The videos of the talks and panels we recorded have been added to our brand new YouTube Channel. We have also retroactively added the videos to the posts we live blogged during the meeting.

And as a special bonus, here is a time lapse of Thursday’s Poster Session!

This talk session is all about planet formation, and is co-chaired by Rachel Worth and Kimberly Cartier. This blog post has been written by Ben Nelson.

Planet Formation in Binary Systems - how Solid is the 1 km Barrier? (Kedron Silsbee, Princeton)

There are two types of binary gemoetries: S-type (circumprimary) and P-type (circumbinary). Binary planet formation is difficult. Planetesimal eccentricity gets excited to high levels and leads to high collision velocities (~1km/s). This problem isn’t as bad when the binary and planetary semi-makor axes are very different. Maybe planet migration helps? They want to know where the planet disks form in the binary.

Stellar binaries can induce secular perturbations in a non-Keplerian potential and an eccentric disk can arise. Disk gravity dominates eccentricity excitation and precession of the free eccentricity throughout much of the disk. Small planetesimals get aligned with the disk. Large planetesimals end up on orbits dictated by the gravity of the disk.

A secular resonance (same time averaged precession rate between two objects) due to the combination of disk gravity and binary gravity at a few AU makes planetesimal coagulation very difficult at those separatons. In situ planet formation in Kepler-16 like systems is difficult even under the most favorable disk assumptions without invoking several km.sized initial planetesimals.

Effects of Disk Photoevaporation on Planet Migration (Alexander W. Wise, University of Delaware)

In type-II migration, material entering a gap formed by a giant planet interacts with the outermost resonances. The asymmetrical strength of the inner and outer resonances drives the giant planet inward. Alexander is looking at how photoevaporation erodes the surface density of the disk and how that affects migration of the planet. Depending on what part of the disk gets eroded, the planet can stop migrating (outer resonant locations) or migrate even quicker (inner resonant locations get eroded).

Vortices in Dead Zones of Protoplanetary Disks (Ryan Miranda, Cornell)

Deadzones in protoplanetary disks (areas with suppressed angular momentum transport) exist in the midplane from ~0.1 to at least several AU. Rossby wave instabilities occur at axisymmetric “bumps in inverse vortensity. Dead zones are a convenient way of producing this bumps and therefore an instability since they are MRI-inactive.

Simulations start off with a smooth disk then mass piles up in the dead zone. “Modes” form and move at slightly different frequencies, causing them to catch up and merge with each other. Visocity parameter “alpha” > 0.04 - 0.07 suppresses these instabilities. Anticyclonic vortices trap dust grains which can result in rapid planetesimal formation.

Dynamical stability of imaged planetary systems in formation: Application to HL Tau (Daniel Tamayo, University of Toronto)

ALMA got this spectacular image of concentric gaps in the HL Tau disk. Are we really seeing giant planets forming in each of these gaps? Probably can’t stick one in ALL of them. An instability occurs on rapid timescales (~10^5 years)

Neptune mass objects won’t create an instability but then again aren’t massive enough to carve these gaps. It turns out, the outer three gaps are in locations associated with resonances with the inner gaps. But the gaps are eccentric! This can arise when planets’ eccentricities are caught between being excited from a MMR and being damped from the disk. Perhaps the planets got caught in resonance and grew around the same time.

After the disk dissipates, these giant planets can scatter off one another to ejection/high eccentricities. So HL Tau system as we know it might not be long lived. This could explain all those RV planets with high eccentricities.

Formation of Misaligned Hot Jupiters in Stellar Binaries (Kassandra Anderson, Cornell)

There are a lot of Hot Jupiters with significant star spin - orbit misalignment. One way of forming this is through a hierarchical triple system (planet at ~few AU and binary at ~100s of AU). If their mutual inclination is >40 degrees, the perturbations of the binary cause the planet’s inclination and eccentricity to oscillate with the conserved quantity sqrt(1-e^2)*cos(i). This is the Lidov-Kozai mechanism.

During these Kozai cycles, what’s the stellar spin doing? It’s definitely not sitting there. The spin angle chaotically evolves but eventually settles to a constant value as the planet’s orbit decays. From population synthesis models, the fraction of systems resulting in a Hot Jupiter depends on the planet mass. Distribution in spin-orbit angle is always bimodal for Jupiter mass planets. Higher mass planets are typically more misaligned. It’s difficult to produce Hot Saturns by Lidov-Kozai.

