My Research

My main research program focuses on understanding gas flows around star-forming galaxies. Indeed understanding galactic outflows and gas accretion is a key requirement for developing a complete picture of how galaxies form since both inflows of the baryons and super-nova driven outflows play a major role in regulating the gas content of galaxies, their star-formation histories and their stellar evolution. Hence, the goal of my research program is thus to put direct observational constraints on the cycle of baryons moving in and out of galaxies.

One way to tackle this issue is to use background quasars passing near star-forming galaxies.  These quasars shed light on absorption lines from intervening clouds which in turn provides critical information on both the accreting of gas (inflow of fresh fuel) (Gas Fueling) and on the galactic wind (outflows of gas ejected) phenomenon (Winds properties).

Observational projects: Currently, my colleagues and I are embarked on several observational projects to tackle these issues:

  1. coI: The MUSE eXtremely Deep Field (MXDF)
  2. coI: The MUSE Hubble Ultra Deep Field Survey (UDF)
  3. PI: The MusE GAs FLow and Wind (MEGAFLOW) survey 2014-2018 based on UVES and MUSE has produced >8 Publications so far (with J. Zabl, I. Schroetter, M. Wendt, J. Freundlich).
  4. PI: The SINFONI MgII Program for Line Emitters (SIMPLE). This program started in 2007 and was funded by a EU Career Integration Grant.
  5. coI: The Keck galaxy-quasar pair program from 2011 to 2013.
  6. coI: The SINS survey

Theoretical analysis:

co-led:

Community software:

Another way to study galaxy formation is to constrain the kinematics of galaxies directly. This is now possible thanks to the recent technological development and in particular thanks to IFUs like SINFONI, MUSE, and KMOS.

Since 2012, I developed an advanced 3D tool to determine simultaneously the morphology and kinematic properties of galaxies from any 3D spectro-imaging data. The algorithm uses the full 3D data cube without projecting the data in 2D maps (see GalPak3D) and is able to recover the kinematics down to very low signal-to-noise ratios.