A U-Net surrogate with multigroup attention pooling is trained on OpenMC sensitivity data and combined with gradient optimization to generate grid-based critical experiment geometries that achieve c_k values up to 0.97757 for HALEU fuel validation.
Methods for the numerical solution of the nonlinear Schrödinger equa- tion
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Establishes well-posedness in history space, Lipschitz and weak-star robustness, and compact global attractors with upper semicontinuity for semilinear reaction-diffusion equations with measure-valued delays.
Randompack is a permissively licensed C library implementing several RNG engines and 14 distributions with cross-platform reproducibility and competitive or superior speed compared to existing libraries.
Neumann-Neumann decomposition plus mass lumping enables fast sampling of Gaussian random fields on metric graphs while preserving theoretical convergence rates of the underlying finite-element scheme.
High-order essentially explicit discretizations using Fourier Galerkin plus projection-relaxation conserve mass, momentum, and energy for BBM, KdV, and NLS equations.
The paper presents MaRDI Open Interfaces, a package providing unified interfaces and automated language interoperability for nonlinear optimization.
New gas-phase measurements of C 1s binding energies in anthrone agree with ΔSCF calculations, and a benchmark of 44 core levels in molecules with 10-40 atoms yields a mean absolute error of 0.19 eV.
MaRDI Open Interfaces supplies common interfaces for nonlinear optimization solvers, shown via an application to physics-informed neural network training on the viscous Burgers' equation.
libwignernj is a library that evaluates standard Wigner symbols and related coefficients exactly to the last floating-point bit by keeping all intermediates as exact rationals using prime-exponent vectors and multiword Racah summation.
citing papers explorer
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Inverse Critical Experiment Design via Gradient Optimization and a Multigroup Attention-Based Neural Network Architecture
A U-Net surrogate with multigroup attention pooling is trained on OpenMC sensitivity data and combined with gradient optimization to generate grid-based critical experiment geometries that achieve c_k values up to 0.97757 for HALEU fuel validation.
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Kernel-Robust Dynamics for Reaction-Diffusion Equations with Measure-Valued Delay
Establishes well-posedness in history space, Lipschitz and weak-star robustness, and compact global attractors with upper semicontinuity for semilinear reaction-diffusion equations with measure-valued delays.
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Randompack: Cross-Platform Reproducible Random Number Generation and Distribution Sampling
Randompack is a permissively licensed C library implementing several RNG engines and 14 distributions with cross-platform reproducibility and competitive or superior speed compared to existing libraries.
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Efficient generation of Gaussian random fields on metric graphs via domain decomposition and mass matrix lumping
Neumann-Neumann decomposition plus mass lumping enables fast sampling of Gaussian random fields on metric graphs while preserving theoretical convergence rates of the underlying finite-element scheme.
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Conserving mass, momentum, and energy for the Benjamin-Bona-Mahony, Korteweg-de Vries, and nonlinear Schr\"odinger equations
High-order essentially explicit discretizations using Fourier Galerkin plus projection-relaxation conserve mass, momentum, and energy for BBM, KdV, and NLS equations.
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MaRDI Open Interfaces for Interoperable Nonlinear Optimization
The paper presents MaRDI Open Interfaces, a package providing unified interfaces and automated language interoperability for nonlinear optimization.
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Does the total energy difference method for modelling core level photoemission fail for bigger molecules?
New gas-phase measurements of C 1s binding energies in anthrone agree with ΔSCF calculations, and a benchmark of 44 core levels in molecules with 10-40 atoms yields a mean absolute error of 0.19 eV.
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Software package MaRDI Open Interfaces for improved interoperability in numerical optimization
MaRDI Open Interfaces supplies common interfaces for nonlinear optimization solvers, shown via an application to physics-informed neural network training on the viscous Burgers' equation.
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libwignernj: a reusable C/C++/Fortran/Python library for exact Wigner symbols and related coefficients
libwignernj is a library that evaluates standard Wigner symbols and related coefficients exactly to the last floating-point bit by keeping all intermediates as exact rationals using prime-exponent vectors and multiword Racah summation.