Chaotic Dynamics of Stellar Spin Driven by Planets Undergoing Lidov-Kozai Oscillations (Natalia I. Storch, Cornell) Conveniently continuing from where Anderson left off! Can the stellar spin axis keep up with the planet orbital axis? If planet’s orbital axis precesses rapidly, star sees this as a “time-averaged” spin axis, so spin axis precesses slowly (“non-adiabatic”). If planet’s orbital axis is slow, the opposite effect happens (spin axis precessing rapidly, “adiabatic”).

So how is the chaotically evolving explained axis explained? Chaos is often a consequence of overlapping resonances. We can use Hamiltonian perturbation theory and get a resonance condition: averaged stellar spin precession = integer multiple of eccentricity oscillation rate.

So what about the bimodality in the spin - orbit axis distribution? As planet’s semi-major axis decays, you go from the “non-adiabatic” case to “adiabatic” case described above. Bimodality is the result of interaction with the N=0 resonance during this transition.

Eccentricity Excitation of Giant Planets: Shedding Light on the Eccentricity Valley (David Tsang, McGill University)

How do disks affect eccentricity? You can think of it as changing the energy - angular momentum ratio. Outer Lindblad resonances like to pump eccentricity, inner Lindblad resonances like to damp eccentricity. If a gap is cleared, inner Lindblad resonances go away, but non-co-orbital corotation resonances damp eccentricity. Gap heating can cause eccentricity excitation.

Let’s jump to a planetary census. There seems to be a lack of giant eccentric planets around low metallicity stars. Disk self-shadowing can prevent gap heating. No gap heating, no eccentric planets, an explanation for this paucity of eccentric giant planets.

Note: you can’t just assume eccentricity is zero for giant planets when starting post-disk evolution.

The Habitable Zones of Pre-Main-Sequence Stars (Ramses Ramirez, Cornell)

Pre-main-sequence M-stars are many times more luminous than main-sequence and this part of their lifetime is very long (up to 1 Gyr). For the pre-MS Sun, the outer edge of the habitable zone is around 2.5 AU. HZs for these larger luminosity stars are put further out, which would make it easier to directly resolve these planets.

Some complications. Long-lasting runaway conditions are triggered during pre MS-on Venus, Earth, and Mars. M dwarfs will have smaller disks so planets won’t be able to accrete more volatiles. But late heavy bombardment can replenish water on planet’s surfaces.

And that’s all folks! The only things left to do for this are clean up (boo!) and dinner (yay!)

For those of you who tuned in to the live blogging, thanks for faithfully reading my words. I hope that you took as much away from this that I got writing it, and hopefully I will see you in the future at the 2016 ERES at Cornell! Good night!

-Kimberly Cartier, AstroLady

Our post-lunch session is chaired by recent PSU PhD, Dr. Benjamin Nelson. These talks are all related to characterization of exoplanet systems using statistical methods.

Systematics-insensitive periodic signal search with K2 (Ruth Angus, University of Oxford)

When the second reaction wheel of Kepler failed, it was recommissioned as the K2 mission. The issue with the K2 mission is that the telescope itself drifts slowly, and they need to fire the thrusters every so often to fix this issue. That mean that, as the star appear to be drifting across the CCD, the precision of K2 has decreased compared to its predecessor.

To compensate for this, they need to come up with a better analysis algorithm for the K2 lightcurves. This involves better modeling of the stellar systematics and convolving that with a sine wave over many many frequencies to create a systematics insensitive periodogram (SIP). The raw periodogram of K2 data shows a very large feature at the 6 hour thruster times along with aliases of that 6 hour frequency. When they redo the lightcurve periodogram with SIP they are able to remove that large systematic feature and pull out the red giant acoustic oscillations of the host stars.

Using SIP, you can also find a better estimation of the stellar rotation period, since the systematics won’t be clogging up the periodogram anymore. They were able to accurately recover the stellar rotation period once the systematics were removed from the lightcurves using SIP. They can also use this method to find other periodic signals like short period exoplanets, RR Lyrae, and eclipsing binary stars. Their code is available on GitHub (don’t use the tweated version!), and the paper recently came out on the arXiv.

