-frame images. This is the first paper to predict planets based on the stars most likely to be observed from the Candidate Target List rather than simulated star populations. Where the authors also considered the hotter, fainter, giant or more crowded stars that TESS would observe (excluded from the Candidate Target List), planet number estimates increased to 16,000. However the higher labour intensity to follow up and much higher rates of false positives mean few of these are likely to be confirmed.

Today’s paper shows that TESS should greatly add to the numbers of known small nearby planets which we should be able to investigate further. Now we just need to find them!

About the author, Emma Foxell:

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

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

Title: Synthesis of Molecular Oxygen via Irradiation of Ice Grains in the Protosolar Nebula
Author: O. Mousis, T. Ronnet, J. I. Lunine, R. Maggiolo, P. Wurz, G. Danger, and A. Bouquet
First Author’s Institution: Aix-Marseille University, France
Status: Accepted to ApJ

Tailing a Comet’s Tail

Figure 1: A picture of the comet 67P/C-G, taken by Rosetta in August 2014. The resolution is 5.3 meters/pixel.  [ESA/Rosetta/MPS for OSIRIS Team MPS/UPD/LAM/IAA/SSO/INTA/UPM/DASP/IDA]

In August 2014, the Rosetta orbiter met up with the comet known as 67P/Churyumov-Gerasimenko (a.k.a. 67P/C-G). Rosetta stuck close by, watching and observing, as the comet orbited around the Sun. Now, nearly four years later, we’re still learning new science from everything Rosetta (and its lander Philae) discovered. In today’s astrobite, we focus on one comet discovery in particular: molecular oxygen.

Molecular oxygen (O2) is certainly important here on Earth. Plants breathe out O2 during photosynthesis, while other living creatures (like humans) breathe it in. But O2 isn’t only produced through life as we know it — which means that if we see molecular oxygen in the atmosphere of, say, an exoplanet, we shouldn’t automatically assume it came from a living source (as talked about in this article and this previous astrobite). 67P/C-G seems like an example of such a non-living, “breathing” body.

67P/C-G is a comet, which means it’s a small icy body of rock, dust, and gas orbiting about the Sun. When a comet passes close to the Sun, the Sun warms up its ices, producing a coma — the iconic tail of released gas that trails after a comet during its orbit, as seen in this gallery. With Rosetta, scientists have detected O2 abundance levels in 67P/C-G’s coma of some 1% to 10% with respect to water (which means 1% to 10% of water’s abundance). Scientists have also noted that the rate of O2 production in the coma is surprisingly correlated with the coma’s rate of water production; from this, they’ve concluded that both the O2 and the water must be coming from the same icy phase of the comet.

So how did all of this O2 get into 67P/C-G in the first place? To try to answer this question, today’s authors looked back to well before 67P/C-G formed.

early solar system

Artist’s impression of the early solar system, a disk of dust around the young Sun. [NASA/JPL-Caltech]

From Cloud to Comet

Back then — waaay back then — our solar system was young and hip and had yet to form any of its signature planets. This (brief) history of the solar system starts righteously with a dense cloud of gas and dust, hanging out in space. The dense cloud eventually collapsed, forming a swirling disk of material known as a solar nebula.  Gravity dragged more and more material towards the center of the nebula, until the pressure at the nebula’s core was so great that it fused hydrogen into helium — leading to the birth of the Sun. From there, the solar nebula transitioned into a protoplanetary disk, which refers to a puffy disk of dust grains and gas orbiting around a young star. The dust grains in this disk clumped together over time, and these clumps grew larger and larger, eventually turning into the asteroids, comets, and planets that we know and love today.

These dust grains may have had O2 tucked into their crevices and corners, and when some of these dust grains accumulated to form 67P/C-G, the O2 was trapped inside the comet as it grew. Given O2‘s correlation with water in 67P/C-G, the O2 itself seems to have come from radiolysis of water ice, which is the process in which molecules (in this case water) are broken apart by ionizing radiation (like cosmic rays).

But 67P/C-G likely formed while our solar system was still a disk of orbiting dust and gas, specifically along the disk’s midplane where heavier grains would have settled. The outer midplane of the disk would have been a cold, dark, and dense place, far from the young Sun, and ionizing radiation would have had a lot of difficulty even reaching water ice to irradiate it. So how could enough radiation have reached the water ice to produce as much O2 as we see from 67P/C-G?

