archive
Every paper Pith has read. Search by title, abstract, or pith.
1525 papers in math.NA · page 18
-
Hybrid scheme tracks Buckley-Leverett shocks with multiwavelets
A bounded-interval multiwavelet formulation with conservative finite-volume transport for one-dimensional Buckley--Leverett waterflooding
-
Affine normals match Newton steps on quadratics
Yau's Affine Normal Descent: Algorithmic Framework and Convergence Analysis
-
Planar aromatic trees span free algebra for manifold integrators
The free tracial post-Lie-Rinehart algebra of planar aromatic trees for the design of divergence-free Lie-group methods
-
Critical q values trigger collapse in kernel point placements
Critical phase transitions in minimum-energy configurations for the exponential kernel family $e^{-|x-y|^q}$ on the unit interval
-
Morse-Bott condition splits Gross-Pitaevskii ground states by symmetry
Structure and symmetry of the Gross-Pitaevskii ground-state manifold
-
The paper studies the long-time behavior of temperature-driven compressible fluid flows…
Temperature-driven turbulence in compressible fluid flows
-
Truncation method gives rigorous bounds for plane Schrödinger eigenvalues
Rigorous Eigenvalue Bounds for Schr\"odinger Operators with Confining Potentials on $\mathbb{R}^2$
-
New ALE mapping keeps FSI velocities divergence-free
Stability Analysis of Monolithic Globally Divergence-Free ALE-HDG Methods for Fluid-Structure Interaction
-
Adjoint method works for nonsmooth definable parametric optimization
The adjoint state method for parametric definable optimization without smoothness or uniqueness
-
Preconditioning cuts saddle iterations from O(κ) to O(κ_M)
Computing Saddle Points in Stiff Problems via a Preconditioned High-index Saddle Dynamics Method
-
Mild augmentation matches full-rank RTE solver accuracy
Highly Efficient Rank-Adaptive Sweep-based SI-DSA for the Radiative Transfer Equation via Mild Space Augmentation
-
Linear-nonlinear fusion speeds neural PDE operator training
Linear-Nonlinear Fusion Neural Operator for Partial Differential Equations
-
Algorithm reduces tensor-train elementwise ops to cubic scaling
Fast elementwise operations on tensor trains with alternating cross interpolation
-
V-wedge primary potential keeps 2.5D resistivity errors under 0.1 percent
2.5-D Electrical Resistivity Forward Modelling with Undulating Topography using a Modified Half-Space Analytical Solution
-
Convex obstacle and impedance uniquely recovered from backscattering data
Inverse Obstacle Scattering from Multi-Frequency Near-Field Backscattering Data
-
OMP sparsity removes spurious poles from LSCF stability diagrams
Sparse stability diagrams of LSCF method via strategic pole destabilization using orthogonal matching pursuit
-
Colloid deposition model admits weak solutions without clogging
A mathematical model for colloids deposition in porous media combined with a moving boundary at the microscale: Solvability and numerical simulation
-
CPU replays exact NVIDIA GPU matrix multiplies without precision loss
Hawkeye: Reproducing GPU-Level Non-Determinism
-
New contour bounds tighten singular-value estimates for noisy matrices
Eigenvalue stability and new perturbation bounds for the extremal eigenvalues of a matrix
-
Neural net approximates Ginzburg-Landau minimizers for many kappa
GLENN: Neural network-enhanced computation of Ginzburg-Landau energy minimizers
-
Born-coordinate neural map cuts Helmholtz iterations 20-fold
Neural Preconditioned Born Series: A Metric-Matched Framework for Learning-based Preconditioners
-
Born-series residual map cuts Helmholtz solver iterations
Neural Preconditioned Born Series: A Metric-Matched Framework for Learning-based Preconditioners
-
Full densities advance through random iterations without Monte Carlo
A Full-Density Approach to Simulating Random Iteration Equations with Applications
-
Space-time SBP operators unify forward and adjoint wave simulations
A space-time dual-pairing summation-by-parts framework for forward and adjoint wave equations
-
