Solicitations for Undergraduate Summer Research Opportunities in 2021
This year, due to unprecedented pandemic circumstances, our approach to Summer research opportunity is different than before (see here for last year's process).
Here is a subset of this year's solicitations in Astronomy and Astrophysics. For more information on the projects please email the prospective advisor; the emails are listed at the bottom of this page.
Kyle Conroy: Long-term follow-up strategies from fitting eclipse timing variations (ETVs) from Kepler data
With the advent of high-precision photometric surveys (including Kepler), the Eclipsing Binary (EB) field has had to shift from modeling individual systems from ground-based photometry to ingesting large quantities of data and using automated pipelines for initial analysis. Eclipse timing variations (ETVs) have been measured across the Kepler EB dataset as a way to search for triple systems. However, the limited time baseline of Kepler has limited our sensitivity to long-period triple star systems. The selected student will develop a code capable of fitting third body orbits to ETVs, determine the uncertainties on the resulting orbital parameters, extrapolate the uncertainties of these orbital parameters onto the model forward in time, and determine a method for optimizing follow-up of eclipse timing variations into the future to attempt to minimize the uncertainties and maximize the science output.
Kyle Conroy: Barycentric and Asymmetric Transverse Velocities (BATV)
Precise timings of eclipses are often measured to look for trends over long time baselines. These trends can suggest many different physical effects including apsidal motion, mass transfer, or the presence of a third body in the system. Barycentric and Asymmetric Transverse Velocities (BATV - see Conroy et al. 2018) is a small contribution that causes an apparent shift in the timing of eclipses caused by the motion of the system on the plane-of-the-sky. The selected student will attempt to apply the theory of BATV to real observational data. Several possible directions of study could include: focusing on one of the “uses” of BATV (apsidal motion, triples, estimating mass ratios, etc) and trying to find systems in the literature with observable contributions; applying more recent GAIA data; or considering the impact of Earth’s motion.
Kyle Conroy/Angela Kochoska: Comparing synthetic light curve models across parameter space
Many different codes exist to model eclipsing binary light curves (including PHOEBE, Wilson-Devinney, ellc, jktebop, etc) each with its own assumptions, approximations, and approaches. In order to understand which are best-suited to a particular region of parameter space and also to understand the *model* uncertainty, we would ideally need to compare the forward-models across a large grid of input values. This project would consist of a pilot study towards this goal by comparing different metrics for comparing these light curves and determining the necessary grid size and spacing.
Kyle Conroy/Angela Kochoska: Implement extensions to the fitting framework in PHOEBE
The recent 2.3 release of PHOEBE (Conroy et al. 2020) included built-in wrappers to a number of different fitting algorithms, including optimizers and MCMC. There is still a significant "wish list" of potential future extensions to the framework, a list of which can be found at https://github.com/phoebe-project/phoebe2/discussions/407. This project requires a student who is quite comfortable and willing to learn about software development in Python (using classes, etc), and choosing one or several of these extensions to implement into the code.
Scott Engle: The Secret Lives of Cepheids Program
Research projects within this program focus on refining the fundamental parameters of Classical Cepheid variables, which have enjoyed a renewed focus in recent years due to their role in highlighting a tension between local and cosmological determinations of the Hubble constant. Based on applicant preference and data availability, the parameters can be refined in a number of ways: monitoring the pulsation period of the variable to search for evolutionary changes, building and modeling spectral energy distributions of the target, and searching the latest Gaia data release for potential cluster membership.
Scott Engle: The Living with a Red Dwarf Program
Red Dwarfs (main sequence K and M dwarfs) make up ~90% of the nearby stellar inventory. Determining their ages, activity levels, and potential suitability to host habitable planets is thus a very important question. We aim to investigate these objects by using X-ray and UV data (activity levels, falre strengths and frequencies) from satellites such as Hubble, Chandra, XMM, Galex and Swift, and also optical photometry (rotation period, flare strengths and frequencies) from ground-based observatories and continuous photometry from the Kepler and TESS satellites when available.