Two mechanisms provide possible answers to this question. One: turbulent mixing in the disk — mixing of the disk’s materials would literally bring dust grains in the midplane up towards the disk surface. And two: the O2 wasn’t produced during the high-density disk phase at all — it was actually produced when our solar system was still a low-density cloud, when radiation would have penetrated more easily. Today’s authors explored the turbulent mixing idea, and investigated if this mechanism would be enough to produce the O2 observed for 67P/C-G today.

Caught Between Rocks and an Irradiated Place

vertical transport

Figure 2: A schematic of vertical transport due to turbulent mixing. Grains cycled from the lower midplane towards the upper regions of the disk are more exposed to external radiation. [Mousis et al. 2018]

The grains in a solar nebula or protoplanetary disk aren’t all the same size. Larger grains tend to huddle along the midplane because of gravity and drag against the gas. But smaller grains, with less weight to throw around, are more easily tossed and turned about by turbulent flows of the disk gas. This turbulent mixing moves smaller grains not only horizontally but also vertically within the disk. Figure 2 gives an illustration of this tossing-and-turning process. Today’s authors pointed out that as grains are churned vertically upwards away from the midplane, they become more exposed to external radiation from ultraviolet, X-ray, and cosmic-ray sources. They set out to model this cyclical process over a disk’s lifetime, to determine how much O2 relative to water would be produced.

O2 abundance relative to water

Figure 3: Plots of O2 abundance relative to water over the disk model’s lifetime. Each line corresponds to a different grain size (as given by the legend at the bottom right of each plot). The top panel is for a disk with more turbulence (represented by the α parameter) while the bottom panel is for a disk with less turbulence. [Mousis et al. 2018]

To do this, the authors built a simulation of vertical grain transport due to turbulent mixing. To define their disk model’s structure, they artfully combined theory, equations, and parameters from a variety of other papers and studies. For example, they adapted parametric profiles to map out the disk’s horizontal and vertical temperature and density. They used their simulation to track the vertical diffusive motion of the grains in the disk model over time for different grain sizes and levels of turbulence, and from there they calculated how much O2 in their disk model was released due to radiolysis over time.

Figure 3 shows results from their simulation over 10 million years (scientists think 67P/C-G formed within 2.2 to 7.7 million years). We can see that even the smallest/least heavy, most churnable grains didn’t reach the same level of O2 abundance observed around 67P/C-G; even in the closest case, the simulation abundances are still some two orders of magnitude below the observations. The authors felt it safe to conclude that turbulent mixing was not a main mechanism for producing the O2 observed in 67P/C-G.

So the authors agreed that the evidence points to the second mechanism, which reasoned that the O2 was produced while our solar system was still a low-density cloud. If this is true, then this affects our beliefs not only about 67P/C-G’s formation, but also about the origins and chemistry of the other comets cruising through our solar system as well. But we’ll need more simulations before we can say for sure!

About the author, Jamila Pegues:

Hi there! I’m a 2nd-year grad student at Harvard. I focus on the evolution of protoplanetary disks and extra-solar systems. I like using chemical/structural modeling and theory to explain what we see in observations. I’m also interested in artificial intelligence; I like trying to model processes of decision-making and utility with equations and algorithms. Outside of research, I enjoy running, cooking, reading stuff, and playing board/video games with friends. Fun Fact: I write trashy sci-fi novels! Stay tuned — maybe I’ll actually publish one someday!

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

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

Good luck getting any sleep on Jupiter! This humongous gas giant rotates faster than any other planet in the Solar System, completing a day in less than 10 hours! If you were to emigrate from Earth to the largest planet in our solar system and still aimed to get the daily 8 hours of sleep recommended for adults, that would leave you with less than two hours per day to eat, exercise, and study astrophysics. That’s not nearly enough time! Future inhabitants of Jupiter’s cloud cities should not complain, though.

When Jupiter formed, it accreted its atmosphere (over 95% of the planet’s total mass!) from the hydrogen and helium gas in the protoplanetary disk surrounding our Sun. As Jupiter ate up this gas mass, it must have begun to spin faster as it also ate up the gas’s angular momentum. Eventually, it would reach the break-up velocity, which is defined as the point when the upper layers of the atmosphere are rotating as fast as an object would if it were placed in orbit around the planet close to the surface. At these speeds, Jupiter could not possibly rotate any faster. Naively, we would expect Jupiter to still be rotating that fast today. However, if we calculate Jupiter’s rotation period based on its break-up velocity, we get that one Jovian day should not even last 3 hours!

