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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Introduces multi-time renewal chains via multi-index convolution and power series, with FFT-based computation, asymptotic theorems under proportional growth, and a nonparametric MLE for fixed-horizon censored data.
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.
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Discrete time-multidimensional renewal theory and applications
Introduces multi-time renewal chains via multi-index convolution and power series, with FFT-based computation, asymptotic theorems under proportional growth, and a nonparametric MLE for fixed-horizon censored data.