Category Archives: news

Prize established for astronomy research software at UMD

This week, we saw another example of the importance of software in astronomy research. We are pleased to announce the establishment of an annual software prize from the UMD Astronomy Department for research software written by a registered undergraduate or graduate student while the student was at University of Maryland, College Park. The source code of the software must be open and assigned an acceptable open source license.

The prize consists of a certificate and a cash award, which will be presented at the Astronomy Department annual award ceremony. We reserve the right to withhold the prize if the criteria are not sufficiently met.

More details will be available later; if you would like additional information, please contact us.

Peter Teuben, teuben@astro.umd.edu
Alice Allen, aallen@ascl.net

 

February and March 2019 additions to the ASCL

Twelve codes were added to the ASCL in February, 2019:

dyPolyChord: Super fast dynamic nested sampling with PolyChord
ExPRES: Exoplanetary and Planetary Radio Emissions Simulator
GraviDy: Gravitational Dynamics
LiveData: Data reduction pipeline

LPNN: Limited Post-Newtonian N-body code for collisionless self-gravitating systems
PINT: High-precision pulsar timing analysis package
PyMF: Matched filtering techniques for astronomical images
Radynversion: Solar atmospheric properties during a solar flare

RPFITS: Routines for reading and writing RPFITS files
SNTD: Supernova Time Delays
Specutils: Spectroscopic analysis and reduction
SpecViz: 1D Spectral Visualization Tool

And sixteen codes were added to the ASCL in March, 2019:

allesfitter: Flexible star and exoplanet inference from photometry and radial velocity
AsPy: Aspherical fluctuations on the spherical collapse background
brutifus: A Python module to post-process datacubes from integral field spectrographs
DAVE: Discovery And Vetting of K2 Exoplanets

GalIMF: Galaxy-wide Initial Mass Function
Galmag: Computing realistic galactic magnetic fields
HelioPy: Heliospheric and planetary physics library
ICSF: Intensity Conserving Spectral Fitting

NFWdist: Density, distribution function, quantile function and random generation for the 3D NFW profile
NIFTy5: Numerical Information Field Theory v5
PLATON: PLanetary Atmospheric Transmission for Observer Noobs
PRF: Probabilistic Random Forest

SimSpin: Kinematic analysis of galaxy simulations
SIXTE: Simulation of X-ray Telescopes
SPICE: Observation Geometry System for Space Science Missions
SpiceyPy: Python wrapper for the NAIF C SPICE Toolkit

Research Data Alliance Plenary 13 presentation

The ASCL is participating in the Research Data Alliance (RDA) meeting currently underway in Philadelphia, PA. The Plenary 13 meeting motto is “With Data Comes Responsibility.” Indeed! Among the sessions of special interest for software folks was yesterday’s Interest Group meeting on Software Source Code and today’s first meeting of a new Working Group on Software Source Code Identification. The Working Group is led by Roberto Di Cosmo, who is a founder of Software Heritage, Martin Fenner from DataCite, and Daniel Katz from the University of Illinois. This initial meeting is titled “Identifying, referencing and citing the source code of research software: a state of the art.” The ASCL is doing a short presentation that focuses on a few of our practices, how we do them, and the rationale for them; this includes what we do when we process a submission, what metadata for software we do and don’t have and why, and some of our curation practices. Our slides for this presentation are available below.

Photograph of Alice presenting a slide

Photo courtesy of @StephvandeSandt

Our attendance at this meeting was made possible with support from Software Heritage; our thanks to that organization!

Slides (PDF)

The ADASS Time Domain Astronomy Hackathon, part 2

This is a continuation of a previous post, and was written by Brian Thomas, Alice Allen, Marc W. Pound, and Peter Teuben.


Lessons Learned
As this was the first such event of this type for ADASS we were unsure of the outcome, as it was somewhat of an experiment. We share some lessons learned for future events.

