About Me

    Education:
  • BS in Physics from Texas Tech University 2014
  • MS in Physics from the University of Pittsburgh 2016
  • PhD in Physics from the University of Pittsburgh 2022

I am a personal postdoc affiliated with the University of Arizona, department of Astronomy and Steward Observatory.

Previously I was a graduate student afiliated with the University of Pittsburgh, department of Physics and Astronomy.

I’m interested in studying the evolution of galaxies and the dark matter haloes in which they reside. My graduate work was centered at the mass range of the Milky Way and I have since started studying dwarf galaxies as well as a postdoc in Dave Sand's group.

  • While the Milky Way offers a unique perspective to study nuanced details of galaxy formation, we still have a very limited ability to compare the Milky Way to other galaxies. Some of my research aims to close this gap.
  • Dwarf galaxies serve as a unique probe into the extrema of the processes of galaxy formation and closely trace underlying dark matter structure. My research focuses on study dwarf populations in a variety of environments to study the details on how they form and evolve.
Please check out my research tab to learn more.

I serve as co-chair in the SDSS-IV Milky Way as a Galaxy group.

I am passionate about inclusion and equity both in an out of academia.

Please check out my publications here:
List of both first author and co-author papers.
ORCID

Research

General Research Interests:

  • galaxy formation and evolution
  • galaxy environments
  • the Milky Way
  • dwarf galaxies
  • machine learning techniques
My research lays at the intersection of interpreting theoretical models and improving observational constraints to understand galaxy evolution. My experience with diverse sets of both observed and simulated data illuminates the discrepancies in existing models which places me in a unique position with which I can bridge the gap between observational constraints and simulation predictions. My prior research focused on leveraging the uniqueness of the Milky Way in order to fill in our gaps of how the Milky Way relates to other galaxies photometrically, and how we should extrapolate from the Milky Way to guide simulations. I have lately been studying both individual dwarf galaxies in the local Universe and dwarf galaxy ensembles. Understanding these systems provides a unique window into the roles galaxy environment and internal processes play in galaxy evolution.

Dwarf Galaxies

Ultra Diffuse Galaxies with Tidal Features: Our group have completed a study of 5 UDGs with tidal featured identified in the CFHT Legacy Survey area. 2 of these UDGs were optically red with no GALEX UV detections, while 3 were optically blue with corresponding UV detections. With HST and VLA follow-up we find that the most viable formation pathway for four of these UDGs is tidal heating by a companion. One of the UDGs is an unusual outlier, with a very high globular cluster abundance, more consistent with a dwarf major merger formation origin. This UDG, UGC 9050-Dw1, has been featured in several popular science outlets:

UGC 9050-Dw1 HST/ACS image of UGC 9050-Dw1 with globular clusters circled. This UDG has an extensive tail structure extending to the North and a very bright core region (see the inset). Figure from Fielder et al. 2023.

Milky Way

Dark Substructure of the Milky Way: Using N-body simulations I found that the Milky Way should have fewer subhalos (and thus satellites) than the average halo of the same mass.

Dark matter halo structure/substrucure: to explore how dark matter subhstructure effects their host halo structure, and to provide a better model for inferences of dark matter halo observationspredictions.

Milky Way analog galaxies: to determine how the Milky Way compares to the general galaxy population, and to constrain photometric properties of the Milky Way that cannot be observed directly.

Machine learning using Gaussian process regressions: to construct robust models that allow us to both better constrain the evolutionary history of the Milky Way and connect dark matter halo simulation predictions with observations.

Milky Way SEDThe first long-baseline SED of the Milky Way constructed in Fielder et al. 2021 with Gaussian Process Regression. .

Data and Tools

Milky Way Analog Selection:
Github repository for selecting Milky Way analogs
This code is designed for efficient selection and analysis of Milky Way analogs. Analogs are selected by random draws from the fiducial Milky Way PDF in the parameter space of interest. More than three parameters are discouraged due to small numbers of analogs. For each set of random draws the nearest neighbors are found in a binary tree. Then the sample's photometric properties, derivatives of the photometric properties, and the errors + Eddington bias are calculated.
This code is useful for anyone interested in selecticting Milky Way, Andromeda, etc. analog galaxies.

Useful Catalogs:
Github repository for catalogues used in Licquia et al. 2015 and Fielder et al. 2021.
This repository contains the cross-matched catalogues for

  1. SDSS DR8 photometry + MPA-JHU stellar masses and star formation rates + Simard et al. 2011 bulge-disck decompositions + GSWLC-M2 + Galaxy Zoo 2
  2. All previously listed catalogues + DESI Legacy DR8 WISE measurements and their k-corrected values

Gaussian Process Regression for Photometry:
Github repository with example code for the methods presented in Fielder et al. 2021.
This code, provided under a CC BY-SA 4.0 license, is available to those interested in using Gaussian Process Regression with observed photometry in some way. We provide our functions fo specifically working with the Milky Way, but these can be adapted for other uses. We also provide examples for running a basic GPR (using the scikit-learn implementation in python), performing Eddington bias calculations and their respective functions, calculating derivatives and their respective functions, and example code for constructing an SED based upon ones results.

Outreach

I personally believe that teaching and outreach are important components of being a scientist. Through these avenues we can improve education and equity. Listed below are activites that I have been involved in at respective universities.

University of Pittsburgh

  • Interviewee on Skyglow Research in Pittsburgh, which helped introduce new Dark Sky legislation for Pittsburgh, Summer 2021. See more details here!
  • Guest Lecturer, Speaking about science and research to multiple high school classes, Fall 2019, Spring 2020
  • Guest Lecturer, Introducing research to undergraduates, Society of Physics Students meeting Fall 2020
  • Speaker, Astronomy on Tap Pittsburgh, Fall 2018
  • Teaching assistant and Teaching Fellow, Introductory astronomy classes Basics of Space Flight and Stonehenge to Hubble, Fall 2014, Spring 2015, Spring 2018, Fall 2018

Texas Tech University

  • President of the Society of Physics Students 2013, 2014
  • Organizer of many public events such as bi-annual star parties, scientific trips, science demonstrations.
  • Science fair judge for local schools, Spring 2013, Spring 2013, Spring 2014