Project Description: This project studies how galaxies become chemically enriched as generations of stars produce and disperse heavy elements. Because these measurements rely on faint spectral features, which are especially difficult to detect in distant galaxies, parts of the population remain poorly characterized. To address this, we will use large datasets of millions of galaxy spectra and combine them (“stacking”) to recover otherwise undetectable signals.
The intern will work with the Astro Data Lab science platform (datalab.noirlab.edu), gaining experience in Python, database queries, and analysis of DESI spectroscopic data (desi.lbl.gov). They will apply statistical methods, build composite spectra, and measure chemical abundances.
The internship includes regular team interactions and will culminate in a short research report and presentation. This project provides training in modern astronomical data analysis while contributing to our understanding of galaxy evolution.
NASA Relevance: This project aligns with NASA SMD’s mission by using large spectroscopic datasets to investigate how galaxies evolve and become chemically enriched, directly addressing fundamental questions about the origins and evolution of the universe.
Work Description: The internship will involve developing well-documented Jupyter Notebooks on galaxy spectral stacking and line measurements using the Astro Data Lab platform. Key tasks include writing Python code, querying databases to retrieve galaxy measurements, and using visualization tools.
The intern will also learn to retrieve spectra with the SPARCL software (astrosparcl.datalab.noirlab.edu), combine them into high-quality composite spectra, and run spectral fitting routines to measure line strengths and infer chemical abundances. They will also use GitHub for version control and sharing notebooks.
A significant component of the internship will be writing a short research paper or a research note based on the results, including reading relevant literature, drafting, incorporating feedback, and preparing a submission.
This experience will be invaluable for applications to graduate programs by providing essential research skills and practical experience in astronomical data analysis.
Open or Reserved Project: Reserved/Open, 1 position reserved for student but mentor may be willing to work with another student if reserved student isn't selected.