Really, Jupiter’s inhabitants should be thankful that something was able to slow down the planet’s rotation enough for them to be able to watch the first four Harry Potter movies in one day instead of just one of them. But what?

We have long known that Saturn also rotates much slower than its break-up speed (11 hr compared to 4 hr). And as Eckhart summarized in his December astrobite, we now know gas-giant exoplanets also rotate slower than expected. In today’s paper, Konstantin Batygin attempts to solve this widespread conundrum with the solution people would most expect: Jupiter’s magnetic field.

Copying the Answer

Jupiter and Saturn aren’t the only objects in our solar system subject to this mystery. When the Sun formed, it too accreted hydrogen gas from the disk around it. As a result, we would naturally expect the Sun to be rotating even faster than Jupiter. Yet a solar day lasts nearly a month, somehow leaving the Sun with only about 1% of our solar system’s angular momentum — even though it has over 99% of the mass!

One way for the Sun, or any object, to lose angular momentum is to fling out some of its material. The leading explanation for why stars like the Sun spin down this way is called magnetic braking. In this process, the solar wind carries material out of the surface just like it does today. Then, some of that material will get caught on the Sun’s magnetic field lines, which expel it even further from the Sun — taking a significant chunk of the Sun’s angular momentum with it. To conserve angular momentum, the Sun will have to slow down how fast it rotates. Can gas-giant planets do this too?

Copying Doesn’t Work

Jupiter is not quite the same as a star. It doesn’t have a solar wind, so it can’t just fling out material. However, recent research on how gas giants accrete their atmospheres may offer an alternative idea.

While we used to assume Jupiter accrued gas directly at its equator, modern simulations show it actually should have collected gas from above its “North Pole” (and below its “South Pole”). As Figure 1 shows, not all of the material gets eaten by Jupiter. Some of it is deflected outward into a disk around Jupiter — called a circumplanetary disk. The disk then spills that material back into the larger disk around the star — the protoplanetary disk from which it came. This makes up for Jupiter not having a solar wind and gives it a way to fling out material and angular momentum.

magnetic braking

Figure 1. Concept diagram of magnetic braking for a growing Jupiter-size planet. A) The planet can accrete hydrogen gas into its atmosphere directly from the blue protoplanetary disk around the star (not the disk around the planet!). This gas follows the meridional flow arrows towards the “North Pole” of the planet. B) The rest of the hydrogen is deflected into the orange disk around the planet. The planet can also accrete some more gas from this orange disk (specifically, the upper and lower layers). However, most of the orange disk (the middle layers) will spill outward, following the white arrows through the red region — leading it back into the blue disk around the star where it started. The fact that the gas is expelled completely out of the disk around the planet makes it possible for the planet to undergo magnetic braking. [Batygin 2018, by James Keane]

Spinning Slower, Then Faster

Figure 2 shows the evolution of Jupiter’s rotation period (i.e. the length of its day) after it formed, with and without magnetic braking. In both models, Batygin assumes that Jupiter starts out with twice as large of a radius before gravity causes it to contract to its present-day size in about 1 Myr. He also assumes that the planet starts out rotating at the break-up velocity (about 8 hours).

Without any slow-down, Jupiter simply speeds up as the planet contracts in order to conserve angular momentum. But with magnetic braking, Jupiter first spins down to a rotation period of 36 hours in about 25,000 years. Then, gravitational contraction spins it back up to a rotation period of 9 hours by the time it reaches its current radius — pretty close to its present rotation period of 9 hours and 56 minutes!

Jupiter's rotation period

Figure 2. Jupiter’s rotation period in the first 2 Myr after it formed. Without magnetic braking (gold), it rotates at the break-up velocity, which gets faster as the planet shrinks in size. With magnetic breaking (blue), Jupiter spins down first, leaving it with about the right rotation period by the time it contracts to its current size. [Batygin 2018]

Now that the model in this paper has demonstrated magnetic braking can lead to about the right spin rate for Jupiter (and Saturn too), Batygin hopes future work will explore more meticulous aspects of the problem related to magnetohydrodynamics (MHD), both with an analytic approach (like with the equations in this paper) and also with simulations (which were not used directly in this model).