A Catalog of Transit Timing Posterior Distributions for all Kepler Planet Candidate Events (Benjamin Montet, Caltech/Harvard)

Ben is working on a number of projects, including a transiting brown dwarf LHS-6343 and a paper on young M-dwarfs. Today he is talking about transit timing variations (TTVs) (which Daniel Jontof-Hutter talked about yesterday). TTVs can ell us about eccentricities, inclinations, and mass ratios of planets in the same system, all of which can be really difficult to measure using another method.

When looking at TTV curves, the variations in transit timing usually follow a sinusoid, but not all points follow this trend. The current methods ignore non-Gaussian errors, assume white noise, ignore ill-fitting transits, short cadence data, and don’t marginalize over transit shape (if the transit is not properly sampled, current methods usually ignore these points). But correlated noise matters too, and needs to be included in analyses.

Posteriors can help with this. If you fit many transit model models and times of transits, infer the posterior distribution for the time of every transit observed with Kepler, you can use importance sampling to get a handle on correlated noise. Importance sampling can help speed up your computation process bu focusing your computation on places in your data that you know, a priori, that the transits will be occurring. They are currently working on all of the single-transit systems, and multiple systems are nearly ready for “prime time”. They are also looking for a cool name for the project, so give him a shout if you have an idea.

Towards a Galactic Distribution of Exoplanets (Matthew Penny, Ohio State University)

Where are the known exoplanets? Microlensing is the only technique we currently have for probing for exoplanets in multiple areas of the galaxy. RV surveys are limited to nearby stars, Kepler looked in one region, K2 will add a ring around the solar system with more nearby targets, but microlensing surveys look straight into the galactic center to find the frequency of exoplanets as a function of galactic radial position.

Question: does plane formation in the bulge differ from the disk of the galaxy? Different galactic environments can have detrimental effects on the longevity of a protoplanetary disk, or can change the temperature of the protoplanetary disk to impede planet formation. They find that, based on microlensing surveys, there are a lot fewer planets in the galactic bulge than in the disk. They determine this by varying the ratio of disk planet formation efficiency to bulge planet formation efficiency to model the current distance distribution of microlensing planets. They find in their first results that the bulge planet formation efficiency must be lower than the disk planet formation efficiency in order to approximate the microlensing planet distance distribution that they see.

They want to find out what is the most probable distance/location in the galaxy to find exoplanets. They can measure distances to microlensing planets with parallax (for nearby planets), using a Bayesian method, or using the relative proper motions of stars to calculate the distances. While there are still some kinks to work out, this mix of techniques lets them probe a wide range of planet distances and begin to map the galactic distribution of exoplanets.

Constraining the Demographics of Exoplanets Using Results from Multiple Detection Methods (Christian Clanton, Ohio State University)

There have so far been about 150 confirmed exoplanets around M-dwarf stars. Confirming these planets really takes a collaborative effort between multiple detection methods. M-dwarfs are good targets for exoplanets because they are the most numerous of stars in the galaxy, RV and microlensing surveys are also more sensitive to lower-mass stars.

There have been individual exoplanet censuses of M-dwarfs using separate methods. Some constrain the actual frequency of planets around these stars, other non-detections (direct imaging) place upper limits on this number. If they combine the results from these various techniques (microlensing + RV, and now direct imaging), they can confirm quite a few planets around M-dwarfs and get a constrain on long-period giant planets around these stars. They ask: is there a single planet population distribution that is consistent with all of these M-dwarf exoplanet surveys?

They map the distribution of planets into distributions of the observables relevant to each technique (microlensing+RV+direct imaging). They then determine the number of expected detections for each survey, and compare that with the actual reported results and determine a likelihood of that particular planet population, and repeat for a variety of planet populations. They can then constrain the planetary mass function and power law slope of this distribution very well for M-dwarfs. What this means is that the results of the microlensing, RV, and direct imaging surveys are consistent with a single planet population distribution. They also want to include the results from Kepler to add constraints from transit surveys as well.