  1. Provide a list of interesting problems and related clean data. Doing so helps to bootstrap project ideas, as not all participants will have enough domain background to start quickly.  Because the event was so short, it was helpful to provide microservices and point to  datasets that were more or less cleaned and ‘ready to go’ for projects directed at these problem areas.
  2. Develop a marketing plan. We could have done a better job to garner interest in the event. We posted to a community BBS, a UMD subreddit, posted paper flyers in campus science and engineering buildings, and contacted student groups and faculty to help spread the word. However, we did not have a coordinated campaign that included social media and messaging targeted for specific dates and groups (e.g., “Save The Date” emails), nor was the hackathon mentioned in the ADASS registration form. A competing, large, all-women hackathon (https://gotechnica.org/) held the same weekend on campus also affected our enrollment.
  3. Venue (location and time) is important. The university was a good choice because of easy access to rooms, wifi, and food choices. Holding the hackathon at a large academic institution ensured that it would be easy for younger participants (undergrads) to attend, as did holding the event over a weekend to avoid conflicting with classes.
  4. Have an assessment tool/strategy. An exit survey or ending discussion with participants can help improve subsequent hackathons. We failed to take advantage of the opportunity to engage either the participants or the ADASS audience at the session where winning projects were presented about perceived problems and good aspects of our event.
  5. Narrow the range of participant experience. Future organizers should consider either limiting participation to non-professionals, or group the participants and awards into professional and non-professionals. It is somewhat unfair to have less experienced coders compete against domain specialists and possibly contrary to the avowed desire to use this event to advertise our field of work to outsiders.
  6. Time management is crucial. Scheduling a conference event right at the end of the hackathon was problematic, and not tightly managing the final presentation time and similar issues became important and detracted from the event. This will be particularly important in other events that have larger participation.

Conclusions
A community lives and dies by how well it nurtures the next generation. Folks enter the ADASS community by a number of means but typically by being either scientists who become attracted to the technical challenges of writing the software or as computer engineers and programmers who find the science use cases particularly interesting. We are not aware of any organized means to train the next generation of ADASS workers; there are no formal degree programs in “Astronomy Software.” As such, our community has taken a somewhat laissez-faire approach to training the next generation and this may lead to a future deficit in skilled professionals willing to work in our field. More and more our community’s skills are being found useful in application elsewhere; for example, many ADASS attendees can easily become highly sought after Data Scientists.

Hackathons are a step towards being more proactive in our outreach and provide an ideal means to encourage and interest a younger group of programmers in the complex and interesting challenges that our community tackles. We found a number of lessons in hosting this event but no showstoppers, and a good deal of goodwill was generated. Based on our experience, we heartily recommend that future ADASS events include hackathon events.

Acknowledgments. We would like to thank the City of College Park for providing the prize money, Vigilante Coffee for supplying much needed coffee, ASCL for providing snacks and the University of Maryland Astronomy Department for hosting the hackathon.

The ADASS Time Domain Astronomy Hackathon, part 1

This post was written by Brian Thomas, Alice Allen, Marc W. Pound, and Peter Teuben, and, with part 2, will appear in the ADASS XXVIII proceedings.
Brian is with the Office of Chief Information Officer, NASA HQ, Washington DC; Marc, Peter, and Alice are in the Astronomy Department at the University of Maryland in College Park, MD.


In this post, we describe the ADASS XXVIII hackathon, the first associated with an ADASS conference, and provide our motivation and the details of the event. A subsequent post discusses the lessons we learned from holding this event and our conclusions about it.

Introduction
A hackathon seeks to draw together a large group of folks for an intense and extended period  of creative programming. Hackathons may be held for a variety of purposes including, but not limited to, teaching (Huppenkothen et al. 2018), to draw together a technical community as a social event (Kellogg et al. 2019), and to draw attention to solving particular challenges or themes (as found, for example, on popular sites such as Kaggle). Pa Pa Pe Than et al. (2018) provides a broader overview of hackathon applications and uses.

Our motivation for holding a hackathon associated with the ADASS XXVIII meeting was aligned with outreach to interested individuals; we wanted to highlight topical technical problems that the ADASS community might be concerned with and introduce a new generation of rising computer programmers and scientists to the excitement of solving them. We chose the topic area of Time Domain Astronomy (TDA) to focus on for this event as it was also one of the themes for this year’s ADASS meeting and aligned well with the interests of the Department hosting the hackathon. We allowed a loose definition of TDA, dealing with any astronomical data where time was a parameter. Thus projects for this hackathon could involve, for example, variable stars, exoplanets, and bodies in the solar system.