The astrophysicists living on Jupiter or gas-giant exoplanets in other star systems will have plenty more time per day to investigate this problem. And they may have both magnetic fields and how these planets accreted their atmospheres to thank.

About the author, Michael Hammer:

I am a 3rd-year graduate student at the University of Arizona, where I am working with Kaitlin Kratter on simulating planets, vortices, and other phenomena in protoplanetary disks. I am from Queens, NYC; but I’m not Spider-Man…

spotted star planet transit

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

Title: The Transit Light Source Effect: False Spectral Features and Incorrect Densities for M-Dwarf Transiting Planets
Author: Benjamin V. Rackham, Dániel Apai, and Mark S. Giampapa
First Author’s Institution: The University of Arizona
Status: Published in ApJ

Twice in my life, I have mistakenly purchased green sweaters. “What a lovely pearl gray!” I have thought in the soothing, dim light of a Target fitting room. “This will go so nicely with my red corduroys,” I have mused under the bland fluorescent bulbs of the check-out line. “Dammit, green again?” I have sworn in the harsh sunshine of the parking lot.

Unhappily, this is neither the most important nor the most expensive mistake an astronomer can make about lighting. Misinterpreting the color of a sweater based on the wrong perception of the ambient light? Not so bad — I just had to wait in another line to return the impostor sweater. But misinterpreting the color of planets based on misunderstanding their host stars’ light? Today’s authors warn that such a mistake could lead us to false conclusions about planetary atmospheres, compositions, and habitability.

The Wrong Kind of Light

Planets are cool (temperature-wise, but also in terms of social status), and therefore planets are dim. All of our knowledge of planets beyond our solar system is therefore somewhat indirect; it comes from analyzing the much brighter light from a planet’s host star, influenced by the planet in some way. In the most straightforward case, a big planet reflects some starlight, and we take a picture of it. Subtler planets block some starlight, or swing the star around at such speeds that the starlight changes color.

Planets with atmospheres are able to warp starlight in another way: while the body of the planet blocks a big chunk of starlight as it crosses in front of its host star, the planet’s thin, enveloping atmosphere absorbs starlight at particular colors, or wavelengths.

We can subtract a spectrum of the star taken before the planet crosses the star from a spectrum taken right in the middle of its transit — the difference, called a “transmission spectrum,” is the signature of the planet’s atmosphere. Different molecules have different spectral effects, so the transmission spectrum tells us what the planet’s atmosphere is made of.

But how do we know what out-of-transit spectrum to subtract? Usually, we take the average spectrum of the whole star. But as today’s authors remind us, stars are fickle and inconstant creatures. Their surfaces change; dark starspots bubble and bright faculae simmer.

If a planet transits directly across one of these features, it’s back-lit by a different light than the average light of the star. Subtracting the average, in this case, imparts a false signal in the transmission spectrum (see Figure 1). Just as I mistook a green sweater for gray by mistaking yellowish indoor light for white, we may end up interpreting planet spectra wrongly by misunderstanding the spectral colors of their host stars.

Figure 1. An illustration of the “transit light source effect,” by which we can derive an incorrect understanding of a transiting planet’s atmosphere by wrongly assuming that the planet transits an “average” piece of the star. Middle panel: The spectrum of the entire star, averaged together (blue) vs. the spectrum of the piece of star that the planet actually crosses (orange). Right panel: As the planet transits, its atmosphere absorbs some of the starlight it intercepts. By subtracting an in-transit spectrum from an out-of-transit spectrum, you can isolate the spectral signature of the planet’s atmosphere. But if you subtract the (wrong) blue spectrum instead of the (right) orange one, you get the wrong atmospheric signal (green) instead of the right one (gray). [Rackham et al. 2018]

The Wrong Answers

An incorrect transmission spectrum is a dangerous thing. Not only can it lead us astray with respect to the chemical makeup of the planet’s atmosphere, it can also lead us to wrong answers about much more basic properties, like the planet’s size.

Alarmingly, it’s difficult to estimate how spotted any particular star is — and therefore how wrong we’re likely to be — based on a transit observation alone. The authors focus on M-dwarf stars, whose surfaces are poorly understood and which commonly host rocky exoplanets.

As a star rotates and spots come in and out of view, they impart a sine-wave pattern to the star’s light curve, which we observe when we look for transits; a larger fraction of the surface with spots means that the amplitude of the wave will be larger. But today’s authors show that you can’t infer the spotted fraction of a star’s surface based on the amplitude alone, because a wide range of “spottinesses” generates the same amplitude.

