Cosmology Data Analysis for the Dark Energy Spectroscopic Instrument
Martin White, Professor
Physics
Applications for Spring 2025 are closed for this project.
The Dark Energy Spectroscopic Instrument (DESI) survey is measuring the expansion history of our universe with unprecedented precision. By measuring the light from tens of millions of extragalactic objects, the DESI team aims to understand the nature of dark energy and how it has shaped our universe. Critical to DESI’s goals is the Lyman-alpha forest that is imprinted in the spectra of the most distant objects observed by the survey, quasars. The Lyman-alpha forest is caused by absorption from neutral hydrogen in the intergalactic medium along the line of sight to quasars. It therefore provides a map of the matter density between us and the quasars we observe. Various astrophysical sources can contaminate this map, requiring automated techniques to identify and remove them. This project focuses on stress testing these techniques to determine their efficiency and accuracy.
Role: In this project, the student will learn to analyze spectroscopic data from DESI to assist with cosmological measurements. The student will learn to run the detection pipeline, manipulate astronomical spectra, and perform data analysis. Future tasks could include improving our contaminant detection algorithms based on findings. Opportunities may be available for co-authorship on peer-reviewed publications depending on progress.
Qualifications: Interest in astronomy/cosmology with some astronomy courses preferred, basic python experience required.
Day-to-day supervisor for this project: Dr. Allyson Brodzeller, Post-Doc
Hours: to be negotiated
Off-Campus Research Site: Lawrence Berkeley National Lab Building 50 and remote work
Related website: https://data.desi.lbl.gov
Related website: https://data.desi.lbl.gov