Many-body localization in the age of classical computing
Statistical mechanics provides a framework for describing the physics of large, complex
many-body systems using only a few macroscopic parameters to determine the state of the …
many-body systems using only a few macroscopic parameters to determine the state of the …
Simulation intelligence: Towards a new generation of scientific methods
The original" Seven Motifs" set forth a roadmap of essential methods for the field of scientific
computing, where a motif is an algorithmic method that captures a pattern of computation …
computing, where a motif is an algorithmic method that captures a pattern of computation …
Global fluid simulations of edge plasma turbulence in tokamaks: a review
With ITER, the largest tokamak ever built, and the growing number of fusion energy startups
in the world, the need for numerical simulations has never been more crucial to progress …
in the world, the need for numerical simulations has never been more crucial to progress …
Scalable multi-FPGA design of a discontinuous Galerkin shallow-water model on unstructured meshes
FPGAs are fostering interest as energy-efficient accelerators for scientific simulations,
including for methods operating on unstructured meshes. Considering the potential impact …
including for methods operating on unstructured meshes. Considering the potential impact …
Using neural networks to solve the 2D Poisson equation for electric field computation in plasma fluid simulations
L Cheng, EA Illarramendi, G Bogopolsky… - arXiv preprint arXiv …, 2021 - arxiv.org
The Poisson equation is critical to get a self-consistent solution in plasma fluid simulations
used for Hall effect thrusters and streamer discharges, since the Poisson solution appears …
used for Hall effect thrusters and streamer discharges, since the Poisson solution appears …
Bayesian calibration with summary statistics for the prediction of xenon diffusion in UO2 nuclear fuel
The evolution and release of fission gas impacts the performance of UO 2 nuclear fuel. We
have created a Bayesian framework to calibrate a novel model for fission gas transport that …
have created a Bayesian framework to calibrate a novel model for fission gas transport that …
PETScML: Second-order solvers for training regression problems in Scientific Machine Learning
In recent years, we have witnessed the emergence of scientific machine learning as a data-
driven tool for the analysis, by means of deep-learning techniques, of data produced by …
driven tool for the analysis, by means of deep-learning techniques, of data produced by …
Performance Portable Solid Mechanics via Matrix-Free -Multigrid
Finite element analysis of solid mechanics is a foundational tool of modern engineering, with
low-order finite element methods and assembled sparse matrices representing the industry …
low-order finite element methods and assembled sparse matrices representing the industry …
Efficient parallelization for 3d-3v sparse grid Particle-In-Cell: Shared memory architectures
Abstract Particle-In-Cell (PIC) schemes are ones of the most broadly used numerical
methods in kinetic simulation of plasmas. The contribution of the present paper is dedicated …
methods in kinetic simulation of plasmas. The contribution of the present paper is dedicated …
[HTML][HTML] Accurate error estimation for model reduction of nonlinear dynamical systems via data-enhanced error closure
Accurate error estimation is crucial in model order reduction, to obtain small reduced-order
models as well as to certify their accuracy when deployed in downstream applications such …
models as well as to certify their accuracy when deployed in downstream applications such …