It’s a bleak outlook! The authors examine one famous M-dwarf planetary system, the seven-rocky-planet TRAPPIST-1, and conclude that the effect of being wrong about starspots is up to 15 times bigger than the signal of the planets’ atmospheres. It’s nigh impossible to measure anything meaningful about planetary atmospheres when there’s such a large confounding influence.

Figure 2. An investigation of the transit light source effect in the 7-planet TRAPPIST-1 system. Left panel: The amplitude of the variability in TRAPPIST-1’s light curve due to starspots is observed to be 0.01 magnitudes (black dashed line), but according to the models plotted in blue and gray, this is consistent with a huge range of starspot covering fractions (x-axis). Middle panel: The ratio of observed transit depth to true transit depth for the TRAPPIST-1 planets, across a range of wavelengths, due to starspots. Starspots cause us to overestimate the radii of planets and therefore underestimate their densities. Right panel: The ratio of observed-to-true transit depths at a handful of specific wavelengths where molecular absorption features appear. The effect of stellar contamination is up to 15 times larger than the signal expected from molecules in the atmosphere of a rocky planet (light green band), which means that we can’t currently draw any meaningful conclusions about planetary atmospheres from measurements like this. [Rackham et al. 2018]

A Call to Action

Right now, we just don’t understand stellar surfaces well enough to be confident that we’re correct in our transmission spectra. To improve our understanding, we can watch planets transit spotted stars in multiple wavelength bands to get better constraints on where the starspots are and how much area they cover. Consider it a silver lining to the recent news that the James Webb Space Telescope is delayed until 2020: we have two more years to figure out stars before it looks at any planets!

About the author, Emily Sandford:

I’m a PhD student in the Cool Worlds research group at Columbia University. I’m interested in exoplanet transit surveys. For my thesis project, I intend to eat the Kepler space telescope and absorb its strength.

Type Ia supernova

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

Title: Further insight on the hypervelocity white dwarf, LP 40-365 (GD 492): a nearby emissary from a single-degenerate Type Ia supernova
Author: Roberto Raddi, Mark Hollands, Detlev Koester, et al.
First Author’s Institution: University of Warwick, UK
Status: Accepted to ApJ

I’m sure you’ve heard of Type Ia supernovae. They’re a certain type of exploding star, most famous for the fact that their brightness can be easily calculated from the other features of the explosion. If you know how bright something is, and you measure how much of the light reaches you, that tells you how far away the light source must be; “standard candle” is the common term for objects like this. Type Ia supernovae are useful to astronomers who want to measure the distance to far-away galaxies, and they form one link in the cosmic distance ladder.

Despite how useful Type Ia supernovae are, we still don’t fully understand how they happen. We know that you need a white dwarf, and you need that white dwarf’s mass to increase until it nears a critical point (the Chandrasekhar mass limit, which is about 1.4 times the mass of the Sun). What we don’t know is what makes a white dwarf’s mass increase to reach that point. There are two models that we usually consider for how this happens. Firstly, the white dwarf could slowly pull matter from a nearby star. Secondly, two white dwarfs could collide. The two models are often called “single-degenerate” and “double-degenerate”, because “degenerate objects” is another term for white dwarfs (a term related to the physics of their structure). The advantages and disadvantages of the two models have been debated for decades. In recent years the debate seems to have leaned more towards the double-degenerate channel for most Type Ia supernovae, and the single-degenerate channel for some unusual-looking Type Ia supernovae.

Last year, a team of astronomers found a white dwarf named LP40-365. It’s moving through the galaxy incredibly fast (about 500–800 km/s), and it contains an unusual collection of elements. The authors of the discovery paper suggest that this is a leftover from a Type Ia supernova — a white dwarf that tried to go bang but survived. Today’s authors studied spectra of the star (from the Copernico telescope) in order to get a better idea of what is going on with it.