Event Organization
The ADASS hackathon took place the weekend before the ADASS starting on Saturday morning and ending at noon on Sunday with the total event time being 27 hours. We provided a space in the University of Maryland Physical Sciences Complex (PSC) as well as snacks and coffee. The participants were required to attend the introduction and be present for final presentations at 11am on Sunday. Otherwise, they could stay in the PSC building or leave as they desired. A cash award (provided by the City of College Park) was available for the top 3 teams with $500, $350 and $150 being awarded to the first, second and third place teams respectively. The winning team was also provided time to present their hack during the ADASS meeting.

We began by having the participants introduce themselves, their backgrounds and interests. We then introduced the participants to the field of TDA, providing some general background and challenges in this area. Presentations were given by Charlotte Ward (UMD graduate student), Gerbs Bauer (UMD Research Professor), and Brian Thomas (NASA). We highlighted some datasets which could be applied to solving aspects of the challenges. This was followed by a freely flowing brainstorming session where people could discuss ideas and questions, and potential hacks could be focused. Ideas were placed on sticky notes on a wall. Participants were then allowed a short period of time to form teams and brainstorm. After another hour or so, each team presented an outline of their hack, potentially allowing members to join another team if skill sets were better suited elsewhere. In our case nobody decided to join another team.

We allowed for a range of project types. Projects could be new analyses or approaches or novel ways of understanding existing solutions or problems. The final product could be a proof-of-concept app, a plugin to existing code, a storyboard design, or really anything that embodies creative hacking around the TDA theme. We did not require that the final project be polished; a good idea that was well fleshed out could also be submitted. A final presentation of a few slides describing the work including the motivation and approach was the only requirement for consideration for a prize.

We used Devpost to help structure the hackathon. This site served as a centralized location from which information could be disseminated including rules of conduct and a discussion board which we used to distribute ideas and answer participant questions. Hackathon rules can be summarized as follows:

  • Each participant belongs to one team and one final submission, but is allowed to switch teams. Team makeup is not final until the presentation. The maximum team size was 5.
  • Only 1 submission per team.
  • A Code of Conduct. We did not tolerate harassment of hackathon participants in any form, including, but not limited to, harassment based on gender identity and expression, age, sexual orientation, disability, physical appearance, body size, race, ethnicity, nationality, religion, political views, previous hackathon attendance, lack of computing experience, or chosen programming language or tech stack. Sexual language and imagery was not appropriate at any point in the hackathon including in software hacks, social media, talks, presentations, or demos.

Hackathon participants violating any of these rules could be sanctioned or expelled
from the hackathon at the discretion of the hackathon organizers.

Participants
Our event was set up as a community hackathon and attracted students, professional hackathonners, and ADASS participants who formed teams (see below). Members of the hosting department and the ADASS program organizing committee served as judges. Out of the 34 original registrations, 6 were present but not playing (being part of the organization or just cheerleading), and 9 did not show up.

Judges, Organizers, and Teams
The session was organized by Peter Teuben, Brian Thomas, Alice Allen, Marc Pound, and Elizabeth Warner. Our judges were Alice Allen, Gerbs Bauer, Andy Harris, Nuria Lorente, Ada Nebot, and Brian Thomas. The 7 teams that participated are listed in Table 1. We have also noted which teams won which prizes.

Team members Project name
Sarah Frail and Patrick Shan Morpheus – Near Earth Objects Visualization
Marco Lam Drag and drop ensemble (2nd prize)
Paul Ross McWhirter and Josh Veitch-Michaelis Auto periodogram selection using MC (3rd prize)
Timothy Henderson and Matt Graber Solar Activity Viewer
Thomas Boch, Matthieu Baumann, and Siddha Mavuram Music of Light curves (1st prize)
Kyle Kaplan, Sankalp Gilda, Hayden Hotham, Steve Gambino, and Abbie Petulante ML on ZTF pipeline
Kevin Cai, Kael Lenus, James Zhou, and Justin Otor Fixed and Variable Time Kepler Viewer in WWT

Table 1. Hackathon Teams

The winning team “The Music of Light Curves” made their hack, the sonification of variable stars from the Gaia catalogue, available on https://tboch.github.io/music-lightcurves-hack/. Their presentation to the ADASS audience during the TDA session on Wednesday met with resounding applause (and later a mention in the international press).