Sifting Through the Noise - Recalculating the Frequency of Earth-Sized Planets Around Kepler-Stars (Ari Silburt, University of Toronto)

Kepler has been invaluable in attempting to answer the age-old question of: is our planet unique? Unfortunately, we haven’t yet found a true Earth-analog. We can estimate the frequency of Earth-like planet by extrapolating our results past our detection biases. We first have to overcome our geometric bias: only certain planetary systems are transiting, and there’s a large population of planets that we simply don’t see in transiting surveys because of this detection bias. This is a strong function of planetary radius and orbital semi-major axis.

This bias causes a lot of large error bars and false-positives in the Kepler data - mainly because we don’t understand the stars themselves. Such large error bars can skew our estimation of the number and frequency of Earth-sized planets. What they’ve done is a new way of accounting for the uncertainty in planetary radius by applying our known Kepler detection probabilities for planets based on their radii and combining that with the probability curve of the planet size. For example, the uncertainties of a detection may include a very small size, but we know that detecting something that small is very unlikely, so that value is downweighted. This allows them to correct our error distribution and use this to improve our estimate of the frequency of Earth-sized planets.

They find that with these corrections, the frequency of Earth-sized planets in the Kepler sample is eta_Earth = 6.4%, which is about half of what it would be if they haven’t accounted for the detection biases of Kepler. They anticipate that the Gaia spacecraft will help better understand the stellar exoplanet hosts, which will further increase the accuracy of their eta-Earth value.

A population-based Habitable Zone perspective (Andras Zsom, MIT)

Most people visualize a habitable zone as a stripe around a star that is capable of supporting liquid water. If you look at it in a population perspective, you can see which planets fall interior to the HZ and are covered in water vapor, those exterior to the HZ with ice on their surface (or like Mars that falls right on the ice/vapor limit), and those inside the HZ which can have liquid water.

From observations we have good estimates on the stellar properties and planetary orbital properties, but we don’t know much about the planet properties and surface climate. How can we know the surface climate without knowing the planetary atmosphere? They describe the HZ as a probability function to estimate the occurrence rate of HZ planets based on this HZ probability. If you treat the stellar and planet properties as random variables, you can create probability density functions out of them. They then sample each variable and use a 1D climate model to calculate the surface climate, repeat this to create an ensemble of climates, and then study the habitable sub-population and calculate their probabilistic HZ.

They find that the most probable area of HZ planets around M-dwarfs occurs around a few times the radius of the Earth, and around 0.5-1 times the stellar flux received at Earth (author’s note: this is a really cool 2D HZ probability plot!). So, they find that the occurrence rate of HZ planets is 0.001-0.3 planet/star for M-dwarfs, but that the surface pressure and atmosphere type strongly impact the surface climate and occurrence rate. We need better estimate of the potential atmospheres of exoplanets. Their code is called HUNTER and is available on GitHub.

The session following the coffee break will be co-chaired by me (Kimberly), so that blog post will be written by Ben Nelson.

A very critical issue for many (most) early career scientists is “impostor syndrome” (IS), which is defined as “an internal experience of intellectual phoniness despite external indications of success” (Clance P, Imes S. The impostor phenomenon in high achieving women: dynamics and therapeutic intervention. Psychotherapy: Theory, Research and Practice. 1978;15:241-247). PSU Astronomy professor, Jason T. Wright, is speaking about impostor syndrome, how it applies to you, and the effects and symptoms of IS.

We asked Jason to give this talk, and at first he seemed a bit surprised, and perhaps felt unqualified to give this talk. But, perhaps, this is the hallmark of IS. Jason agreed, however, did a bunch of research, and now feels ready to give this talk to us all.

Who is this IS talk for? Those who suffer from IS are often unaware that they do, and so those people need to be educated so that they can overcome it. If you have students, you should also know about this, since your students and advisees may have IS.

IS was first quantified in 1978 as “impostor phenomenon” and only applied it to successful women, those who, despite numerous accomplishments in their field, persisted in thinking that they weren’t skilled enough for the job that they have and were only fooling their peers into thinking that they belonged.

Jason anonymously surveyed ERES participants about their own thoughts and experiences with IS before the conference. His results show that most participants believed that around 70% of their peers have been affected, at least mildly, by IS (they included themselves in that percentage). This is a persistent and widespread phenomenon, and we need to educated ourselves about this more.

