[{"content":" About I am a computational physicist whose research focuses on the development of numerical methods for atomic structure and collision calculations relevant to astrophysical and laboratory plasmas. I earned my Ph.D. in Physics from Auburn University in 2025, where I developed algorithms to improve the efficiency and accuracy of configuration interaction calculations for dielectronic recombination.\nBeyond my doctoral work, I am broadly interested in scientific computing, computational physics, and the development of mathematical and algorithmic tools for understanding complex physical systems.\nIn addition to my research, I maintain a collection of independent projects and educational notes exploring topics in mathematics, computation, and theoretical physics. Contact For professional inquiries, please contact me at the email linked below: Email ","date":"21 July 2026","externalUrl":null,"permalink":"/","section":"","summary":"","title":"","type":"page"},{"content":"","date":"10 July 2026","externalUrl":null,"permalink":"/media/","section":"Media","summary":"","title":"Media","type":"media"},{"content":"","date":"28 June 2026","externalUrl":null,"permalink":"/projects/cristal/","section":"Projects","summary":"","title":"CRISTAL","type":"projects"},{"content":" Curriculum Vitae # Full CV\nDownload Curriculum Vitae (PDF) Summary\nMy research focuses on computational atomic physics, plasma spectroscopy, and scientific software development. I received my Ph.D. in Physics from Auburn University in 2025 and develop computational methods for modeling atomic structure and collision processes in astrophysical and laboratory plasmas.\nHighlights\nPh.D. in Physics, Auburn University Computational atomic physics and plasma spectroscopy Scientific software development in Python, Fortran, C, and MATLAB Conference presentations at AAS, ICPEAC, DPP, and GEC Publication in The Astrophysical Journal (in review) ","date":"5 June 2026","externalUrl":null,"permalink":"/cv/","section":"","summary":"","title":"CV","type":"page"},{"content":" $$ \\begin{align*} \\delta\\mathcal{L} = \u0026\\left(\\frac{\\partial\\mathcal{L}}{\\partial\\phi} + \\sum_{n=1}^\\infty (-\\boldsymbol{\\nabla})^{\\otimes n}\\cdot\\frac{\\partial\\mathcal{L}}{\\partial(\\boldsymbol{\\nabla}^{\\otimes n}\\phi)}\\right)\\delta\\phi\\\\ \u0026+ \\sum_{n=1}^{\\infty}\\boldsymbol{\\nabla}\\cdot\\left(\\sum_{k=0}^{n-1}\\left((-\\boldsymbol{\\nabla})^{\\otimes k}\\cdot \\frac{\\partial\\mathcal{L}}{\\partial(\\boldsymbol{\\nabla}^{\\otimes n}\\phi)}\\right)\\cdot \\boldsymbol{\\nabla}^{\\otimes n-1-k}\\delta\\phi\\right) \\end{align*} $$","date":"5 June 2026","externalUrl":null,"permalink":"/notes/","section":"Notes","summary":"","title":"Notes","type":"notes"},{"content":"These projects form a unified software ecosystem for large-scale atomic structure calculations. The AUTOSTRUCTURE extensions provide scalable computational capabilities, the pipeline automates simulation workflows, and CRISTAL builds upon this framework to optimize configuration interaction calculations.\nCRISTAL\nStatus: Published\nConfiguration interaction calculations often require tens of thousands of electronic configurations to accurately model complex atomic systems, making them computationally expensive. CRISTAL (Complex Resolved Ion Spectroscopy Tree Algorithm) is a decision-tree algorithm designed to identify the smallest configuration set needed to achieve a desired level of accuracy. The set of possible configurations (up to a maximum value of the principal quantum number, $n$) is organized into a tree data structure. The tree is then pruned to find the minimum number of states necessary to reach a given accuracy. The current implementation evaluates candidate models by comparing calculated and experimental energy levels, although future work aims to replace this empirical metric with more fully ab initio selection criteria.\nAUTOSTRUCTURE Extensions\nStatus: Ongoing\nAUTOSTRUCTURE is a widely used atomic structure code which calculates atomic energies, stationary states, and autoionization and radiative rates using the configuration interaction method. The original implementation was primarily intended for serial calculations involving relatively modest configuration expansions. My collaborators and I have extended this code to perform parallelized calculations on much larger configuration sets. In principle, the upper limit is now only bounded by the available memory.