Scott Engle: Planetary Transit Photometry
Using either the on-campus observatory, or our remote telescope at Kitt Peak National observatory, we will acquire and analyze transit photometry of known or suspected exoplanets. For known exoplanets, we will refine their orbital parameters or search for variations in them. For suspected exoplanets, we will be looking to help confirm their existence.
Ed Guinan: Mars Gardens / Artemis Gardens
Mars Gardens -testing growing plants / vegetables under lower (45% Earth) Martian solar light irradiances, in simulated Martian soil. Because of NASA's upcoming Artemis Moon Base, we now have lunar highlands and mare regolith simulants to test growing plants in lunar-like soil using solar-simulated LED lighting.
Ed Guinan: Physical properties of pulsating red supergiant stars (RGSs)
These massive stars are progenitors of Type II Supernovae. Analyze available photometry and spectroscopy along with carrying out period studies of time-series data to probe the internal structure of these stars as well as to search for evidence rapid evolutionary changes. Also use new methods to estimate distances and luminosities of these important massive stars. Plan to continue the study of Betelgeuse but also to study Antares (alpha Sco) - the neglected twin of Betelgeuse. This program has been expanded to study all RSGs within 2000 ly of Sun that will include mu Cep and VV Cep.
Ed Guinan/Scott Engle: Living with a Star - Know Thy Star/ Know thy Planet
Use X-ray and UV measures of G, K, M stars with different ages to determine the X-ray-UV irradiances and stellar plasma (winds) on hosted exoplanets. The exoplanets selected for study orbit within their liquid water habitable zones of the stars. The star-planet systems under study are most likely rocky (terrestrial) planets. Projects include: The Sun in Time, Living with a Red Dwarf (LivReD), GoldiloKs (K-stars).
Ed Guinan/Scott Engle: Binary stars as Astrophysical Laboratories
Analyses of the X-ray and UV properties of the short-period white dwarf-red dwarf eclipsing binary V471 Tauri. Includes the analysis recent time series observation of X-ray and UV observations from XMM-Newton and NICER.
Kelly Hambleton: Validating and Expanding the Tests of Asteroseismic Scaling Relations Using Red Giant Binary Stars
Kelly Hambleton is seeking to employ a Villanova University undergraduate student to work in the field
of binary stars and asteroseismology. The selected candidate will be fully funded for 10 weeks.
This will include a stipend and funding for the AAS in January 2021. If the project is permitted to
be undertaken in person room and board will also be funded. During the ten-week period, the student will
work with the Kepler data, which they will extract from the MAST website. Using the acquired data, the
student will then learn how to generate a binary star model of an eclipsing binary with a red giant
component. The results of the model will include fundamental stellar parameters (masses and radii). The
student will then determine the mass and radius of the red giant component using asteroseismology. A
comparison will be made between the asteroseismic mass and radius, and the mass and radius determined
through binarity. The results will be used to validate and calibrate the asteroseismic scaling relations,
which allow the determination of the masses and radii of thousands of solar-like oscillators based on their
pulsations alone.
Kelly Hambleton: Identification and Analysis of Heartbeat Stars
Heartbeat stars are eccentric ellipsoidal variable stars which have light curves that look similar to cardiograms, hence the name. The selected student will explore the TESS data to identify all unknown heartbeat stars. With the catalog of new and previously identified heartbeat stars, the student will preform analysis including amplitude and period determination. Approximately 20% of known heartbeat stars pulsate with tidally induced pulsations, pulsations that occur a precise number of times per orbit. The student will identify these objects and analyse the pulsation frequencies, amplitudes and phases to identify interesting objects and correlations in the data.
Angela Kochoska: Binary Stars in bulk?
With the advent of big data astronomy we are faced with increasingly large amounts of eclipsing binary light curves whose modeling is no longer feasible using the “classical” way – one person spending days, weeks and sometimes months on a single light curve. The project proposed involves bridging the gap between modeling and big data by using bulk-parameter estimators. The student will test the efficiency, accuracy and validity within different parameter ranges of a nearest-neighbors algorithm that uses a pre-computed library of synthetic light curves with known parameter values to estimate the parameters of large data sets of EBs, like Kepler/K2 and TESS. It is preferable that the student is familiar with scripting in python.
