Astrophysics

Machine learning (ML) techniques are revolutionizing our ability to study galaxy evolution and large-scale structure. Convolutional neural networks (CNNs) can now reliably predict galaxies' physical properties, including cold gas content and...

Abstract: I will present several results on linear and nonlinear models, relating to the problem of stability/instability of the exterior region (up to and including the event horizon) of extremal Reissner-Nordstrom black hole spacetimes.

Each week, we hold a relatively informal seminar/discussion series with an emphasis on extra-galactic and large-scale structure astrophysics.

During Galread a leader/visitor presents a recent paper to the discussion group. The PDF of the paper is...

Abstract: A sharp definition of what “adiabatic” means is given; it is then shown that the time-dependent expectation value of a quantum-mechanical observable in the adiabatic limit can be expressed— in many cases—by means of the appropriate Berry...

I will present surprising observational results on the 3D shapes and large-scale alignments of high-redshift galaxies from JWST. I will show that there are many more linear, elongated dwarf galaxies than there are round, circular dwarf galaxies seen...

The common observation that Jupiter's Galilean moons resemble a miniature Solar System has long been seen as evidence that young giant planets are surrounded by circumplanetary disks of gas and dust. Recently, one circumplanetary disk - around the...

Chandra is one of NASA's "great observatories" and was launched in 1999. In this talk, I will review Chandra's history and instruments and show highlights from an absolutely astonishing 25 years of science observations. 

A "30 ft orbiting X-ray...

Modern large-scale surveys have adopted “3x2pt" correlations as one of their key probes for extracting cosmological information. 3x2pt techniques combine gravitational lensing and clustering of (selected) large-scale structure tracers with the goal...