PIRSA:16030130

Data Science in Radio Cosmology

Shaw, R. (2016). Data Science in Radio Cosmology. Perimeter Institute. https://pirsa.org/16030130

Shaw, Richard. Data Science in Radio Cosmology. Perimeter Institute, Mar. 24, 2016, https://pirsa.org/16030130 

          @misc{ pirsa_PIRSA:16030130,
            doi = {10.48660/16030130},
            url = {https://pirsa.org/16030130},
            author = {Shaw, Richard},
            keywords = {Other},
            language = {en},
            title = {Data Science in Radio Cosmology},
            publisher = {Perimeter Institute},
            year = {2016},
            month = {mar},
            note = {PIRSA:16030130 see, \url{https://pirsa.org}}
          }

Richard Shaw University of British Columbia

DOI 10.48660/16030130
Collection
Talk Type Scientific Series
Subject

Abstract

In recent decades probing for the subtle indications of new physics in
experimental data has become increasingly difficult. The datasets have gotten
much bigger, the experiments more complex, and the signals ever smaller. Success
stories, like LIGO and Kepler, require a sophisticated combination of statistics
and computation, coupled with an appreciation of both the experimental realities
and the theoretical framework governing the data.

In this talk I will look broadly at data science in physics, and how and why it
has taken an increasingly central role. I'll highlight specifically my current
area of research, radio cosmology: discussing why it is one of the most
challenging areas for data science, and describing my work developing optimal
and efficient statistical methods for turning terabytes of timestreams into
cosmology.