Galaxies and Cosmology Seminar
Oct
6
2025
Oct
6
2025
Description
Ana Sofia Uzsoy, Harvard Center for Astrophysics
Lyman Alpha Emitters in DESI: Automated Redshift Inference and Environmental Dependence
Lyman-Alpha Emitters (LAEs) are star-forming galaxies with significant Lya emission which are often used as tracers of large-scale structure at high redshift. We present a Bayesian spectral component separation technique to automatically determine spectroscopic redshifts for LAEs while marginalizing over sky lines. Using spectra of LAEs from the Dark Energy Spectroscopic Instrument (DESI), we create a data-driven prior and determine redshift by jointly inferring sky, LAE, and residual components for each individual spectrum. We then use this method to explore the relationship between the Lya line profile and environmental density with spectroscopy of LAEs selected with narrow-band photometry. At z = 3.1, the spectra show significantly higher Lya line luminosity for galaxies in denser environments, indicating an overdensity of ionized gas in these regions. This effect is not seen at z = 2.45, suggesting a redshift dependence. These data indicate a potential relationship between LAE local environmental density, ionized gas distribution, and Lya line luminosity, which has important implications for the use of LAEs as cosmological probes.
Yonny Sklansky, The University of Texas at Austin
A New Efficient Model for Reionization
Reionization marks the last major phase transition of the universe, when the first galaxies and black holes ionized the neutral IGM. Upcoming 21cm surveys will observe this period in detail, producing massive datasets that will require fast, flexible models to analyze. In this talk I will present a new analytic framework for reionization that is computationally efficient, modular, and physically motivated. By tracking the growth and clustering of ionized regions, this model will give us a powerful way to infer reionization. I will also briefly talk about a recent application of this model to line intensity mapping.
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