Understanding the circumgalactic medium--the gaseous halo surrounding a galaxy, is an integral part to understanding galaxy evolution. The z ~ 2-3 universe is interesting as this is when the star formation rate and AGN activity peak. My work concludes the decade-long Quasars Probing Quasars survey designed for studying massive galaxy formation and quasar feedback. I […]

The line-of-sight power spectrum (P_F(k)) of the Ly-α forest has proven to be a valuable tool for doing cosmological observations. It also not only allows to constrain cosmological parameters, but enables us to measure the thermal state of the IGM at redshifts z>1.8. While at large scales (k<0.02 s/km) P_F(k) has been accurately measured using […]

Deep Learning has revolutionized the fields of computer vision, speech recognition and control systems. Can Deep Learning (DL) work for scientific problems? This talk will explore a variety of DOE/LBL applications that are currently benefiting from Deep Learning. We will review classification and regression problems in astronomy, cosmology, neuroscience, genomics and high-energy physics. We will […]

I will describe our development of a convolutional neural network (CNN) to learn to search for and characterize absorption lines in quasar spectra. Specifically, the algorithm discovers and measures the redshift and Hydrogen column density of damped Lya systems (DLAs). These systems dominate the neutral hydrogen gas of the universe, trace the interstellar medium of […]

In the last few years, the dark matter field has bifurcated into experiments focused on wimp-scale dark matter with massive liquid noble detectors and experiments focused on so-called ‘hidden sectors’ dark matter, pushing small detectors to much lower energy resolutions. Low-mass dark matter searches, focusing on single eV-scale energy deposits, are sensitive to different backgrounds […]