Related papers: Cosmology on a Mesh
We describe large scale structure at high redshift in terms of the Cosmic Web picture for {S,Lambda,O,H}CDM models: how galactic-scale ``peak-patches'', filaments and membranes create an interconnected intergalactic medium. The ideas are…
LCDM is remarkably successful in predicting the cosmic microwave background and large-scale structure, and LCDM parameters have been determined with only mild tensions between different types of observations. Hydrodynamical simulations…
Multilayer metasurfaces (MLMs) represent a versatile type of three-dimensional optical metamaterials that could enable ultra-thin and multi-functional photonic components. Herein we demonstrate an approach to readily fabricate MLMs…
Detecting and analyzing the local environment is crucial for investigating the dynamical processes of crystal nucleation and shape colloidal particle self-assembly. Recent developments in machine learning provide a promising avenue for…
We present a novel method to significantly speed up cosmological parameter sampling. The method relies on constructing an interpolation of the CMB-log-likelihood based on sparse grids, which is used as a shortcut for the…
Nature is remarkably adept at using interfaces to build structures, encapsulate reagents, and regulate biological processes. Inspired by Nature, we describe flexible polymer-based ribbons, termed "mesoscale polymers" (MSPs), to modulate…
We present the Locally Adaptive Morphable Model (LAMM), a highly flexible Auto-Encoder (AE) framework for learning to generate and manipulate 3D meshes. We train our architecture following a simple self-supervised training scheme in which…
After two decades of direct dynamical simulation of large-scale structure in the universe, it is safe to say the subject is now mature. Still, there are parts of the problem that are less well developed than others. In general, the…
We carry out adaptive mesh refinement (AMR) cosmological simulations of Milky-Way mass halos in order to investigate the formation of disk-like galaxies in a {\Lambda}-dominated Cold Dark Matter model. We evolve a suite of five halos to z =…
Cosmological simulations play an important role in the interpretation of astronomical data, in particular in comparing observed data to our theoretical expectations. However, to compare data with these simulations, the simulations in…
We present a new exploratory framework to model galaxy formation and evolution in a hierarchical universe by using machine learning (ML). Our motivations are two-fold: (1) presenting a new, promising technique to study galaxy formation, and…
Understanding the large-scale structure of the universe remains a fundamental challenge in cosmology, with computational simulations providing critical insights into non-linear structure growth. Particularly, computational simulations…
I present a large set of high resolution simulations, called CosmicGrowth Simulations, which were generated with either 8.6 billion or 29 billion particles. As the nominal cosmological model that can match nearly all observations on…
Canada has thriving communities in CMB (cosmic microwave background) studies, cosmology and submillimetre (submm) astronomy, with involvement in many facilities that featured prominently in previous Astronomy Long Range Plans. The standard…
Next-generation tests of fundamental physics and cosmology using large scale structure require measurements over large volumes of the Universe, including high redshifts inaccessible to present-day surveys. Line intensity mapping, an…
Heliospheric plasmas require multi-scale and multi-physics considerations. On one hand, MHD codes are widely used for global simulations of the solar-terrestrial environments, but do not provide the most elaborate physical description of…
MRChem is a code for molecular electronic structure calculations, based on a multiwavelet adaptive basis representation. We provide a description of our implementation strategy and several benchmark calculations. Systems comprising more…
Matter evolved under influence of gravity from minuscule density fluctuations. Non-perturbative structure formed hierarchically over all scales, and developed non-Gaussian features in the Universe, known as the Cosmic Web. To fully…
We present a collection of new, open-source computational tools for numerically modeling recent large-scale observational data sets using modern cosmology theory. Specifically, these tools will allow both students and researchers to…
Machine learning interatomic potentials (MLIPs) have become powerful tools to extend molecular simulations beyond the limits of quantum methods, offering near-quantum accuracy at much lower computational cost. Yet, developing reliable MLIPs…