Two-layer nets match polygonal level sets to speed Chan-Vese segmentation
Neural network parametrized level sets for image segmentation
-
Branch-free algorithms speed up high-precision arithmetic
Acceleration of multi-component multiple-precision arithmetic with branch-free algorithms and SIMD vectorization
-
Conditional expectations average out Brownian noise in deep PDE training
A deep backward regression-based scheme for high-dimensional nonlinear partial differential equations
-
Regression reformulation stabilizes deep PDE solvers beyond dimension 10
A deep backward regression-based scheme for high-dimensional nonlinear partial differential equations
-
Package reduces layered planets to simple Voigt rheologies
A user-friendly package and workflow for generating effective homogeneous rheologies for the study of the long-term orbital evolution of multilayered planetary bodies
-
Mixed FEM restores well-posedness for 3D Dirichlet vector Laplacian
A Mixed Finite Element Method for the Dirichlet Vector Laplacian in Three Dimensions
-
Aromatic indices reduce volume preservation to one dimension
Aromatic and clumped multi-indices: algebraic structure and Hopf embeddings
-
Linearized attention misses kernel regime at practical widths
Linearized Attention Cannot Enter the Kernel Regime at Any Practical Width
-
Finite element turns Burgers into stable port-Hamiltonian system
Discretization of the Burgers' equation as a port-Hamiltonian system
-
RUNNs recover discontinuous PDE solutions from H-2 sources
RUNNs: Ritz-Uzawa Neural Networks for Solving Variational Problems
-
Optimized designs sharpen identifiability of memory effects in solids
Optimal Experimental Design for Reliable Learning of History-Dependent Constitutive Laws
-
Superellipse fitting reconstructs compressor speedlines from sparse data
Physics-based Approximation and Prediction of Speedlines in Compressor Performance Maps
-
OptEMA optimizer adapts convergence to noise level automatically
OptEMA: Adaptive Exponential Moving Average for Stochastic Optimization with Zero-Noise Optimality
-
Two-grid penalty reaches O(Δt^{1/2}) rate for doubly reflected BSDEs
Two-grid Penalty Approximation Scheme for Doubly Reflected BSDEs
-
Direct solver compresses scattering system to O(ω D) size
An accelerated direct solver for scalar wave scattering by multiple transmissive inclusions in two dimensions
-
Decoupled stabilization removes bulk pollution from VEM kernel in hyperelasticity
An Investigation of Stabilization Scaling in Finite-Strain Virtual Element Methods for Hyperelasticity
-
Certified norms computed for deep neural networks
Certified and accurate computation of function space norms of deep neural networks
-
Latent autoencoder makes Kalman filter accurate for nonlinear systems
Latent Autoencoder Ensemble Kalman Filter for Nonlinear Data assimilation
-
Nitsche methods rewritten as minimization problems enforce mechanical constraints
Nitsche methods for constrained problems in mechanics
-
Trust-region method uncovers new FDDD phase in LB model
Discovering new phases via computing second-order stationary states of Landau-Brazovskii model
-
New theorem shows gradient descent avoids saddles with vanishing steps
A non-autonomous center-stable set theorem for saddle avoidance in optimization
-
Fejér filter gives finite-depth bounds for constrained QAOA
Finite-Depth, Finite-Shot Guarantees for Constrained Quantum Optimization via Fej\'er Filtering
-
Neural PDE solvers learn boundary-indexed operator families
One Operator to Rule Them All? On Boundary-Indexed Operator Families in Neural PDE Solvers
-
Kernel LMI with Riccati constraint approximates nonlinear HJB
Kernel-Based LMI Approaches to Solving the Hamilton-Jacobi-Bellman Equation and Nonlinear Optimal Control
-
Algorithm reduces incommensurate fractional stability to linear algebra
A Stability Testing Algorithm for Incommensurate Fractional Differential Equation Systems
-
Inexact preconditioners confine eigenvalues to unit disk centered at 1
Inexact versions of several block-splitting preconditioners for indefinite least squares problems