Angela Kochoska: Supervised vs. unsupervised methods of light curve classification
Machine learning is everywhere, but how do we make the most of it? We’ll try to answer this question within the realm of light curve classification by probing different supervised and unsupervised methods avalable in the scikit-learn package: https://scikit-learn.org/stable/supervised_learning.html https://scikit-learn.org/stable/unsupervised_learning.html . The goal is to determine which ones are best suitable for fast and efficient classfication of large datasets, with a focus on TESS EBs. This project is perfect for a student interested in complementing their scientific knowledge with some data science!
Angela Kochoska/Kyle Conroy: Second order effects and eclipsing binary parameters
This project involves fitting light curves of Kepler or TESS EBs to determine the impact second order effects, like limb darkening, gravity darkening and reflection, have on the fitted stellar parameter values. The student will be using the PHOEBE code and all of its fitting functionality, in particular optimization and sampling with MCMC. It is preferable that the student is comfortable with scripting in python.
Andrej Prsa: Eclipsing binaries observed by the TESS mission
Andrej Prša’s research group is seeking a Villanova undergraduate student for the summer research
opportunity to work on light curves of eclipsing binary stars observed by the TESS mission. The
appointment is for 10 weeks. The selected student will learn to extract light
curve data from TESS fits files hosted on MAST, detrend extracted light curves, detect and classify
eclipsing binary light curves, determine the ephemerides and cross-match TESS data with other
published works. The student will also work on full-frame images (FFIs) and learn how to extract light
curves of objects that are not on the TESS target list. The result of this work will be a catalog of TESS
eclipsing binary stars and identification of the systems of most scientific interest.
Andrej Prsa: Virtual and Augmented Reality solutions to multi-dimensional visualization and classification
Andrej Prša’s research group is seeking a Villanova undergraduate student for the summer research
opportunity to work on 3-D visualization using the Oculus Quest 2 VR headset. Both data dimensionality reduction and
object visualization will be explored. Proficiency with programming, and any prior C#/Unity experience, is highly desired.
Andrej Prsa: Light curve classification using artificial intelligence and deep learning
Andrej Prša’s research group is seeking a Villanova undergraduate student for the summer research
opportunity to work on classifying light curves of various astronomical objects using artificial
intelligence and machine learning, including dimensionality reduction algorithms. The appointment is
for 10 weeks. The selected student will learn to train and run neural networks
on heterogeneous publicly available light curve data and interpret the results from the network, most
notably the confusion matrix. The data to be used for the project will be proposed by the student. The
result of this work will be a pilot test case for the ambitious project to classify all publicly available
data in astronomy.
Andrej Prsa: Discovering Unknown Unknowns
Kepler, K2 and TESS observed hundreds of thousands of stars each; finding a needle in a haystack among millions of lightcurves is difficult, especially if we do not quite know what a needle might look like because it is ... well, unknown. The idea is to find statistically unique lightcurves and try to figure out what objects might be responsible. During the process we are likely to come up with an objective classification scheme that may change the way we discern objects in astronomy. Programming skills and statistical affinity are quite important for this project.
Andrej Prsa: Peanuts in Space
Contact binary stars are systems of two stars that share a common envelope. One glaring gap in their understanding is energy transfer, and we are hoping to figure out how they work.
Ed Sion: Cataclysmic Variable Stars
Modeling of white dwarfs in a cataclysmic variable.
Faculty emails:
Kyle Conroy: kyle.conroy@villanova.edu
Scott Engle: scott.engle@villanova.edu
Ed Guinan: edward.guinan@villanova.edu
Kelly Hambleton: kelly.prsa@villanova.edu
Angela Kochoska: angela.kochoska@villanova.edu
Andrej Prsa: aprsa@villanova.edu
Edward Sion: edward.sion@villanova.edu