Spectrum of LP40-365

Figure 1: The spectrum of LP40-365. The top panel shows the low-resolution spectrum taken for today’s paper, while the bottom panels show two high-resolution spectra. Black lines show the spectrum itself; red the best-fit model found by today’s authors. Spectral lines from identified elements are labeled. [Raddi et al. 2018]

From their spectrum, they measure a temperature of 8,000 to 10,000 Kelvin (towards the cool end for white dwarfs) and a surface gravity between 100 and 3,000 times that of Earth (uncertainties this size on surface gravity are not too uncommon). This surface gravity is very low for a white dwarf, suggesting it has an unusually low mass — which seems to fit with the theory that the white dwarf has been partially exploded.

white dwarf abundances

Figure 2: Measured abundances for various elements shown as black dots, scaled so that 0 = the abundance of that element in the Sun. For comparison, the abundances of the same elements are shown for a typical low-mass white dwarf (red), metal-polluted white dwarf (green), and oxygen-atmosphere white dwarf (blue). [Raddi et al. 2018]

The spectrum of LP40-365 is pretty complicated, and it shows a multitude of unusual elements. It’s rare that astronomers have to talk about any material heavier than, say, oxygen; in LP40-365 today’s authors found helium, oxygen, neon, sodium, magnesium, silicon, calcium, iron, nickel, sulphur, chromium, titanium, and — importantly — manganese. They measured the abundance of each of these elements (see Figure 2). They found that the white dwarf seems to be around 2/3 helium and 1/3 neon, with other elements being at most 2% of the mass. However, they do stress the difficulties of modelling such an unusual system — the elements interact in ways that aren’t fully understood and hence aren’t included in the modelling code, and there are several features in LP40-365’s spectrum that they haven’t been able to understand.

The Supernova

The presence of manganese turns out to be an important clue as to how this white dwarf formed — specifically, what kind of Type Ia supernova created it. Manganese creation only occurs under high pressures, the type of pressure found in high-mass white dwarfs. If the supernova occurred through the single-degenerate channel, this makes sense — our white dwarf has grown to its high mass over millions of years, and it therefore had plenty of time for the pressure to increase in response to the high mass. In the double-degenerate channel, however, our two normal-mass white dwarfs collide and explode almost straight away, and the pressure needed is never reached. The presence of manganese is then a strong sign that this failed supernova formed via the single-degenerate channel.

The authors also note that a remnant with this composition — dominated by helium and neon, with very little carbon — is hard to make from the most commonly considered Type Ia supernova progenitor, a carbon-oxygen-core white dwarf. Instead, they point towards a rarer type of white dwarf that has oxygen-neon cores.

In any case, LP40-365 is the first known white dwarf to have survived a (failed) Type Ia supernova, and as such it opens up some exciting prospects for future science.

About the author, Matthew Green:

I am a PhD student at the University of Warwick. I work with white dwarf binary systems, and in particular with AM CVn-type binaries. In my spare time I enjoy writing of all kinds, as well as playing music, board games and rock climbing. For more things written by me, take a look at my website.

TESS

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

Title: Precision Light Curves from TESS Full-Frame Images: A Difference Imaging Approach
Author: Ryan J. Oelkers and Keivan G. Stassun
First Author’s Institution: Vanderbilt University
Status: Submitted to AJ

Disclaimer by Tarini: The first author of this paper was my supervisor during an REU, and while I was briefly involved with TESS as an undergraduate I did not participate in this work.

Figure 1: Left: field of view of the four TESS cameras. Middle: the twenty-six observation sectors TESS will cover across the northern and southern hemispheres of the sky. Right: the duration for which TESS will observe different parts of the sky, with the James Webb Space Telescope (JWST) continuous viewing zone. [NASA/TESS]

The Transiting Exoplanet Survey Satellite (TESS) will be launching very soon (in about a month, according to NASA’s launch countdown clock), and it promises to yield exciting results with a near all-sky survey for exoplanets around bright, nearby stars. Over two years, TESS will observe over 400 million stars by systematically scanning sectors of the sky for 27 days at a time (see Figure 1). About 400,000 of these stars will be studied closely and will have light curves associated with them in data releases. The rest of the stars can be studied through full-frame images (FFIs), which have a 30-minute cadence and consist of TESS’s entire field of view. To clarify, this doesn’t mean that an observation is taken every thirty minutes. The TESS cameras take images every two seconds. To save on storage and transmission time those images are stacked to create new images with effective exposure times of thirty minutes.

Because TESS is designed to conduct a wide survey, its pixels span a large part of the sky — 21 arcseconds per pixel, to be exact. For comparison, the Wide Field Camera 3 on the Hubble Space Telescope spans 0.04 to 0.13 arcseconds per pixel, depending on the detector. The large arcsecond-per-pixel scale means that the stars in TESS FFIs are more likely to be distorted and blurred into each other, making it difficult to measure changes in brightness (see Figure 2). How can one get around this? The authors of this paper offer up an image-processing pipeline that does the trick.

