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FIRST CONFERENCE TALK                                                 

(@ APS MARCH 2020)


Project | 04

The Fermi-Löwdin Orbital Self-Interaction Correction

Affiliation: Electronic Structure Laboratory, UTEP

Supervisor: Prof. Rajendra Zope

I performed my undergraduate thesis work and some master's research for over 1.5 years about the effects of Perdew-Zunger self-Interaction correction on the regularized Strongly Constrained and Appropriately Normed (rSCAN) exchange-correlation energy functional using the FLOSIC code. I compared the performance of the rSCAN and SCAN functionals with and without self-interaction correction for several electronic properties in standard datasets.



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Project | 03

Precision Reactor Oscillation and Spectrum Experiment (PROSPECT)

Affiliation: Physics Division, ORNL

Supervisor: Dr. Alfredo Galindo-Uribarri

I worked on data analysis during Summer 2018 under the supervision of Dr. A. Galindo-Uribarri. This experiment is an effort led by Yale University to find signatures of the sterile neutrino at short baselines from ORNL’s High Flux Isotope Reactor and to determine the antineutrino energy spectrum from fission of U-235. My task was to write ROOT scripts to do background studies and explore cuts in the data parameters that would maximize antineutrino counts. The parameters that we varied included pulse-shape discrimination, e-scatter, fiducial z, and time range between inverse beta decay signals, which described properties of antineutrino detections. This project looks for physics beyond the Standard Model by looking for another neutrino flavor.

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Project | 02

Classification of Dynamical Systems and Prediction of their Physical States Using Deep Learning

Affiliation: Center for Theoretical Physics, MIT

Supervisors: Prof. John W. Negele, Prof. Phiala Shanahan, Dr. Andrew Pochinsky.

I worked with the Lattice QCD group of Prof. John Negele, Dr. Phiala Shanahan (now assistant professor at MIT), and Dr. Andrew Pochinsky as an MIT Summer Research Program fellow during Summer 2017. They had me develop machine learning codes to solve classical systems. In this project, I wrote codes solving the equations concerning motion of oscillators, constructed deep neural networks, and quantified the network’s efficiency to classify these systems and predict their coordinates and momenta by comparing the network’s predictions to the correct solutions.

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Project | 01

Thermodynamics of Neutron-Rich Nuclear Matter

Affiliation: Nuclear Theory Group, UTEP

Supervisor: Prof. Jorge A. Lopez

I worked at UTEP for one year under the supervision of Prof. Jorge A. Lopez performing calculations of energy and pressure of proton-neutron asymmetric nuclei at high temperatures to construct their liquid-gas coexistence phase diagrams. My task consisted on running more than three hundred simulations of nuclei under varying temperatures, densities, and proton-neutron ratios, obtaining their energy and pressure, plotting them as function of density using GNUplot, and reporting the data to my supervisor. As a result, Prof. Lopez used this to finish a work on course and publish an article in which he acknowledged my participation. This effort is related to the rare-isotopes research that will soon be done at the Facility for Rare Isotope Beams from Michigan State University, which I had the chance to visit as an NS3 participant in 2017 (See CV).

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