IS is…
- a mismatch between external evidence of accomplishments and self-image
- feeling fraudulent or phony, having achieved success not though general ability
- a distorted, unrealistic, unsustainable definition of competence
- a fear of being “discovered” not to be worthy of position or honors
- feeling of having deceived others to achieve position

All people, regardless of their accomplishments in life (like Jodie Foster and Meryl Streep) can be susceptible to IS. But, this can apply even to the “Meryls” of science. Or the supporting actors of science. Jason gives a poignant example in the form of John Asher Johnson (with Dr. Johnson’s permission of course), quoting Dr. Johnson’s own talks and feelings of IS.

What are some of the misconceptions that contribute to IS?
- success is primarily dye to extreme amounts of narrow technical competence (“The Cult of Smart”)
- competence is a fixed trait that some people have others do not
- the most successful, competent people are perfectionists who never make a mistake and who never take on a problem without the necessary preparation

Well…none of these are actually true statements! Academic and research success is not based on any one quality, but rather exists in multiple dimensions. These include: the ability to identify important and answerable questions, the adeptness at basic complex problem solving, the ability to persevere on a problem, the possession of knowledge and skills, curiosity, luck (whether random or manufactured), and communication. This list comes from Ed Turner and Scott Tremaine, and is expounded upon by John Johnson on his own blog post.

The point of this is that success in academia is a constantly evolving process, and it acquired from this set of skills that improve and evolve with practice. No one gets everything right the first try (or even the hundredth!). Most academics work on problems that are outside their area of expertise, and take that risk of mistake in order to work on something interesting or valuable.

How can you begin to overcome IS? It’s something that you can do something about, both for yourself and for others. Talk about it! Normalize it! It happens to everyone, so there is no shame in feeling it. Try to emulate the the personality traits of people you look up to (“fake it until you make it” or “try to live the dream”). Find supportive people to talk to and to discuss the problem. Make note of the nice and complementary things that people say about you: make a file, save them, refer to them, and BELIEVE IT!

IS contains within it some inherent double-standards. You think that your own successes are due to luck or deceptions, but everyone else’s successes are due to skills. You respect your peers’ and superiors’ judgments and knowledge – except when it’s about you. Also…you think so highly of yourself that you can deceive everyone you meet, but you don’t have enough skill to do what you’re trained to do. Acknowledge these logical flaws and use them to combat IS.

IS is not a recognized mental disorder, but happens to everyone. This phenomenon occurs across all demographics, no one is immune. If someone comes to you to talk about this, don’t brush it off, don’t shame it, be supportive and have an open discussion. Learning to combat IS, both in yourself and in others, is something that can only benefit this community at large.

This session is our “Alternate Career Panel,” where we’ve invited three speakers who have all completed an astronomy PhD and then chosen to enter a career outside of a large, research-based academic environment. Our three speakers will be providing their perspectives on careers in a smaller academic environment, industry, and science policy.

Note: as Kimberly is moderating this panel, your blog post for this session is written by Robert Morehead.

Our speakers are:

Eric Jensen (EJ): is a Professor of Astronomy at Swarthmore College. He holds a BA in Physics from Carleton College, and a PhD in Astronomy from the University of Wisconsin-Madison.

Josh Shiode (JS): completed his PhD research at the University of California, Berkeley. He is currently the Senior Government Relations Officer at the AAAS. Josh was also the John N. Bahcall Public Policy Fellow of the AAS.

Daniel Angerhausen (DA): received his PhD from the German Sofia Institute. He then moved on to a postdoc at RPI, and is now an NPP fellow at Goddard. He in the n the process of starting up a company that he will tell you more about.

Dave Spiegel (DS): received his PhD in Astronomy from Columbia University, and subsequently took postdocs at Princeton and at the Institute for Advanced Study. He now works as an R&D Data Scientist at Sum Labs.

Last minute substitution - Daniel Angerhausen (DA): has graciously agreed to join the panel at the last minute to fill-in for Dave Spiegel, who was not able to join us.