Continue to Part 2, Lessons Learned and Conclusions

A visit to NASA’s Goddard Space Flight Center

Photo showing slide of new journals friendly to astro computing articles started since 2012

At the podium

Although I was born in Washington, DC and have spent most of my life in its Maryland suburbs, yesterday was my first time on the Goddard campus (aside from its Visitor Center, which I’ve been to many times), this despite having two family members and many friends who used to1 or do work there. I was excited! And I had a great reason for going: I was presenting a talk to the Astrophysics Science Division titled “Make your research software famous! (or at least discoverable).” The talk, broadcast on a NASA UStream channel and recorded for future viewing,2 covered a bit about our research on source code availability in astronomy, and also covered our current project to make NASA astro research software more discoverable, what the Astrophysics Source Code Library is and how it improves research transparency, software citation, and recent changes in publishing with regard to software that, combined with other changes in the community and science in general, make it easier than ever before to make one’s astro research software discoverable. The slides I presented are available for download (PDF), and links to different resources, journals, and organizations that I mentioned in the talk are also available.

Kristin Rutkowski, along with Tess Jaffe and Alex Reustle, hosted my visit to GSFC; I had met both Kristin and Tess at last year’s ADASS conference in College Park, where we had our first conversation about my visiting the site to talk about the ASCL. Yesterday’s audience was great; they were involved and asked a lot of excellent questions, about copyright, code authors not receiving credit for the software they write, how we handle dead links, mutable author lists, NASA policies regarding software release, and how the ASCL is funded. Some of the questions came from people attending remotely and were asked online; Alex made sure these were covered, too. Alex is also involved in making the video of the talk available online, and when it is available, I’ll update this post with its link.

Photo of NASA's Space Environment Simulator

Space Environment Simulator

After my presentation, Kristin and Tess took me to see some of the NASA labs and equipment, including the Space Environment Simulator Facility, the JWST/OTIS Vibration Test System, the currently out-of-service High Capacity Centrifuge, and the Acoustic Test Cell. We went through doors marked “Authorized Personnel Only”!! This is one of the perqs of working on the ASCL — I become “Authorized Personnel” when visiting telescopes and labs and such, which, to me, is very cool and exciting! Sure, it’s only for a few minutes and always in the company of others who have far more business being there than I do, but still: very cool and exciting!! After looking at these labs and equipment, Kristin and I said goodbye to Tess, and then drove over to see dinosaur footprints that had been found on the Goddard campus. (Could a visit anywhere be any cooler?!?!)

Dinosaur and small mammal tracks

Science science everywhere! I had a great time at Goddard, and thank Alex and Tess and especially Kristin for hosting my visit!

 

 

 

 

 

 

 

1 Happy retirement day, Janie!
2 No, that’s not nerve-wracking at all, so long as one doesn’t think about it.

Changes on the ASCL, #1

As we mentioned back in June 2018, ASCL editors had been examining the papers listed in the Appears in field and disambiguating these into new Described in and Used in fields, this to better capture the relationship of a mentioned article to the software. Disambiguated links have been appearing in ADS since May 2018, as you can see in this example, with the ASCL entry (as it had been) on the left, and the (classic) ADS screen display on the right:

We completed the disambiguation process earlier this month, and now with the completion of that project, our excellent developer/designer Judy Schmidt (@SpaceGeck) has changed the ASCL entry screen slightly; it now displays the Described in and Used in fields rather than the ambiguous Appears in field.

The entry has changed from this:

to this:

Screenshot showing code entry screen with described in and used in fields

Our reports and data feeds, such as to Web of Science’s DCI and the JSON data dump, have also been changed to show the Described in and Used in fields.

We have a few more screens and forms to change, such as the Submit form, and when these other changes have taken place, we will let you know in another blog post that will be cleverly titled Changes on the ASCL, #2.

January 2019 additions to the ASCL

Twelve codes were added to the ASCL in January, 2019:

bettermoments: Line-of-sight velocity calculation
Bilby: Bayesian inference library
CCL: Core Cosmology Library
cFE: Core Flight Executive

eddy: Extracting Disk DYnamics
Galaxia_wrap: Galaxia wrapper for generating mock stellar surveys
OCFit: Python package for fitting of O-C diagrams
Photon: Python tool for data plotting

SEDobs: Observational spectral energy distribution simulation
ssos: Solar system objects detection pipeline
stellarWakes: Dark matter subhalo searches using stellar kinematic data
unwise_psf: PSF models for unWISE coadds

