English
Related papers

Related papers: Linear response strength functions with iterative …

200 papers

Iterative deblurring, notably the Richardson-Lucy algorithm with and without regularization, is analyzed in the context of nuclear and high-energy physics applications. In these applications, probability distributions may be discretized…

Numerical Analysis · Mathematics 2025-11-05 Sinethemba Neliswa Mamba , Pawel Danielewicz

We propose a novel method for reconstructing Laurent expansion of rational functions using $p$-adic numbers. By evaluating the rational functions in $p$-adic fields rather than finite fields, it is possible to probe the expansion…

High Energy Physics - Theory · Physics 2025-11-10 Tianya Xia , Li Lin Yang

The Arnoldi process provides an efficient framework for approximating functions of a matrix applied to a vector, i.e., of the form $f(M)\bm{b}$, by repeated matrix-vector multiplications. In this paper, we derive error estimates for…

Numerical Analysis · Mathematics 2026-01-27 James H. Adler , Xiaozhe Hu , Wenxiao Pan , Zhongqin Xue

Single-particle resonance parameters and wave functions in spherical and deformed nuclei are determined through analytic continuation in the potential strength. In this method, the analyticity of the eigenvalues and eigenfunctions of the…

Nuclear Theory · Physics 2009-11-06 G. Cattapan , E. Maglione

This paper proposes a novel non-iterative method to solve power system differential algebraic equations (DAEs) using the differential transformation, a mathematical tool that can obtain power series coefficients by transformation rules…

Systems and Control · Electrical Eng. & Systems 2019-11-19 Yang Liu , Kai Sun

Radiative strength functions (RSFs) model the bulk electromagnetic response of highly-excited nuclei and are critical inputs for statistical reaction codes. In this paper, we present a definition of the RSF that is consistent with…

Nuclear Theory · Physics 2026-04-30 Oliver C. Gorton , Konstantinos Kravvaris , Jutta E. Escher , Calvin W. Johnson

A method is proposed for estimating the potential function of a non-parametric estimator for stationary and isotropic pairwise interaction point process. The relation between a pair potential and the corresponding Papangelou conditional…

Probability · Mathematics 2015-06-08 Nadia Morsli

Two quadrature-based algorithms for computing the matrix fractional power $A^\alpha$ are presented in this paper. These algorithms are based on the double exponential (DE) formula, which is well-known for its effectiveness in computing…

Numerical Analysis · Mathematics 2021-09-14 Fuminori Tatsuoka , Tomohiro Sogabe , Yuto Miyatake , Tomoya Kemmochi , Shao-Liang Zhang

A concise method is presented for the non-perturbative computation of the counterterms renormalising 2PI-actions. The procedure is presented for a real scalar field up to lambda^2 order in the skeleton truncation of Gamma_2PI with respect…

High Energy Physics - Phenomenology · Physics 2009-11-13 A. Patkos , Zs. Szep

We obtain the strong asymptotics of polynomials $p_n(\lambda)$, $\lambda\in\mathbb{C}$, orthogonal with respect to measures in the complex plane of the form $$ e^{-N(|\lambda|^{2s}-t\lambda^s-\overline{t\lambda}^s)}dA(\lambda), $$ where $s$…

Mathematical Physics · Physics 2016-07-05 Ferenc Balogh , Tamara Grava , Dario Merzi

A LMTO implementation of Aversa and Sipe's length-gauge formalism for calculating the full frequency dependent second-harmonic generation in the independent particle approximation is presented. It is applied to GaAs, GaP, 3C-SiC, c-BN and…

Materials Science · Physics 2008-02-03 Sergey N. Rashkeev , Walter R. L. Lambrecht , Benjamin Segall

In this paper, new digital predistortion (DPD) solutions for power amplifier (PA) linearization are proposed, with particular emphasis on reduced processing complexity in future 5G and beyond wideband radio systems. The first proposed…

Signal Processing · Electrical Eng. & Systems 2020-07-03 Pablo Pascual Campo , Alberto Brihuega , Lauri Anttila , Matias Turunen , Dani Korpi , Markus Allén , Mikko Valkama

Reinforcement Learning (RL) has achieved remarkable success in sequential decision tasks. However, recent studies have revealed the vulnerability of RL policies to different perturbations, raising concerns about their effectiveness and…

Machine Learning · Computer Science 2025-07-08 Buqing Nie , Yangqing Fu , Jingtian Ji , Yue Gao

Many modern datasets don't fit neatly into $n \times p$ matrices, but most techniques for measuring statistical stability expect rectangular data. We study methods for stability assessment on non-rectangular data, using statistical learning…

Computation · Statistics 2021-02-23 Kris Sankaran

We study structure and direct decay of the Giant Monopole Resonance (GMR) at the RPA level using the Time-Dependent Energy Density Functional method in the linear response regime in a few doubly-magic nuclei. A proper treatment of the…

Nuclear Theory · Physics 2013-06-25 B. Avez , C. Simenel

This paper presents a novel framework for high-dimensional nonlinear quantum computation that exploits tensor products of amplified vector and matrix encodings to efficiently evaluate multivariate polynomials. The approach enables the…

Quantum Physics · Physics 2025-10-01 Matthias Deiml , Daniel Peterseim

Many problems in physics, chemistry and other fields are perturbative in nature, i.e. differ only slightly from related problems with known solutions. Prominent among these is the eigenvalue perturbation problem, wherein one seeks the…

Mathematical Physics · Physics 2020-03-12 Maseim Kenmoe , Matteo Smerlak , Anton Zadorin

A dynamical model based on effective Lagrangians is proposed to describe the bremsstrahlung reaction $ \pi N \to \pi N \gamma$ at low energies. The $\Delta(1232)$ degrees of freedom are incorporated in a way consistent with both,…

Nuclear Theory · Physics 2016-09-08 A. Mariano

We identify three common cases that lead to overestimation of adversarial accuracy against bounded first-order attack methods, which is popularly used as a proxy for adversarial robustness in empirical studies. For each case, we propose…

Machine Learning · Computer Science 2020-06-03 Kyungmi Lee , Anantha P. Chandrakasan

This paper discusses the solution of nonlinear integral equations with noisy integral kernels as they appear in nonparametric instrumental regression. We propose a regularized Newton-type iteration and establish convergence and convergence…

Numerical Analysis · Mathematics 2015-04-01 Fabian Dunker , Jean-Pierre Florens , Thorsten Hohage , Jan Johannes , Enno Mammen
‹ Prev 1 8 9 10 Next ›