Opening Remarks

(JS) Decided that research wasn’t a good fit. Looked for science education, communication and policy after grad school. Won the Bahcall Fellowship and got into science policy. Works primarily on policy for science, basically how we get our funding. If you are good at communication, policy can be a great fit for you. .

Q:What did you wish you had known before you got on your current path?

A:How to apply for jobs and what career options were available.

(EJ) Feels a little strange being on alternate career panel, since he is a college professor. He works at 1,600 undergraduate institution, no grad students. Balance between research and teaching can vary greatly over the continuum of academic jobs from small colleges to R1.

It’s a challenge to balance out time between teaching and research. Time management is very important and a continuing challenge.

(DA) Almost left science at the end of his graduate program. Don’t be too focused and try for broad opportunities. Networking is vital, get your name out there! Currently in the early field of starting a business in science communication.

(JS)back to what did you feel was most helpful to you in crystallizing your decision to pursue the career path that you choose?

A: I got several mentors outside of my department. They helped me broadening my horizons, outside voices may not be as invested in you staying in academia. Informational interviews are great to cultivate other opportunities.

What are skills that you learned in your education that have been really useful to you later?

(EJ) Writing and communicating

(JS) I agrees, also how to collaborate with others, but as a leader and a follower. Your critical thinking skills will be better than average.

(DA) Communicating. Also don’t worry.

Teaching at liberal art colleges, what are the ranks and what is the typical teaching load?

(EJ) Most US institutions have the three typical ranks, assistant, associate, full. Teaching loads vary. At Swarthmore it is two classes a semester, community college can be as many as five a semester, R1 often one per semester.

How important is prior teaching experience?

(EJ) First I look of that the candidate knows what they are getting into. Teaching experience is valuable, especially if you can narrate you own role. Leading your own class is better than just being a TA. Multiple years have diminishing returns.

How many applications are rehashed R1 applications and do you have to do a post doc?

(EJ) Strongest applications are those that have done a post doc. Shows you can do a post doc. Maybe a quarter look like rehashes.

How much is there an expectation that you are doing research or is there a range?

(EJ) There is a trend towards more research at 4-year liberal arts colleges, but the criteria is often showing evidence that you are engaged in scholarship, rather than bringing in grant money.

What is the best way to network to get a post doc?

(DA) Communication and start early. Go to meetings, talk to people. Not all of the jobs are on the AAS job register a lot are word of mouth.

Post docs often have teaching experience early as a grad student, is lack of recent experience a problem?

(EJ) Being a lead instructor once while in grad school or as a post doc is one of the best things you can do.

For JS, how is my AAAS different from AAS?

(JS) The AAAS position is not a fellowship. But AAAS has a large fellowship program. A lot do program management. 30 go to congress as aids. My job is now a senior government relations position. I talk to policy makers.

For JS, are there positions with research and science communication?

(JS) The Bachal fellowship can be up to 20 percent your own research. There are other jobs like that as well, and also the NSF post doc fellowship. 40 percent of AAAS fellowships go back to research.

(DA) Most NASA missions have Education and Public Outreach positions. 50/50 research and science communication.

Is it harder to teach politics to scientists or science to policy makers?

(JS) That’s the wrong way to think of it, we tend to talk AT people. Policy makers need the advice of experts. They can’t be an expert on everything. They are ready, they need to be communicated with.

(EJ)This applies to teaching too, the best approach is to motivate others to learn.

For JS, what other jobs are available at non-society groups, like NGOs.

(JS)There are many places you can work in policy, university institutes, think-tanks, etc.

How can students and advisors find contacts out of academia.

(JS) The alumni association/fund-raising office may be an useful resource to keep in contact with people who have moved out of academia.

For students, ask the people you do informational interviews with for more contacts.

(DA) Be sure to be honest about your actual skill sets. You know a lot!

(EJ) For faculty, keep in track of our former students. It gives a range of trajectories and contacts.

Do you feel you have let people down by leaving academia?

(JS) My advisor/committee was very supportive, but there are probably others who look down on the choice.

(EJ) Most people have been supportive

(DA) Your supervisors are aware of how hard it is to navigate the academic job market.

Comment from Audience The AAS has a lot of alternative career resources. Also Jobs for Astronomers Facebook group, and Astronomers Beyond Academia on linkedin.

(EJ) Please feel free to contact me