GPPU Seminar

Date

15:00—17:00, April 18th, 2025

Place

(hybrid) Room 745, Science Complex B (H-03), Zoom registration map

Abstract

1) The main tool astronomers have to understand distant galaxies is the light they have emitted. A galaxy’s spectral energy distribution (SED) is a measure of its flux density across the electromagnetic spectrum. This SED contains unique signatures which tell us how the galaxy formed and how it has evolved over cosmic time. From these SEDs we are able to recover key physical properties, which include but are not limited to: the stellar mass of the galaxy, the star formation rate of the galaxy, and the age of the galaxy. This is done by building theoretical models of how SEDs of various stellar populations would look like, and then finding the combination that best matches observed galaxy SEDs. Nevertheless, SEDs are not the only observable we have of galaxies. We also have high resolution images of them taken with telescopes, from which we can observe their morphologies (i.e their physical structure). Traditionally, unlike with SEDs, the information contained in the morphology of a galaxy has not been used to help derive its physical properties. However, we know there is a clear connection between physical properties and galaxy morphology. With the upcoming waves of unprecedented amounts of high quality imaging from space based telescopes like Euclid and Roman it is of utmost importance to make meaningful use of all this data. In this seminar I will present my work which uses state of the art machine learning to (i) show we can derive physical properties of galaxies just from imaging and (ii) create a new methodology for incorporating galaxy morphology information into existing SED fitting pipelines to get better constraints on the physical properties of galaxies.

2) When viewed from Earth, the entire sky is covered by Galactic interstellar dust, which absorbs, scatters, and re-emits light across a broad spectral range from millimeter waves to ultraviolet. Among these, nanoscale very small grains (VSGs)—containing 10² to 10⁴ atoms—are “mesoscopic” systems with unique thermal and optical properties. For example, at low temperatures, the quantization of energy levels limits the number of thermally accessible states, making it difficult to describe thermal properties using the conventional thermodynamical temperature. In this study, we construct a new emission model for carbonaceous VSGs by incorporating mesoscopic physics. We applied the method of energy level statistics to account for the effect of free electrons, which contribute to the thermal emission at low temperatures. We found that the spectral energy distribution of carbonaceous VSGs exhibits an excess emission at wavelengths beyond the submillimeter range. The observational implications of this result will be discussed. Interstellar dust—being extremely cold and isolated—provides an ideal environment to study mesoscopic physics. The future high-precision observational data will enable us to explore the detailed properties of interstellar dust that have previously been overlooked.

Point

GSP 1