Physics PhD. Candidate at West Virginia University
Gravitational Wave Astrophysicist, Avid Learner, Python Enthusiast
I grew up in rural Northwest Arkansas, and got my Bachelor's in Physics with
a minor in Math from the University of Arkansas. From there I moved to West Virginia
and am working on my PhD in Physics.
I am most interested in gravitational wave (GW) astrophysics and I have studied a wide range of subjects in the field; determining GW detector sensitivities, modeling GW sources, searching for GWs with pulsar timing arrays using Bayesian statistics, and more!
I have spent the majority of my research experience exploring and characterizing sources of noise and signals in current and future gravitational wave (GW) detectors using frequentist and Bayesian methods. My work revolves specifically around three projects:
• Estimating the response strength in current and future gravitational wave detectors under a variety of designs to coalescing black hole binaries using frequentist methods.
• Assessing the potential of pulsar timing arrays (PTAs) to detect multiple GW backgrounds through simulation and recovery work.
• Holistically examine pulsar timing parameters inside PTAs’ current GW detection pipeline using non-linear parameterization of pulsar timing models in tandem with noise and dispersion measure modeling.
For all of these projects I worked alongside my colleagues in the North American Nanohertz Observatory for Gravitational Waves (NANOGrav).
In addition to these main projects, I have broader interests searching for individual GW sources, data analysis, pulsar noise characterization, and data visualization.
My software development interests have followed my research interests greatly. As a part of my first project on simulating GW detectors, I led the development of the open-source software package gwent including fully documenting it and deploying it to the Python Package Index (PyPI). Throughout my career I have contributed to multiple packages relevant to the detection of GWs with PTAs: enterprise, enterprise_extensions, and hasasia. Beyond research, I have done projects on website development using Django, machine learning, and data visualization areas where I am very interested in learning and doing more!
Throughout my time in academia, I have worked very hard to bring equity and inclusivity into the departments and collaborations of which I have been a part. I've attended countless trainings and colloquia by some amazing people and have learned a lot to try and change academia for the better. I have fought for fair graduate student representation and pay at West Virginia University as part of the Graduate and Professional Student Senate and the Physics and Astronomy Graduate Student Organization. I have been a part of the American Physical Society's Inclusivity, Diversity, and Equity Alliance (APS IDEA), and I have spent multiple years on the NANOGrav Climate and Equity Committee.
In my spare time, I like to bake, garden, play french horn in the community orchestra, go for bike rides, play videogames, make short videos, stargaze, and watch movies.
My first major research project on using matched-filtered signal-to-noise ratios to estimate the detectability of gravitational wave sources in variable detector realizations.
A web application I made to calculate stresses on a timber frame houses after not finding any useful tools when building my house.
A machine learning tool I developed to predict what movies my friends would pick in our movie club (and how to rig it so we watched what I wanted to watch).
Pulsars are rapidly rotating neutron stars with extremely strong electromagnetic fields. The strong fields produce a cone of emission that beams light into the Universe much like a lighthouse. To help visualize (or more accurately, auralize) how rapidly these pulsars rotate, I used their rotation frequency as an audible note converted through the Python package Pyo. All of these sounds and images were made entirely in Python by me.
Pulsars rotate at a fundamental frequency, these happen to be in the human range of sound. This visualization plays the respective frequencies for all of the pulsars in NANOGrav's 12.5-year data release.
Many binaries in PTA datasets have a binary companion. Here I combined each pulsar's rotation frequency with information about the binary system's orbital period (how long it takes for a full revolution of the pair of stars), and the distance the pulsar is from its companion at closest approach. In the visualization, the pulsar chimes at its rotation frequency every full orbit with its companion and is displayed at its distance from its companion in light-seconds on a logarithmic scale. For reference, Earth is about 500 light-seconds from the Sun and about 1.3 light-seconds from the Moon.
Pulsars can be found throughout the Galaxy. Wherever massive stars die, there will be pulsars. Unfortunately for us, we are kind of stuck in a particular portion of the Milky Way, in a somewhat backwater district. Pulsars are mostly observed in radio frequencies, these can be pretty weak signals and take very specialize telescopes to observe them. For scale, pulsars are measured in Jansky's (in honor of Karl Jansky, the person who discovered natural radio emission from our Galaxy) and often milli-Jansky's, while a cellphone at a kilometer away emits about 110 million Jansky's. So we tend to only find these weak signals in our local region.
Pulsars are found distributed all around us in the Milky Way. This visualization shows the position relative to our solar system on the night sky and in the plane of the Milky Way of a selection of pulsars from NANOGrav's 12.5 year dataset that have the nearest frequencies to our typical scale of notes used in music. I then use these nearest notes in a transcribed (by me) version of the theme from Star Trek: The Next Generation.
This visualization is the same as its partner, but instead of converting the pulsar frequencies to notes, I simply used the rotational frequencies of the pulsars. As you can hear, they are not quite in tune.