LEAPS-MPS: A Systematic and Automatic Spectral Analysis of Physical Conditions of Circumgalactic Medium using Genetic Algorithms;

Astronomical spectroscopy lies at the foundation of our understanding of the universe and its constituents (e.g., stars, planets, galaxies, interstellar medium), and for generations of astronomers, the analysis of spectroscopic data has been carried out by experienced and highly trained end-users - the astronomers themselves. This paradigm will be severely challenged by new generations of spectrographic instruments that will produce literally billions of high-resolution spectra on relatively short timescales and orders of magnitude faster than they can be analyzed. The research team will address this "data firehose" problem by developing an open-source spectral analysis package based on a genetic algorithm (GA) to accurately analyze astronomical spectra automatically with minimal human intervention, and then use it to explore the physical conditions within the gaseous halos of galaxies as a proof-of-concept. This project will support the thesis research of two graduate students and allow the PI to further efforts at his home institution to involve students in computational astrophysics and other STEM fields. This project is co-funded by the Established Program to Stimulate Competitive Research (EPSCoR).Establishing fast and automated global optimum search methods applicable to large and rapid growing datasets in spectral analysis is a complex and long-standing problem. The proposed work will advance knowledge in multiple areas by developing a GA-based global optimization method for the analysis of high-resolution spectra that is applicable to large and rapid growing datasets in modern data environments and then applying it to facilitate understanding of the circumgalactic (CGM) and intergalactic (IGM) media of galaxies using archival spectra of background sources obtained with the HST's Cosmic Origin Spectrograph (COS). The project outcomes will include an extensible and open-source code base software package (Astro-Neo) that will enable astronomers to analyze large quantities of data with improved quality and reproducibility. The core software has been applied successfully in materials science and will be extended to other fields beyond the lifetime of this project. The project outcomes will directly address the challenges of data analysis when data is obtained at Petabyte/year rates and contribute to a new research platform for accelerating discovery.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.