\nAtomic Data Pipelines\nStatus: Ongoing\nLarge-scale atomic structure calculations require the generation of input files, execution of many computational jobs, and post-processing of extensive output data. To streamline this workflow, I have developed a Python-based pipeline that automates these tasks while providing a more intuitive interface to AUTOSTRUCTURE. This pipeline currently serves as the platform on which CRISTAL is implemented and is intended to support additional atomic structure codes in the future.\n","date":"5 June 2026","externalUrl":null,"permalink":"/projects/","section":"Projects","summary":"","title":"Projects","type":"projects"},{"content":" Garcia, J. I. , Chilen, C. , Garbe, E. F. , Stancil, P. C. , Fontes, C. J. , Fogle, M. , Loch, S. D. , ”A configuration interaction decision tree algorithm to improve dielectronic recombination rates in low temperature photoionized plasmas” Astrophysical Journal (in review, expected 2026)\n","date":"5 June 2026","externalUrl":null,"permalink":"/publications/","section":"Publications","summary":"","title":"Publications","type":"publications"},{"content":" Current Research Interests # Atomic Physics\nAtomic structure modeling: Computational methods for calculating the electronic structure and properties of atoms using quantum mechanical models. Electron-ion collisions: Theoretical and computational modeling of electron-impact processes, including excitation, ionization, and recombination. Configuration interaction: Non-perturbative electronic structure methods for accurately describing electron correlation in many-electron atoms. Dielectronic recombination: Resonant electron capture and radiative stabilization processes that play a central role in determining the ionization balance and spectra of astrophysical and laboratory plasmas. Computational Methods\nNumerical algorithms: Methods for approximating solutions to mathematical relations to arbitrary precision. Scientific software: Codes for modeling physical phenomena and interpreting physical data. High-performance computing: Optimization, parallelization, and memory allocation and management for computationally intensive simulations or calculations. Machine learning methods: Data-driven approaches for accelerating scientific computation, selecting optimal models, and discovering efficient representations of complex physical systems. Applications\nPlasma spectroscopy: Analysis of emitted radiation to diagnose the elemental abundances and temperature profile of a plasma. Astrophysical plasmas: Interpretation of spectra from stellar atmospheres, nebulae, planetary nebulae, and other astrophysical environments. Laboratory plasmas: Applications to fusion and laboratory plasma experiments, including tokamaks, stellarators, and storage-ring measurements. Emerging Research Interests # Quantum Information and Algorithms\nQuantum chemistry simulations: Exploring quantum algorithms for electronic structure calculations and many-body quantum systems. Generalizable quantum algorithms: Investigating mathematical frameworks that may extend the applicability of quantum algorithms across multiple classes of scientific computing problems. Machine Learning for Physical Sciences\nLinearizing complex physical systems: Investigating operator-theoretic approaches for representing nonlinear dynamical systems through linear evolution in higher-dimensional spaces. Scientific model discovery: Applying machine learning techniques to identify reduced-order models, hidden structure, and emergent patterns in complex many-body systems. ","date":"5 June 2026","externalUrl":null,"permalink":"/research/","section":"Research","summary":"","title":"Research","type":"research"},{"content":"","externalUrl":null,"permalink":"/authors/","section":"Authors","summary":"","title":"Authors","type":"authors"},{"content":"","externalUrl":null,"permalink":"/categories/","section":"Categories","summary":"","title":"Categories","type":"categories"},{"content":"","externalUrl":null,"permalink":"/series/","section":"Series","summary":"","title":"Series","type":"series"},{"content":"","externalUrl":null,"permalink":"/tags/","section":"Tags","summary":"","title":"Tags","type":"tags"}]