Figure 2: Comparing the pipeline’s output for three different data sets with different arcsec/pixel scales. The x-axis records magnitude and the y-axis records the deviation from the average magnitude of a given object. The inset images show how stars appear in the typical image from that data set. From left to right, the scales are 6.4”/pix, 15”/pix, 21”/pix (TESS). [Oelkers & Stassun 2018]

Stack, Subtract, Extract

One way to measure how an object’s brightness changes is to count the number of photons it emits over time. This is easy to do when a star is in a sparsely-populated part of an image; it’s safe to assume that any light from that part of the image is coming from the star. In crowded fields, things get complicated. Stars can appear to overlap, making it difficult to tell where the light is coming from.

A way around this is Difference Imaging Analysis (DIA). To do this, you need at least two images of the same part of the sky. Usually, one has a higher signal-to-noise ratio (SNR) than the other. Blur the image with the higher SNR to match the image with the lower SNR, and subtract one from the other. This should eliminate any objects that have a constant brightness and leave behind — you guessed it — the objects that do change brightness!

To determine a DIA approach to TESS FFIs, the authors used NASA’s “End-to-End 6” (ETE-6) simulated FFIs for TESS. To create the higher-SNR image, all 1,348 ETE-6 images were aligned and stacked to create a master frame. Aside from creating a frame to subtract from, stacking several images also ensures that transient objects like asteroids are removed from the master image. To be sure that subtraction had occurred properly, the authors checked the distribution of the values of background pixels in the differenced image. If only variable objects were left behind, then the rest of the pixels ought to be around zero. This is indeed the case with the differenced images that are produced (see Figure 3).

Figure 3: Left: a typical science image, with the colors inverted and an arrow pointing towards a candidate variable object. Middle: the differenced image, with an arrow still pointing at the much more distinct variable object. Right: the distribution of background pixel values from the differenced image. The distribution follows a Gaussian centered at zero, which means that the subtraction occurred properly. [Oelkers & Stassun 2018]

Through the Light Curves, and What the Pipeline Found There

The exact number of variable events (transits and variable stars) injected into the simulated images is unknown, but there should be several hundred of each type. The authors recovered 2,275 stars that showed variability (see Figure 4), which is good news for the pipeline. With their current resources, the authors estimate that they should be able to extract light curves from TESS FFIs a few weeks after data releases. The pipeline is publicly available and can be adapted for other data sets.

Figure 4: Examples of the variable-object light curves extracted from the ETE-6 FFIs. Left: likely simulated periodic variable star. Middle: likely simulated transit or binary candidate. Right: simulated large-amplitude variable star. [Oelkers & Stassun 2018]

All in all, it seems that TESS is going to uncover loads of interesting objects. It’s expected to recover approximately 1,700 planets from its target stars — including 70 or so Earth-like planets — and variable objects by the thousands from its FFIs. And DIA will definitely make a difference.

About the author, Tarini Konchady:

I’m a first year graduate student at Texas A&M University. Currently I’m looking for variable stars to better calibrate the distance ladder. I’m also looking for somewhere to hide my excess yarn (I’m told I may have a problem).

SL2S0217

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

Title: A Window on the Earliest Star Formation: Extreme Photoionization Conditions of a High-Ionization, Low-Metallicity Lensed Galaxy at z∼2∗
Author: Danielle A. Berg, Dawn K. Erb, Matthew W. Auger, Max Pettini, Gabriel B. Brammer
First Author’s Institution: University of Wisconsin Milwaukee
Status: Submitted to ApJ

A crucial component of understanding how galaxies evolve is figuring out what their earliest years are like. However, this process presents a problem to astronomers, since most early galaxies are believed to have been small and faint and are quite distant to boot. One simple workaround is to study nearby galaxies that we believe have similar properties to the progenitors of older galaxies like the Milky Way or Andromeda. Today’s paper covers the analysis of one such galaxy.

