David Hendel

Postdoctoral Fellow

I am an astrophysicist specializing in galactic dynamics. Much of my work examines the destruction of satellite galaxies to understand their original properties as well as the current shape and past history of the larger galaxies that shred them.

I completed my PhD at Columbia University with Kathryn Johnston in 2018 and am now a postdoc at the University of Toronto. I recieved a B.S. in Physics from the University of North Carolina at Chapel Hill in 2011.

Header photo: Jean-Charles Cuillandre (CFHT) & Giovanni Anselmi (Coelum)


  • Galactic dynamics, assembly, and evolution
  • Astrophysical probes of dark matter
  • Astronomical data & large survey science
  • Near-field cosmology
  • Drinking coffee
  • Public outreach, large & small

Research highlights

Below are a selection of topics from my work; see also my CV.

Tidal debris morphology

In Hendel & Johnston 2015 we examined the physics that control the phase mixing of tidal debris to develop a "morphology metric" that can predict the final appearance of minor mergers. We proposed that observed fraction of galaxies with different kinds of substructure could be used to infer the orbits of their infalling satellites, an otherwise difficult to assess dimension of galactic assembly.

Anatomy of the Orphan Stream

Using Spitzer Space Telescope photometry and the latest period-luminosity-metallicity relations, Hendel et al. 2018 presented 2.5% distances to RR Lyrae stars along the Orphan stellar tidal stream. By fitting to both the observed distribution and N-body models with constraints from Hubble Space Telescope proper motion measurments, we determined that the stream's progenitor was most likely small galaxy similar to the classical dwarf spheroidals like Sculptor or Leo I.

Automatic classification of tidal debris

In Hendel et al. 2019 I demonstrated a new machine-vision method to automatically identify and classify halo substructure, the first of its kind. This type of tool is necessary in the new era of big-data astronomy, where traditional by-eye classifiation is difficult or impossible. The technique will likely have applications across all kinds of other datasets, too!

Contact me

I am always happy to talk about astronomy for fun or collaboration. Send me an email with the form below or the social buttons at the bottom right!