Related papers: GalacticFlow: Learning a Generalized Representatio…
Understanding the evolution of galaxies provides crucial insights into a broad range of aspects in astrophysics, including structure formation and growth, the nature of dark energy and dark matter, baryonic physics, and more. It is,…
Generative models that can model and predict sequences of future events can, in principle, learn to capture complex real-world phenomena, such as physical interactions. However, a central challenge in video prediction is that the future is…
Stars are fossils that retain the history of their host galaxies. Elements heavier than helium are created inside stars and are ejected when they die. From the spatial distribution of elements in galaxies, it is therefore possible to…
A tightly correlated star formation rate-stellar mass relation of star forming galaxies, or star-forming sequence (SFS), is a key feature in galaxy property-space that is predicted by modern galaxy formation models. We present a flexible…
We investigate the formation and evolution of dwarf galaxies in a high resolution, hydrodynamical cosmological simulation of a Milky Way sized halo and its environment. Our simulation includes gas cooling, star formation, supernova…
Modern hydrodynamic simulations of galaxy formation are able to predict accurately the rates and locations of the assembly of giant molecular clouds in early galaxies. These clouds could host star clusters with the masses and sizes of real…
Normalizing flow (NF) has gained popularity over traditional maximum likelihood based methods due to its strong capability to model complex data distributions. However, the standard approach, which maps the observed data to a normal…
In this work, we propose the Generative Latent Flow (GLF), an algorithm for generative modeling of the data distribution. GLF uses an Auto-encoder (AE) to learn latent representations of the data, and a normalizing flow to map the…
Galactic outflows are believed to play a critical role in the evolution of galaxies by regulating their mass build-up and star formation. Theoretical models assumes bipolar shapes for the outflows that extends well into the circumgalctic…
The accuracy and robustness of a simple method to estimate the total mass profile of a galaxy is tested using a sample of 65 cosmological zoom-simulations of individual galaxies. The method only requires information on the optical surface…
Normalizing Flows (NFs) are flexible explicit generative models that have been shown to accurately model complex real-world data distributions. However, their invertibility constraint imposes limitations on data distributions that reside on…
We examine the growth of the stellar content of galaxies from z=3-0 in cosmological hydrodynamic simulations incorporating parameterised galactic outflows. Without outflows, galaxies overproduce stellar masses (M*) and star formation rates…
(Abridged) The star-formation rate (SFR) quantitatively describes the star-formation process in galaxies. Current ways to calibrate this rate do not usually employ observational methods accounting for the low-mass end of stellar populations…
In search for a synthetic understanding, a scenario for the evolution of the star formation rate and the chemical abundances in galaxies is proposed, combining gas infall from galactic halos, outflow of gas by supernova explosions, and an…
We introduce a Variational Autoencoder (VAE)--Normalizing Flow (NF) framework for rapid probabilistic inference of galaxy properties and emission line fluxes at $z \leq 0.3$ from SDSS \textit{gri} imaging and photometry. Our model…
Precipitation is potentially a mechanism through which the circumgalactic medium (CGM) can regulate a galaxy's star formation. Here we present idealized simulations of isolated Milky Way-like galaxies intended to examine the ability of…
Solving decision problems in complex, stochastic environments is often achieved by estimating the expected outcome of decisions via Monte Carlo sampling. However, sampling may overlook rare, but important events, which can severely impact…
Generative flows are attractive because they admit exact likelihood optimization and efficient image synthesis. Recently, Kingma & Dhariwal (2018) demonstrated with Glow that generative flows are capable of generating high quality images.…
Galaxies evolve via a complex interaction of numerous different physical processes, scales and components. In spite of this, overall trends often appear. Simplified models for galaxy histories can be used to search for and capture such…
We outline a method to infer the global history of star formation in galaxies with input only from absorption-line observations of quasars. The application of the method to existing data leads to the conclusion that most stars formed at…