December 2018 additions to the ASCL

Eighteen codes were added to the ASCL in December 2018:

aesop: ARC Echelle Spectroscopic Observation Pipeline
AUTOSPEC: Automated Spectral Extraction Software for integral field unit data cubes
distlink: Minimum orbital intersection distance (MOID) computation library
easyaccess: SQL command line interpreter for astronomical surveys
ExoGAN: Exoplanets Generative Adversarial Network

Fermipy: Fermi-LAT data analysis package
galclassify: Stellar classifications using a galactic population synthesis model
GENGA: Gravitational ENcounters with Gpu Acceleration
GLADIS: GLobal Accretion Disk Instability Simulation
GRAND-HOD: GeneRalized ANd Differentiable Halo Occupation Distribution

Juliet: Transiting and non-transiting exoplanetary systems modelling tool
Lightkurve: Kepler and TESS time series analysis in Python
OctApps: Octave functions for continuous gravitational-wave data analysis
PFANT: Stellar spectral synthesis code
psrqpy: Python module to query the ATNF pulsar catalogue

PynPoint 0.6.0: Pipeline for processing and analysis of high-contrast imaging data
SPAMCART: Smoothed PArticle Monte CArlo Radiative Transfer
WISP: Wenger Interferometry Software Package

Software activities at AAS 233 in Seattle, Jan 2019

It’s that time of year again when software folks — users and authors alike — dream of all the software activities at the winter AAS meeting. So here is the ASCL’s (abbreviated*) annual round-up to jumpstart your dreams and warm your code-loving heart! If you have items you want added, please let me know in the comments below or send an email to editor@ascl.net. Thank you!

All rooms are in the Washington State Convention Center unless otherwise specified.


SATURDAY, 5 JANUARY 2019
Workshops
Introduction to Software Carpentry (Day 1), 9:00 AM – 5:00 PM; 211
The AAS Chandra/CIAO Workshop, 9:00 AM – 6:00 PM; 204
Using Python to Search NASA’s Astrophysics Archives, 10:00 AM – 11:30 AM; 213


SUNDAY, 6 JANUARY 2019
Workshops
SOFIA Workshop for FORCAST and HAWC+ Data Analysis, 8:30 AM – 5:15 PM; 201
Adding LISA to your Astronomy Tool Box, 9:00 AM – 5:00 PM; 213
Introduction to Software Carpentry (Day 2), 9:00 AM – 5:00 PM; 211
Using Python and Astropy for Astronomical Data Analysis, 9:00 AM – 5:00 PM; 4C-4
The AAS Chandra/CIAO Workshop, 9:00 AM – 6:00 PM; 204
Advanced Searching in the New ADS: On the Web and Using the API, 3:00 PM – 4:30 PM; 304


MONDAY, 7 JANUARY 2019
Splinter meetings
Data Science, 8:00 AM – 6:00 PM, 4C-1
Updates on Implementing Software Citation in Astronomy, 12:30 PM – 2:00 PM; 203
An Open Discussion on Astronomy Software, 2:00 PM – 3:30 PM; 4C-4

Open event
AAS WorldWide Telescope presents: Advances in Astronomical Visualization, 10:00 AM – 11:30 AM; 214

Oral presentations
Session 126. Machine Learning in Astronomical Data Analysis, 2:00 PM – 3:30 PM; 607 (5 presentations)

Also:
112.01. Constraining BH formation with 2M05215658+4359220, 10:00 AM – 10:10 AM, 612
109.03. Real-time data reduction pipeline and image analysis software for FIREBall-2: first flight with a δ-doped UV-EMCCDs operating in counting mode, 10:30 AM – 10:40 AM, 608
175.06. Python, Unix, Observing, and LaTeX: Introducing First Year Undergraduates to Astronomical Research, 10:50 AM – 11:00 AM, 620
109.08. TESS Data Analysis using the community-developed Lightkurve Python Package, 11:20 AM – 11:30 AM, 608
123.02D. A Uniform Analysis of Exoplanet Atmosphere Spectra Observed by HST WFC3 Is Consistent with Watery Worlds, 2:10 PM – 2:30 PM, 6C
129.06. Reconstructing the Orphan Stream Progenitor with MilkyWay@home Volunteer Computing, 3:00 PM – 3:10 PM, 611

