Related papers: Galaxy Merger Reconstruction with Equivariant Grap…
This paper introduces a generative model equivariant to Euclidean symmetries: E(n) Equivariant Normalizing Flows (E-NFs). To construct E-NFs, we take the discriminative E(n) graph neural networks and integrate them as a differential…
Context. Generative models open up the possibility to interrogate scientific data in a more data-driven way. Aims: We propose a method that uses generative models to explore hypotheses in astrophysics and other areas. We use a neural…
The fraction of distant disks and mergers is still debated, while 3D-spectroscopy is revolutionizing the field. However its limited spatial resolution imposes a complimentary HST imagery and a robust analysis procedure. When applied to…
Galaxy merging is the late time manifestation of the galaxy formation process and likely significantly effects $z<1$ galaxies. A ``maximum reasonable rate'' model for merging finds a $\sim2$ mag K band increase in the luminosities of dwarf…
We introduce graph normalizing flows: a new, reversible graph neural network model for prediction and generation. On supervised tasks, graph normalizing flows perform similarly to message passing neural networks, but at a significantly…
Elliptical and S0 galaxies dominate the galaxy population in nearby rich clusters such as Coma. Studies of the evolution of the colors, M/L ratios, and line indices of early-type galaxies indicate that they have been a highly homogeneous,…
About two-thirds of present-day, large galaxies are spirals such as the Milky Way or Andromeda, but the way their thin rotating disks formed remains uncertain. Observations have revealed that half of their progenitors, six billion years…
Generative models have recently revolutionized image generation tasks across diverse domains, including galaxy image synthesis. This study investigates the statistical learning and consistency of three generative models: light-weight-gan (a…
We investigate the impact of hierarchical galaxy merging on the statistics of gravitational lensing of distant sources. Since no definite theoretical predictions for the merging history of luminous galaxies exist, we adopt a parametrized…
Massive galaxies, such as nearby ellipticals, have relatively low number densities, yet they host the majority of the stellar mass in the universe. Understanding their origin is a central problem of galaxy formation. Age dating of stellar…
I review the general progress made in the study of galaxy evolution concentrating on the impact of systematic ground-based spectroscopic surveys of faint galaxies and high resolution imaging with Hubble Space Telescope. The picture emerging…
We present a new version of the GALFORM semi-analytical model of galaxy formation. This brings together several previous developments of GALFORM into a single unified model, including a different initial mass function (IMF) in quiescent…
In order to prepare for the upcoming wide-field cosmological surveys, large simulations of the Universe with realistic galaxy populations are required. In particular, the tendency of galaxies to naturally align towards overdensities, an…
We estimate the evolution of the galaxy-galaxy merger fraction for $M_\star>10^{10.5}M_\odot$ galaxies over $0.25<z<1$ in the $\sim$18.6 deg$^2$ deep CLAUDS+HSC-SSP surveys. We do this by training a Random Forest Classifier to identify…
We test the hypothesis that elliptical galaxies are formed by violent mergers in a universe with hierarchical structure formation. Within the framework of a semi-analytic scheme for galaxy formation, we predict the distribution of…
Cumulative number density matching of galaxies is a method to observationally connect descendent galaxies to their typical main progenitors at higher redshifts and thereby to assess the evolution of galaxy properties. The accuracy of this…
Galaxy mergers are crucial for understanding galaxy evolution, and with large upcoming datasets, automated methods such as Convolutional Neural Networks (CNNs) are essential for efficient detection. It is understood that CNNs classify…
The Thesis is an attempt to combine data from three previously independent areas - the structure and kinematics of stellar populations of the Galaxy, photometric and dynamical models of galaxies, and models of the dynamical and physical…
We follow the evolution of the galaxy population in a Lambda-CDM cosmology by means of high-resolution N-body simulations in which the formation of galaxies and their observable properties are calculated using a semi-analytic model. We…
We introduce a framework for simultaneously investigating the structure and luminosity evolution of early-type gravitational lens galaxies. The method is based on the fundamental plane, which we interpret using the aperture mass-radius…