Previous observations of the galaxy SL2S0217 using the Hubble Space Telescope have revealed that it is young, small, metal-poor, and forming about 23 solar masses of new stars per year. Small galaxies like SL2S0217 can sometimes be hard to observe at large distances since they tend to be faint. However, this galaxy is serendipitously located behind a much larger galaxy, which gravitationally lenses it and magnifies its light by a factor of 17, simultaneously smearing it into an arc-like shape (see the cover image above). Using a model of the lens, astronomers have been able to reconstruct the true appearance of the galaxy, revealing a clumpy and irregular shape.

In today’s paper, the authors used spectra of this galaxy obtained from the Keck I telescope to study its strong UV emission lines (Figure 2), which likely come from a combination of nebular gas around hot stars and from the interstellar medium (ISM). These features are highly unusual for redshift z = 2 galaxies, which generally don’t show signatures of strong emission.

spectrum of emission line galaxy overlaid with stacked spectra from "normal" galaxies

Figure 2:  The spectrum of SL2SJ0217 is shown in black, while the orange line shows the stacked spectrum of 1,000 redshift z = 2 galaxies to serve as a comparison. The blue dotted lines and purple dashed lines show nebular and ISM features, respectively. The gray bars show regions of the spectrum that may be contaminated in observations by spectral features of the Earth’s atmosphere. [Adapted from Berg et al. 2018]

In order to figure out what the conditions in the real galaxy are like, the authors use the program CLOUDY17 to model the chemistry and photoionization occurring in nebular gas and the ISM, generating a simulated spectrum.  By varying the input parameters to the model and comparing the simulated and observed spectra, the authors find the best-fit model to the observed spectrum — confirming the previous finding that the nebular gas of SL2S0217 is metal-poor and embedded in a hard radiation field. This hard radiation indicates that there is an abundance of high energy photons in the galaxy.

Building on this result, their best fit is obtained when including the effects of binary-star evolution, indicating that this galaxy contains a high fraction of binary stars (which is not generally assumed when modeling stellar populations). However, one characteristic of the spectrum could not be reproduced using stellar photoionization alone: a particularly strong and narrow He II emission line (Figure 3). To reproduce this line, the authors consider additional ionization sources for the gas, separately incorporating the effects of shock and active galactic nuclei (AGN) heating into the photoionization code to see if these could potentially cause the high He II emission.  Varying the shock velocity and the radiation field of the AGN, they find the inclusion of strong ionization from shocks or AGN into the model increases the predicted He II emission, but it does so at the expense of overpredicting the emission in the other observed lines. Thus, this line remains unexplained.

spectrum of galaxy showing strong emission lines along with a simulated model fit

Figure 3:  The observed spectrum of SL2SJ0217 shown in black, while the best-fit model spectrum is shown in orange. Most emission features are well matched with the exception of the He II line, which is underpredicted. [Berg et al. 2018]

Another item of interest in the spectrum of SL2SJ0217 is its double-peaked Lyman-alpha emission (Figure 4).  Lyman-alpha emission arises when an electron in the n = 2 orbital of a neutral hydrogen atom drops into the n = 1 orbital, emitting a photon with a wavelength of 1216 Angstroms. It isn’t uncommon to see Lyman-alpha emission in a galaxy, but the double-peaked structure is less typical. Luckily, simple models have shown that a double-peaked structure can arise in Lyman-alpha emission when the photons scatter through a spherical or shell-like cloud of gas around a region of star formation. The unequal peak heights can then be attributed an inflow of gas into the cloud. Thus, SL2SJ0217 appears to be hosting an inflow, which could also explain its star formation activity.

double-peaked, red-suppressed lyman alpha emission profile

Figure 4: The double-peaked emission of SL2SJ0217 in Lyman alpha. The red dashed lines show the average velocity range of absorption features in the spectrum (not shown), the black dashed line shows the systemic velocity of the galaxy, while the solid blue line shows the blended Gaussian profiles used to fit the emission. [Berg et al. 2018]

Overall, it is clear that this galaxy has many unique characteristics distinguishing it from others at its cosmic epoch. However, the strong He II emission is unexplained and the authors speculate that better models of massive, metal-poor stars are necessary in order to fully explain the observed nebular emission. If SL2SJ0217 is indeed representative of the very first generation of galaxies, there is still some work do be done before we can understand them completely.

About the author, Caitlin Doughty:

I’m a third year graduate student at New Mexico State University working with Dr. Kristian Finlator. I use numerical simulations to study galaxy evolution during the epoch of reionization, with a focus on metal absorption in the circumgalactic medium.

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