Selected posters
144.25. Identifying and Comparing Centrally Star-Forming Galaxies Using MaNGA
144.29. Deriving star formation histories from photometric spectral energy distributions with diffusion k-means
144.30. Using Convolutional Neural Networks to predict Galaxy Metallicity from Three-Color Images
144.35. Automatic Detection and Analysis of Debris from Galactic Accretion Events
145.05. Galaxy Gradients Across Simulations
145.07. Reduction and Analysis of GMOS Spectroscopy for Herschel Sources in CANDELS
145.25. Comparison of the HI Signal Extraction Algorithms of SoFiA and ALFALFA
140.02. Tracking the TESS Pipeline
140.12. Undergraduates Can Find Planets Too
140.16. Identifying Transiting Exoplanets in with Deep Learning in K2 Data
140.20. The Impact of Small Statistics on Identifying Background False Positives in Kepler Data
140.23. AutoRegressive Planet Search for Ground-Based Transit Surveys
140.29. Getting to Know Your Star: A comparison of analytic techniques for deriving stellar parameters and abundances
149.18. NANOGrav: Data Accessibility, Analysis and Automation using Python
150.01. Revised Simulations of the Planetary Nebulae Luminosity Function
150.15. Identifying Binary Central Stars of Planetary Nebulae with PSF Fitting
158.02. HaloSat: X-Ray Calibration and Spectral Analysis for a NASA CubeSat
162.04. The Starchive

Selected iPosters
167.02. Modeling circumstellar dust around low-mass-loss rate carbon-rich AGB stars
167.04. The response of optical Fe II emission in AGNs to changes in the ionizing continuum, I: photoionization modelling
164.02. A Maximum Likelihood Approach to Extracting Photon-Starved Spectra of Directly Imaged Exoplanets
166.02. Smoothed Particle Inference Analysis of SNR DEM L71
171.03. The State of Software Tools for the Space Telescope Imaging Spectrograph

Other activities of possible interest
Monday, January 7: Data Science Splinter Meeting, 8:00 AM – 6:00 PM, 4C-1


TUESDAY, 8 JANUARY 2019
Workshop
LSST Science Pipelines Stack Tutorial for AAS, 9:00 AM – 5:00 PM; 310

Splinter meeting
Cafe SCiMMA: Conceptualizing an NSF Center for Scalable Cyberinfrastructure for Multimessenger Astrophysics, 3:15 PM – 5:15 PM; Redwood (Sheraton Seattle Hotel)

Oral presentations
Session 225. Computation, Data Science, and Image Analysis, 2:00 PM – 3:30 PM, 6E (6 presentations)

Also:
218.05. A Uniform Analysis of Kepler/K2 Exoplanet Transit Parameters, 10:40 AM – 10:50 AM, 603
206.05D. High Resolution spatial analysis of z ~2 lensed galaxy using pixelated source-reconstruction algorithm, 10:50 AM – 11:10 AM, 605/610
203.05. Atmosphere Retrieval of Planetary Mass Companions with the APOLLO Code: A Case Study of HD 106906b and Prospects for JWST, 11:00 AM – 11:10 AM, 6B
207.10. astroquery: An Astronomical Web-Querying Package in Python, 11:03 AM – 11:10 AM, 606
239.04D. Kinematics of Circumgalactic Gas and Cold Gas Accretion at Redshift z=0.2, 2:40 PM – 3:00 PM, 609
227.07. Mu and You: Public Microlensing Analysis Tools and Survey Data, 3:12 PM – 3:24 PM, 606

Poster presentations
Session 245. Computation, Data Science, and Image Analysis posters (31 posters!)

Selected posters
243.08. Utilizing Independent Component Analysis to Explore the Diversity of Quasars
245.01. Making organizational research software more discoverable
245.27. The MAESTROeX low Mach number stellar hydrodynamics code
245.29. The Castro Adaptive Mesh Refinement Hydrodynamics Code: Applications, Algorithm Development, and Performance Portability
247.30. Chemical Analysis of Tabby’s Star (KIC 8462852)
247.35. VPLanet: The VIrtual Planet Simulator
249.11. Know Your Neighbors: New Catalogs and Analysis of Star Clusters in the LMC, SMC, & M33
250.02. X-Ray Source Analysis In The Globular Clusters NGC 6341 and NGC 6541
253.06. Structure Function Analysis of Turbulent Properties in the Small and Large Magellanic Clouds
259.05. Forward-Modeling Analysis of Late-T Dwarf Atmospheres
259.15. Finding age relations for low mass stars using magnetic activity and kinematics
259.24. A Uniform Retrieval Analysis on a Sample of 16 T-dwarfs
258.25. SuperNovae Analysis aPplication (SNAP): Identifing and Understanding the Physics of Supernovae

