Project | 04

The Fermi-Löwdin Orbital Self-Interaction Correction

Affiliation: Electronic Structure Laboratory, UTEP

Supervisor: Prof. Rajendra Zope

Performed thesis studies about effects of Self-Interaction Correction on the Regularized Strongly Constrained and Appropriately Normed exchange-correlation energy functional on Density Functional Theory using the FLOSIC code to improve ab initio calculations in the electronic structure of atoms and molecules.

Project | 03

Precision Reactor Oscillation and Spectrum Experiment (PROSPECT)

Affiliation: Physics Division, ORNL

Supervisor: Dr. Alfredo Galindo-Uribarri

I performed data analysis during the summer of 2018 under 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 flavor of the neutrino. Currently, the open questions of neutrino physics and connections to Lattice QCD drive me to pursue a PhD in any of these fields.

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, Phiala Shanahan, and Andrew Pochinsky as an MIT Summer Research Program fellow during the summer of 2017. They had me develop Machine Learning algorithms 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.

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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