Results 61 to 70 of about 78,319 (219)
Krylov Subspace Recycling for Evolving Structures
CoRR, 2020 Krylov subspace recycling is a powerful tool for solving long series of large, sparse linear systems that change slowly. In PDE constrained shape optimization, these appear naturally, as hundreds or more optimization steps are needed with only small changes in the geometry.
Matthias Bolten +2 more
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Analysis of Eigenvalue Clustering Leads to Optimal Scaling in Numerical Radiative Transfer
Numerical Linear Algebra with Applications, Volume 33, Issue 5, October 2026.ABSTRACT We consider a multidimensional polychromatic radiative transfer (RT) problem, accounting for scattering processes in a general form, that is, anisotropic (dipole) scattering with partial frequency redistribution. Given a discrete ordinates (SN$$ {S}_N $$) discretization, we report the corresponding matrix structures, depending on the model and
Pietro Benedusi +3 more
wiley +1 more source
Krylov Subspace Methods in the Electronic Industry [PDF]
, 2006 In most practical cases, the convergence of the GMRES method applied to a linear algebraic system Ax -- b is determined by the distribution of eigenvalues of A. In theory, however, the information about the eigenvalues alone is not sufficient for determining the convergence. In this paper the previous work of Greenbaum et al.
Heres, P.J., Schilders, W.H.A.
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Quantum Spectral Clustering Framework via Compact Circuit Structures
Advanced Quantum Technologies, Volume 9, Issue 10, October 2026.Can a quantum computer cluster data without ever reading the full kernel? This work shows that compact, parameterized circuits estimate the Laplacian quadratic forms directly and perform clustering, without explicitly constructing the full quantum fidelity‐kernel matrix.
Hyeong‐gyu Kim +2 more
wiley +1 more source
Journal of Geophysical Research: Solid Earth, Volume 131, Issue 10, October 2026.Abstract High‐resolution crustal‐scale seismic imaging from long‐offset ocean‐bottom seismometer (OBS) data using full‐waveform inversion (FWI) remains challenging because the large number of propagated wavelengths and waveform complexity make the inversion highly sensitive to time‐shift errors (cycle skipping). To mitigate this nonlinearity, we assess
Gaoshan Guo +2 more
wiley +1 more source
Fractal and FractionalTo better simulate the prices of underlying assets and improve the accuracy of pricing financial derivatives, an increasing number of new models are being proposed.
Xu Chen +3 more
doaj +1 more source
Multiphysics Simulation of Positive Streamer Discharge in Air Using Finite Element Method
International Journal for Numerical Methods in Engineering, Volume 127, Issue 18, 30 September 2026.ABSTRACT Streamer discharge modeling by means of the Finite Element Method (FEM) presents a formidable challenge in computational physics due to its nonlinear and convection‐dominated characteristics that cause numerical instabilities, including negative densities of charged particles.
Hasupama Jayasinghe +3 more
wiley +1 more source
Krylov subspace methods in the electronic industry [PDF]
, 2004 Summary. Krylov subspace methods are well-known for their nice properties, but they have to be implemented with care. In this article the mathematical consequences encountered during implementation of Krylov subspace methods in an existing layout ...
Schilders, W.H.A. +3 more
core
Compile‐Once Block Encodings for Masked Similarity‐Transformed Effective Hamiltonians
Advanced Quantum Technologies, Volume 9, Issue 9, September 2026.Composer transforms structured electronic‐structure operators into a reusable quantum‐circuit fabric. Once compiled, the same block‐encoding architecture is re‐dialed through coefficients, rotation angles, and masks to generate similarity‐transformed effective Hamiltonians across related problem instances, avoiding repeated structural recompilation ...
Bo Peng, Yuan Liu, Karol Kowalski
wiley +1 more source
Detecting When One Probe Vector is Enough for Preconditioned Log‐Determinant Approximation
Numerical Linear Algebra with Applications, Volume 33, Issue 4, August 2026.ABSTRACT We present randomized algorithms for estimating the log‐determinant of regularized symmetric positive semi‐definite matrices. The algorithms access the matrix only through matrix vector products, and are based on the introduction of a preconditioner and stochastic trace estimator.
Alice Cortinovis, Daniele Toni
wiley +1 more source