Kim Venn

Kim Venn
Professor, Director (ARC, NTCO)
Physics and Astronomy
Office: Elliott 111
Area of expertise

Discovery and analysis of the oldest metal-poor stars to study the fossil record of the formation and evolution of the Galaxy and the origin of the elements.

Astronomy Research

My main research interests are on the formation and evolution of dwarf galaxies, globular clusters, and stellar systems and the origin of the elements.   I primarily use stellar spectroscopy for this work, specializing in the discovery and analysis of the most metal-poor stars in our Galaxy and its satellites.  This research is primarily funded through my NSERC Discovery Grant, and also through our NSERC CREATE program on New Technologies for Canadian Observatories.

Observational Studies:

My group is currently working on spectra taken with the Gemini Observatory GRACES spectrograph as part of our Large and Long Program (GN-LP-102).  We were granted nearly 200 hours over 3 years to observe the spectra of newly discovered very metal-poor stars found in the Pristine survey.   The Pristine survey is a Canada-France-Hawaii Telescope MegaCam imaging program using a new narrow-band filter to discover and map metal-poor stars throughout the Galaxy and Local Group satellites.   Metal-poor stars are particularly fascinating in that they provide a fossil record of the earliest stages in the formation of their host galaxies, as well as providing unique constraints on the nucleosynthesis and origins of the chemical elements.   The Pristine survey is providing metal-poor target to the European WEAVE high-resolution spectroscopic survey, and we are now preparing for the first light from that survey in mid-2022.   

My group is also involved with commissioning and early science verification of the Gemini Observatory GHOST spectrograph, planned for early 2022.   We are excited to use this new and uniquely designed high resolution spectrograph for the analysis of metal-poor stars in the nearby dwarf galaxies and globular clusters, as part of a new Gemini-South Large and Long Program.   We plan to explore the build up of the light elements through the different histories of supernova events in each dwarf galaxy, as well as the origins of the very heavy elements through massive stars, supernovae, and neutron star mergers.

Machine Learning:

My group has been exploring the new machine learning tools for the fast and efficient analysis of stellar spectra at the rates expected from the ongoing stellar spectral survey (such as the European WEAVE survey).   Using various synthetic spectral grids with a range of data augmentations, we are exploring the precision and accuracy in stellar parameters using a variety of neural network architectures.   We also explore the uncertainties not only in the data sets and imposed by the synthetic gaps, but also in the machine learning calculations themselves, e.g., through deep ensembling.   Comparisons with radiative transfer solutions using classical stellar model atmospheres and other diagnostics are also important tests for benchmarking these results. This is a growing field of research with many interesting applications istellar spectroscopy and astronomy more generally.

Sample Projects available for Students

  • Spectroscopy of heavy elements of metal-poor stars in dwarf galaxies.
  • Spectroscopy of metal poor stellar streams, and other novel stellar groups in our Galaxy.
  • GHOST spectrograph commissioning and science verification.
  • Machine learning techniques for a variety of large and small spectroscopic data sets. 
  • Heavy elements in globular clusters with high frequencies of X-ray sources.