Hello, I’m Ze’ev Vladimir, a post-baccalaureate researcher at the University of Chicago working with Dr. Jacob Bean. I will be attending the University of Arizona this Fall as a Ph.D. candidate and I’m very excited to be working with Dr. Gurtina Besla. As an undergraduate I worked with Dr. Benedikt Diemer at the University of Maryland.
My primary interests are in how computational techniques can be applied to better understand galaxy formation, evolution, and dynamics. I use N-body simulations, hydrodynamical simulations, and machine learning techniques to better understand galaxies and dark matter.
About
I have some information about my personal interests and community work in About Me. For information about my research projects see any of the overview pages which are listed below.
Research Projects
Exoplanet Search with the Radial Velocity Method
My current work is with Dr. Jacob Bean at the University of Chicago to reduce the data produced by MAROON-X, an instrument on the Gemini-North telescope. This reduction process takes the raw CCD images and through careful calibrations produces extremely precise radial velocity measurements of stars. With these radial velocities we, and our collaborators, are able to find and characterize exoplanets.
For a more in-depth explanation please check out MAROON-X Overview
Dark Matter Halo Characterization with Machine Learning
Dark matter halos are one of the key building blocks in our universe and are the hosts of galaxies. Understanding their shape is important to understanding how galaxies themselves form and evolve as well as providing an essential probe into what dark matter is. With Dr. Benedikt Diemer at the University of Maryland I trained a machine learning model, XGBoost, to accurately and quickly identify which dark matter particles in an N-body simulation belong to a dark matter halo. With this we were able to more effectively determine the halo’s structure than comparable methods.
For more information check out:
- Distinguishing Orbiting and Infalling Dark Matter Particles with Machine Learning. Vladimir, Z., Osinga, C., Diemer, B., Salazar, E. M., & Rozo, E. — The Astrophysical Journal, 2025 Paper | arXiv | Code
- ATHENA Overview
Dwarf Galaxy versus Stellar Cluster
Dwarf galaxies, the smallest galaxies, provide an excellent “laboratory” to study both galaxies and dark matter. Based on characteristics of these galaxies like their mass, luminosities, or what stars are present we can place constraints on different models of dark matter. These constraints will help us eliminate certain models and narrow the possibilities that need to be tested. With Dr. Andrey Kravstov at the University of Chicago I am running N-body simulations of a potential dwarf galaxy, Ursa Major III / UNIONS 1. We are looking for an observable stellar stream from which we would be able to determine if it is indeed the smallest dwarf galaxy ever found.
Navigating the Website
I also am trying to make my website as accessible as possible to people from a broad range of backgrounds. You have probably noticed links like Example Link which take you to different pages within the website much like Wikipedia. Additionally, if you are on a computer you can just hover over these links to get a quick look!
I’ve tried to provide definitions, illustrations, videos, and links to additional resources where possible. The goal is to provide a broader understanding of some key astrophysical concepts which motivate the very specific work I do. Additionally, as you navigate, you will see some of these pages have the following call outs:
For everyone!
These blocks indicate the information is for people of any background. Expect more digestible explanations that leave out the more technical details/nuances. They also might include longer descriptions of plots or results to help everyone learn.
Slightly more technical
These blocks indicate that the topics will contain more complex material, often more jargon or equations. They are intended for an audience with background in astrophysics but not so difficult to scare anyone off. So if you’re interested in a particular topic definitely check these out too!
Contact
Email: zevvladimir3002@gmail.com
