Curriculum Vitae
Links
Education
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University of Pittsburgh
(Expected Spring 2023) - Ph.D. Physics
12/2018 - M.S. Physics
Rensselaer Polytechnic Institute
05/2017 - B.S. Physics, magna cum laude
Final year PhD candidate
Department of Physics and Astronomy
University of Pittsburgh
Soon-to-be Postdoc at Argonne National Lab
Contact me: alannpearl@outlook.com
University of Pittsburgh
(Expected Spring 2023) - Ph.D. Physics
12/2018 - M.S. Physics
Rensselaer Polytechnic Institute
05/2017 - B.S. Physics, magna cum laude
mocksurvey is a Python package used for constructing mock galaxy catalogs and perform mock surveys seeded from the UniverseMachine empirical model.
JaxTabCorr is a Python package that integrates classes from TabCorr and halotools into a differentiable prediction framework made possible by JAX autodiff libraries.
galtab is a Python package that tabulates possible galaxy locations to improve prediction efficiency of my Counts-in-Cylinders estimator.
I am a contributor to halotools, which is a Python package that provides a wide array of models of the galaxy-halo connection.
You can download my mock catalogs for PFS here
Publications: See my papers on ADS
Illuminating and Tabulating the Galaxy-Halo Connection
Part I: Illuminated the UniverseMachine to construct PFS mock catalogs
Using UniverseMachine as a model and UltraVISTA photometry as training data, I created a mock galaxy catalog specifically tailored to making predictions for the upcoming PFS survey. Using this mock, I published a paper which demonstrated that future extensions of the PFS survey should prioritize increasing the survey area to best improve scientific goals. This mock is publicly available.
Part II: Tabulated statistical estimators to be fast, precise, and differentiable
The galaxy-halo connection is typically analyzed via Markov-chain Monte Carlo (MCMC) sampling of parameter-space in order to place constraints on models. However, this process is slowed down by the stochastic nature of halo occupation distribution (HOD) models. I have improved the efficiency of this process with two open-source projects: