Lukas M. Zalesky: Astrophysics

I am a PhD candidate at the University of Hawaii's Institute for Astronomy working in extragalactic astronomy. My specialties include using multiwavelength surveys to measure and characterize the ways galaxies evolve over billions of years as well as techniques involving gravitational lensing.

I obtained my B.S. in Astrophysics with a minor in Mathematics from College of Charleston's Honors College where I worked under Dr. George Chartas and graduated summa cum laude. My undergraduate thesis focused on creating and applying new methods to measure the spins of gravitationally lensed quasars using X-ray spectroscopy. Since then I have developed a new code for modeling the mass distributions of massive galaxy clusters for the purpose of measuring their magnification profiles due to gravitational lensing. For my dissertation, I am working under Dr. David Sanders on the Hawaii Twenty Square Degree Survey (H20), an ultra-deep (AB mag < 27.5) optical and near-infrared survey of the primary calibration fields of the Euclid mission. The H20 survey will obtain the single largest sample of galaxies with stellar mass estimates from times earlier than two billion years after the Big Bang.

Below I describe a few of the recent projects I have been a part of. For a more complete listing of my research projects, head over to my research page and check out my ADS history. Publicly available code and other useful documents I have contributed to are shared on my code/resources page. At the bottom of this page you'll find information about my outreach involvement, which I describe more fully on my outreach page.

The Hawaii Twenty Square Degree Survey

Combining ultra-deep Subaru Hyper Suprime-Cam and Spitzer Space Telescope imaging with Keck DEIMOS spectroscopy over the North Ecliptic Pole and Euclid Deep Field Fornax, the Hawaii Twenty Square Degree Survey (H20) will provide the most comprehensive view of the high-redshift universe to date. My role in this effort includes obtaining precision photometry using new techniques and software developed by our team and measuring the redshifts and physical properties of galaxies through multi-wavelength analysis of their spectral energy distributions. I am also the lead team member of the H20 survey in measuring the galaxy stellar mass function at high-redshift. See our website for more information.

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The Farmer Model-Based Photometry

Ultra-deep, panchromatic surveys like Hawaii Two-0 require new tools and strategies for generating astronomical source catalogs. With increasing survey depth, the fraction of sources which overlap with one another likewise increases. Additionally, when considering faint and distant sources (like those targeted by many upcoming, high-redshift focused surveys), robust photometry is paramount and statistical reliability of such measurements is required. With this in mind, we have developed The Farmer, a flexible pythonic wrapper of the profile-fitting software The Tractor (Lang & Hogg 2016), which enables superior photometric deblending and statistical insight into the properties measured during source extraction. The Farmer is designed to handle all of the requirements of a full-scale photometry pipeline, from source detection, model-fitting and forced photometry, through final catalog creation. See more in our paper, or check out the code/resources page for access to the code and documentation.

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AStroLens: Automatic Strong-Lens Modeling

In the past decade, numerous software packages have been written to model the mass distributions within galaxy clusters, providing measurements of their gravitational lensing ability and predictions of the locations and magnifications of strongly-lensed images. Many of these codes require substantial prior information about the lensing system in the form of numerous spectroscopic redshifts of lensed sources in order to build a quality lens model. But what if you don't have that prior information? For situations like these, I have written the code AStroLens, which requires only the photometric and geometric information of cluster galaxies to build a lens model and no other information. AStroLens uses parameters tuned on known lensing clusters to rapidly build models, enabling immediate insight to the magnification abilities of massive clusters. This code has been validated in two publications, and will soon become publicly available through my code/resources page.