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Double cake talk:
Probing the High-Redshift Universe with Galaxy Line-Intensity Mapping
Extraction of HI 21cm signal from Low Frequency Radio Observations using ANN
- 2:00-2:15: Lauren
- [CII] as a Tracer of HI Gas in High-z Galaxies
- 2:15-2:30: Eric
- [CII] as a tracer of molecular and atomic gas
- 2:30-2:45: Allan
- Analyzing ALESS73.1 in CO and [CI]
- 2:45-3:00: Rebeca
- Star Formation Efficiency with FLARES
- 3:00-3:15: Hanga
- Searching through MOSFIRE Archival Data
Learning Galaxy Properties from Merger Trees with Mangrove
Efficiently mapping between baryonic properties and dark matter is a major challenge in astrophysics.
Although semi-analytic models (SAMs) and hydrodynamical simulations have made impressive advances in reproducing galaxy observables across cosmologically significant volumes, both still require significant computation times, and are hard to succinctly analyze, representing a barrier to many applications. Graph Neural Networks (GNNs) have recently proven to be the natural choice for learning physical relations. Among the most inherently graph-like structures found in astrophysics are the dark matter merger trees that encode the evolution of dark matter halos. In this cake talk I will introduce a new, graph-based emulator framework, Mangrove, and show that it emulates the galactic stellar mass, cold gas mass and metallicity, instantaneous and time-averaged star formation rate, and black hole mass with scatters two times lower than other methods across a simulation box of side length 75 Mpc/h in 40 seconds, 4 orders of magnitude faster than a SAM and 9 orders of magnitude faster than a hydro simulation. I’ll also show how Mangrove allows for quantification of the dependence of galaxy properties on merger history, making it possible to learn about the simulations on a new level. I will also compare Mangrove results to the current state of the art in emulating the dark matter – galaxy connection and show significant improvements for all target properties.
Mangrove is publicly available at https://github.com/astrockragh/Mangrove.
Kate: The formation and quenching of the first massive galaxies (status seminar)
In this talk I will summarise the work achieved so far in my PhD and discuss plans for the rest of the PhD. I will summarise two projects nearing completion that explore the formation and quenching of the first massive galaxies in COSMOS2020. The first, entitled “COSMOS2020: Explore the epoch of quenching at z>3 with a new colour diagram” presents a new colour diagram to find massive quenched galaxies in photometric data, and presents the results of this applied to the latest COSMOS catalog. The second, entitled ” COSMOS2020: Star formation histories of massive quiescent galaxies at 3<z<5 imply early mass assembly followed by rapid quenching” explores the use of non-parametric methods to reconstruct the stellar assembly of the first massive galaxies and answer the questions: when did they form, when did the quench, and possibly – how did they quench? The final part of the talk details my plans for exploring quenching with JWST, specifically using data from the Canadian NIRISS Unbiased Cluster Survey (CANUCS).
Adele: Probing CDM interactions in high-z galaxy clustering with the BUFFALO HST survey
Analyzing the clustering behavior of galaxies across a wide redshift range allows us to model the gravitational assembly of such structures over cosmic time. We achieve this by measuring the 2-point correlation of galaxies at 0.01 < z < 8.5, gravitationally lensed by the foreground cluster Abell370 in BUFFALO. With this understanding, we can probe our current model of Cold Dark Matter (CDM), specifically the assumption that it interacts solely through gravitation. More importantly, studying galaxies at high redshift gives us a more complete picture of clustering at various snapshots in time. In this talk, I will summarize how the correlation function informs us about galaxy clustering behavior, my results from running correlation functions in both the COSMOS 2020 and BUFFALO surveys, and share how predictive clustering calculations at different redshift and mass bins compare to measured correlations.
Riely: Evidence for Inside-Out Growth in Galaxy Simulations
Recent observations have found a correlation for galaxies between their gas temperatures in star-forming clouds and specific Star Formation Rate (sSFR). The resulting model has led to several new predictions, such as inside out galaxy growth, compact galaxies at high redshifts and distinct morphological phases of galactic evolution. We employ GIDGET, a one-dimensional semi-analytical radius dependent galaxy evolution model, to explore these observational results. We find broadly similar behaviour of inside out galaxy growth and changing morphology. Additionally, we present new predictions for the nature of galaxy evolution with implications for their behaviour right after formation and for the extrapolation of the star-forming main sequence to lower masses.
Ethan: Unlocking Star Formation in Galactic Photometry
Understanding star-formation conditions and its associated Initial Mass Function (IMF) is critical to deriving galactic properties and their evolution in the universe. Although the IMF has traditionally been inconclusive beyond the local universe, recent research at DAWN parameterized the IMF in the EAZY photometric fitting code. Here, we employ the same IMF parameterization in LePhare, a fundamentally different method of fitting photometry. Results from fitting thousands of galaxies in extensive catalogs suggest systematic variations in the IMF over time that are similarly consistent with EAZY, further verifying that most galaxies exhibit top-heavier stellar populations than in the Milky Way. In addition, LePhare extracts relationships of the variable IMF with properties of star-forming and quenched populations, yielding a more complete and accurate picture of galactic evolution.
Thomas: Constraints and Predictions on Alternatives to Dark Energy
Recent studies find that measurements of the Hubble constant (H0) determined from the Cosmic Microwave Background are ~9% lower than measurements of H0 from much lower-redshift supernova observations. Several possible modifications to the standard ΛCDM cosmological model have been proposed to explain this discrepancy. A re-analysis of the supernova dataset finds that there are actually two discrepancies: one in H0 but another in the composition of the Universe as well. We show that the models designed to fix this “Hubble Tension” are incapable of correcting each simultaneously. And in a different, simple class of dark energy models, we show these quantities are not only preserved, but meet other observations including Ωmh2. These models predict drastic differences for the future of the Universe than those under ΛCDM—possibly even in the present.
Title: AGN Activity and Environment of Massive Quiescent Galaxies at High Redshift
Abstract: Recent multi-band observations have found that galaxies with suppressed star formation activity exist even in the high redshift universe. The state-of-art spectrograph has now confirmed them up to z~4. On the other hand, it is not well understood why they get quenched at such a high redshift and where they live. Here, I will introduce our two recent works for quiescent galaxies in the COSMOS field, (1) X-ray (Chandra) and radio (VLA) stacking analysis to explore their AGN activity and its connection to quenching and (2) the discovery of an overdense structure of quiescent galaxies at z=2.77 which are likely to be a new type of protocluster with the Keck/MOSFIRE observation.