VLBI data on TXS 2005+403 show refractive substructure from interstellar turbulence that cannot be explained by diffractive scattering alone and remains stable over nine years.
Makie.jl: Flexible high-performance data visualization for Julia
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DenseAMs show tradeoffs between entropy production, retrieval accuracy, and speed at intermediate loads, with a new failure mode in higher-order networks at finite temperature.
Exact sampling algorithm for Pfaffian point processes via skew-symmetric Cholesky factorization, together with a symplectic Arnoldi method for constructing skew-orthogonal polynomial kernels.
An adaptive anisotropic composite quadrature strategy combined with refresh-based training narrows the gap between training and reference losses in neural residual minimization for PDEs while using quadrature points more efficiently.
High-order essentially explicit discretizations using Fourier Galerkin plus projection-relaxation conserve mass, momentum, and energy for BBM, KdV, and NLS equations.
Domain-of-dependence stabilization for cut-cell meshes achieves fully discrete stability for linear advection under a CFL condition independent of arbitrarily small cell sizes.
citing papers explorer
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Direct VLBI Detection of Interstellar Turbulence Imprint on a Quasar: TXS 2005+403
VLBI data on TXS 2005+403 show refractive substructure from interstellar turbulence that cannot be explained by diffractive scattering alone and remains stable over nine years.
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Stochastic Thermodynamics of Associative Memory
DenseAMs show tradeoffs between entropy production, retrieval accuracy, and speed at intermediate loads, with a new failure mode in higher-order networks at finite temperature.
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Sampling Pfaffian point processes and the symplectic Arnoldi method
Exact sampling algorithm for Pfaffian point processes via skew-symmetric Cholesky factorization, together with a symplectic Arnoldi method for constructing skew-orthogonal polynomial kernels.
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Adaptive anisotropic composite quadratures for residual minimisation in neural PDE approximations
An adaptive anisotropic composite quadrature strategy combined with refresh-based training narrows the gap between training and reference losses in neural residual minimization for PDEs while using quadrature points more efficiently.
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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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The domain-of-dependence stabilization for cut-cell meshes is fully discretely stable
Domain-of-dependence stabilization for cut-cell meshes achieves fully discrete stability for linear advection under a CFL condition independent of arbitrarily small cell sizes.