Related papers: A High Throughput Workflow Environment for Cosmolo…
The use of high-quality simulated sky catalogs is essential for the success of cosmological surveys. The catalogs have diverse applications, such as investigating signatures of fundamental physics in cosmological observables, understanding…
As part of the EU-funded Center of Excellence SPACE (Scalable Parallel Astrophysical Codes for Exascale), seven commonly used astrophysics simulation codes are being optimized to exploit exascale computing platforms. Exascale cosmological…
High performance computing numerical simulations are today one of the more effective instruments to implement and study new theoretical models, and they are mandatory during the preparatory phase and operational phase of any scientific…
Very High Resolution satellite and aerial imagery are used to monitor and conduct large scale surveys of ecological systems. Convolutional Neural Networks have successfully been employed to analyze such imagery to detect large animals and…
Galactic cosmic rays are the high-energy particles that stream into our solar system from distant corners of our Galaxy and some low energy particles are from the Sun which are associated with solar flares. The Earth atmosphere serves as an…
A large scientific community depends on the precise modelling of complex processes in particle cascades in various types of matter. These models are used most prevalently in cosmic-ray physics, astrophysical-neutrino physics, and gamma-ray…
Ground and space-based sky surveys enable powerful cosmological probes based on measurements of galaxy properties and the distribution of galaxies in the Universe. These probes include weak lensing, baryon acoustic oscillations, abundance…
We present a case study of a cloud-based computational workflow for processing large astronomical data sets from the Murchison Widefield Array (MWA) cosmology experiment. Cloud computing is well-suited to large-scale, episodic computation…
Exascale computers will offer transformative capabilities to combine data-driven and learning-based approaches with traditional simulation applications to accelerate scientific discovery and insight. These software combinations and…
The ability to test the nature of dark mass-energy components in the universe through large-scale structure studies hinges on accurate predictions of sky survey expectations within a given world model. Numerical simulations predict key…
Several cosmological measurements have attained significant levels of maturity and accuracy over the last decade. Continuing this trend, future observations promise measurements of the statistics of the cosmic mass distribution at an…
Powerful new observational facilities will come online over the next decade, enabling a number of discovery opportunities in the "Cosmic Frontier", which targets understanding of the physics of the early universe, dark matter and dark…
Cosmological probes pose an inverse problem where the measurement result is obtained through observations, and the objective is to infer values of model parameters which characterize the underlying physical system -- our Universe. Modern…
Apache Spark is a Big Data framework for working on large distributed datasets. Although widely used in the industry, it remains rather limited in the academic community or often restricted to software engineers. The goal of this paper is…
Resolving the most fundamental questions in cosmology requires simulations that match the scale, fidelity, and physical complexity demanded by next-generation sky surveys. To achieve the realism needed for this critical scientific…
The architecture of Exascale computing facilities, which involves millions of heterogeneous processing units, will deeply impact on scientific applications. Future astrophysical HPC applications must be designed to make such computing…
$ $Future surveys could obtain tighter constraints on the cosmological parameters with the galaxy power spectrum than with the Cosmic Microwave Background. However, the inclusion of multiple overlapping tracers, redshift bins, and more…
Modern simulations and observations in Astronomy & Cosmology (A&C) produce massively large data volumes, posing significant challenges for storage, access and data analysis. A long-standing bottleneck in high-performance computing,…
The next generation of galaxy surveys will observe millions of galaxies over large volumes of the universe. These surveys are expensive both in time and cost, raising questions regarding the optimal investment of this time and money. In…
This paper presents a simulation workflow for generating synthetic LiDAR datasets to support autonomous vehicle perception, robotics research, and sensor security analysis. Leveraging the CoppeliaSim simulation environment and its Python…