Results 51 to 60 of about 3,221,012 (201)
Toward an Efficient Shifted Cholesky QR for Applications in Model Order Reduction Using pyMOR
ABSTRACT Many model order reduction (MOR) methods rely on the computation of an orthonormal basis of a subspace onto which the large full order model is projected. Numerically, this entails the orthogonalization of a set of vectors. The nature of the MOR process imposes several requirements for the orthogonalization process.
Maximilian Bindhak +2 more
wiley +1 more source
On Sound Relative Error Bounds for Floating-Point Arithmetic
State-of-the-art static analysis tools for verifying finite-precision code compute worst-case absolute error bounds on numerical errors. These are, however, often not a good estimate of accuracy as they do not take into account the magnitude of the ...
baranowski +9 more
core +1 more source
The Climate Modeling Alliance Atmosphere Dynamical Core: Concepts, Numerics, and Scaling
Abstract This paper presents the dynamical core of the Climate Modeling Alliance (CliMA) atmosphere model, designed for efficient simulation of a wide range of atmospheric flows across scales. The core uses the nonhydrostatic equations of motion for a deep atmosphere, discretized with a hybrid approach that combines a spectral element method (SEM) in ...
Dennis Yatunin +18 more
wiley +1 more source
Continued fractions and their generalization, branched continued fractions, are the effective tools used to study special functions. In this aspect, an important problem of continued fractions and branched continued fractions is the study of their ...
M. V. Dmytryshyn +3 more
doaj +1 more source
Quantization in Control Systems and Forward Error Analysis of Iterative Numerical Algorithms [PDF]
The use of control theory to study iterative algorithms, which can be considered as dynamical systems, opens many opportunities to find new tools for analysis of algorithms.
Constantinides, GA +2 more
core +2 more sources
This article reviews and compares popular methods, some old and some recent, that produce time series having Poisson marginal distributions. The article begins by narrating ways where time series with Poisson marginal distributions can be produced.
Jiajie Kong, Robert Lund
wiley +1 more source
A Distributed and Incremental SVD Algorithm for Agglomerative Data Analysis on Large Networks
In this paper, we show that the SVD of a matrix can be constructed efficiently in a hierarchical approach. Our algorithm is proven to recover the singular values and left singular vectors if the rank of the input matrix $A$ is known.
Iwen, M. A., Ong, B. W.
core +1 more source
Abstract Machine learning (ML) weather models like GraphCast and NeuralGCM show forecasting promise but face fundamental limitations for data assimilation (DA) integration. This study reveals critical problems in error covariance representation and adjoint sensitivity patterns challenging their operational viability.
Xiaoxu Tian +2 more
wiley +1 more source
How Accurate is Richardson's Error Estimate?
ABSTRACT We consider the fundamental problem of estimating the difference between the exact value T$$ T $$ and approximations Ah$$ {A}_h $$ that depend on a single real parameter h$$ h $$. It is well‐known that if the error Eh=T−Ah$$ {E}_h=T-{A}_h $$ satisfies an asymptotic expansion, then we can use Richardson extrapolation to approximate Eh$$ {E}_h $$
Carl Christian Kjelgaard Mikkelsen +1 more
wiley +1 more source
Solving the Net Worth Optimization Problem
ABSTRACT The mean–variance optimization (MVO) model of Harry M. Markowitz is the foundation of quantitative portfolio construction and asset allocation. While Markowitz originally developed MVO for forming portfolios of tradable assets in isolation, it has been adapted for creating portfolios of tradable assets in the presence of non‐tradable assets ...
Paul D. Kaplan
wiley +1 more source

