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To facilitate the numerical analysis of particle methods, we derive truncation error estimates for the approximate operators in a generalized particle method. Here, a generalized particle method is defined as a meshfree numerical method…

Numerical Analysis · Mathematics 2019-07-09 Yusuke Imoto

We first give an overview of the shell-correction method which was developed by V. M. Strutinsky as a practicable and efficient approximation to the general selfconsistent theory of finite fermion systems suggested by A. B. Migdal and…

Nuclear Theory · Physics 2015-03-17 A. G. Magner , I. S. Yatsyshyn , K. Arita , M. Brack

We study quadrature methods for solving Volterra integral equations of the first kind with smooth kernels under the presence of noise in the right-hand sides, with the quadrature methods being generated by linear multistep methods. The…

Numerical Analysis · Mathematics 2016-05-02 Robert Plato

Accurate calculations of the spectral density in a strongly correlated quantum many-body system are of fundamental importance to study its dynamics in the linear response regime. Typical examples are the calculation of inclusive and…

Nuclear Theory · Physics 2022-06-15 Joanna E. Sobczyk , Alessandro Roggero

We consider model selection and estimation for partial spline models and propose a new regularization method in the context of smoothing splines. The regularization method has a simple yet elegant form, consisting of roughness penalty on…

Methodology · Statistics 2013-11-25 Guang Cheng , Hao Helen Zhang , Zuofeng Shang

This paper is devoted to the study of a newly introduced tool, projectional coderivatives and the corresponding calculus rules in finite dimensions. We show that when the restricted set has some nice properties, more specifically, is a…

Optimization and Control · Mathematics 2024-10-24 Wenfang Yao , Kaiwen Meng , Minghua Li , Xiaoqi Yang

The present work shows a novel fractal dimension method for shape analysis. The proposed technique extracts descriptors from the shape by applying a multiscale approach to the calculus of the fractal dimension of that shape. The fractal…

Data Analysis, Statistics and Probability · Physics 2015-06-03 André R. Backes , João B. Florindo , Odemir M. Bruno

Spectral methods provide an elegant and efficient way of numerically solving differential equations of all kinds. For smooth problems, truncation error for spectral methods vanishes exponentially in the infinity norm and $L_2$-norm.…

Numerical Analysis · Computer Science 2019-10-09 Joanna Piotrowska , Jonah M. Miller , Erik Schnetter

Frequency-dependent correlations, such as the spectral function and the dynamical structure factor, help understand condensed matter experiments. Within the density matrix renormalization group (DMRG) framework, an accurate method for…

Strongly Correlated Electrons · Physics 2016-12-21 A. Nocera , G. Alvarez

An efficient way of solving 2D stability problems in fluid mechanics is to use, after discretization of the equations that cast the problem in the form of a generalized eigenvalue problem, the incomplete Arnoldi-Chebyshev method. This…

Computational Physics · Physics 2007-05-23 Lorenzo Valdettaro , Michel Rieutord , Thierry Braconnier , Valerie Fraysse

Particle density fluctuations in the scrape-off layer of magnetically confined plasmas, as measured by gas-puff imaging or Langmuir probes, are modeled as the realization of a stochastic process in which a superposition of pulses with a…

Plasma Physics · Physics 2015-01-07 Ralph Kube , Odd Erik Garcia

Particulate flows have been largely studied under the simplifying assumptions of one-way coupling regime where the disperse phase do not react-back on the carrier fluid. In the context of turbulent flows, many non trivial phenomena such as…

Chaotic Dynamics · Physics 2023-07-19 P. Gualtieri , F. Picano , G. Sardina , C. M. Casciola

B-spline models are a powerful way to represent scientific data sets with a functional approximation. However, these models can suffer from spurious oscillations when the data to be approximated are not uniformly distributed. Model…

Numerical Analysis · Mathematics 2023-01-04 David Lenz , Raine Yeh , Vijay Mahadevan , Iulian Grindeanu , Tom Peterka

On the one hand, Sobolev gradient smoothing can considerably improve the performance of aerodynamic shape optimization and prevent issues with regularity. On the other hand, Sobolev smoothing can also be interpreted as an approximation for…

Optimization and Control · Mathematics 2022-03-22 Thomas Dick , Stephan Schmidt , Nicolas R. Gauger

Adaptive cubic regularization methods have emerged as a credible alternative to linesearch and trust-region for smooth nonconvex optimization, with optimal complexity amongst second-order methods. Here we consider a general/new class of…

Optimization and Control · Mathematics 2018-11-20 Coralia Cartis , Nicholas I. M. Gould , Philippe L. Toint

Filtering and smoothing with a generalised representation of uncertainty is considered. Here, uncertainty is represented using a class of outer measures. It is shown how this representation of uncertainty can be propagated using…

Methodology · Statistics 2018-08-02 Jeremie Houssineau , Adrian N. Bishop

We propose a new smoothing method for obtaining surface densities from discrete particle positions from numerical simulations. This is an essential step for many applications in gravitational lensing. This method is based on the ``scatter''…

Astrophysics · Physics 2011-02-11 Guo-Liang Li , S. Mao , Y. P. Jing , X. Kang , M. Bartelmann

Shape calculus concerns the calculation of directional derivatives of some quantity of interest, typically expressed as an integral. This article introduces a type of shape calculus based on localized dilation of boundary faces through…

Numerical Analysis · Mathematics 2023-05-29 Martin Berggren

Some methods based on simple regularizing geometric element transformations have heuristically been shown to give runtime efficient and quality effective smoothing algorithms for meshes. We describe the mathematical framework and a…

Computational Geometry · Computer Science 2013-07-09 Dimitris Vartziotis , Benjamin Himpel

This paper presents new quadrature rules for functions in a reproducing kernel Hilbert space using nodes drawn by a sampling algorithm known as randomly pivoted Cholesky. The resulting computational procedure compares favorably to previous…

Numerical Analysis · Mathematics 2023-12-08 Ethan N. Epperly , Elvira Moreno