Selected iPosters
268.02. Towards 3D Parameter Space Studies of CCSNe With Grey, Two-Moment Neutrino Transport
261.12. Using Machine Learning to Predict the Masses of Galaxy Clusters
261.15. Mapping Galaxy Cluster Orientations from Cosmo-OWLS Simulations
261.16. A Hydrodynamical Simulation of the Off-Axis Cluster Merger Abell 115


WEDNESDAY, 9 JANUARY 2019
Open meeting
AAS WorldWide Telescope with Python and Astropy, 10:00 AM – 11:30 AM; 214

Oral presentations
316.04D. Feedback and Chemical Enrichment in Low Mass Dwarf Galaxies: Insights from Simulations Tracking Individual Stars, 10:30 AM – 10:50 AM, 617
304.03. Recent upgrades to the pyLIMA software for microlensing modeling and analysis of two binary events, 10:10 AM – 10:20 AM, 6E
311.05. Quantifying the effects of spatial resolution and noise on galaxy metallicity gradients, 11:00 AM – 11:10 AM, 612
313.05D. Probabilistic data analysis methods for large photometric surveys, 10:50 AM – 11:10 AM, 614
336.04D. Simultaneous modelling of X-rays emission and optical polarization of intermediate polars using the CYCLOPS code: the case of V405 Aurigae, 2:40 PM – 3:00 PM, 614
342.06. On Open Cluster Disruption, 3:00 PM – 3:10 PM, 620
341.01. Reproducing Stellar Rotation Periods in the Kepler Field via Magnetic Braking and Tidal Torques

Selected posters
346.04. Designing a Python Module for the Calculation of Molecular Parameters and Production Rates in Comets
347.01. Hyperlink preservation in astrophysics papers
348.19. The COBAIN code. Basic principles and geometrical considerations
348.27. Considerations and Design Principles for the 2.1 Release of the PHOEBE Eclipsing Binary Modeling Code
356.06. Analysis of a large number of spiral galaxies shows asymmetry between clockwise and counterclockwise galaxies

Session 381. Computation, Data Science, and Image Analysis session (8 iPosters)

Selected iPosters
381.03. ASTROstream: Automated claSsification of Transient astRonomical phenOmena in the streaming mode
381.05. Understanding and using the Fermitools
381.07. Polarization Calibration Post-Pipeline in CASA: Pilot Implementation
381.08. Transitioning from ADS Classic to the new ADS search platform


THURSDAY, 10 JANUARY 2019
Hack Together Day
8:30 AM – 7:00 PM; 4C-2

Oral presentations
413.06. The Radio Astronomy Software Group: Foundational Tools for 21 cm Cosmology and Beyond, 11:10 AM – 11:20 AM, 614
408.07D. Hundreds of New Planet Candidates from K2, 11:00 AM – 11:20 AM, 608
411.05D. AzTEC Survey of the Central Molecular Zone: Modeling Dust SEDs and N-PDF with Hierarchical Bayesian Analysis, 10:40 AM – 11:00 AM, 612
405.05. How can new data analysis methods get more out of Kepler/K2 data?, 10:40 AM – 10:50 AM, 605/610
425.01. The Dedalus project: open source science in astrophysics with examples in convection and stellar dynamos, 2:00 PM – 2:22 PM, 606
430.02D. Analysis of the spatially-resolved V-3.6μm colors and dust extinction within 257 nearby NGC and IC galaxies, 2:20 PM – 2:40 PM, 612

Selected posters
443.11. WFC3 PSF Database and Analysis Tools
457.02. The Stak Notebooks: Transitioning From IRAF to Python
442.01. ExoPhotons: Exoplanet Monte Carlo Radiative Transfer
442.02. Quantifying inhomogeneities in the HI distributions of simulated galaxies
445.01. Lightkurve v1.0: Kepler, K2, and TESS time series analysis in Python
445.05. Using Kepler DR25 Products to Compute Exoplanet Ocurrence Rates
465.07. Distribution of stellar rotation periods using light curve analysis of second phase Kepler data


* abbreviated as in I haven’t listed all the posters that could be listed here, as the list was getting very very long…