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Related papers: Generalised quasi-linear approximation of the HMRI

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Partial least squares (PLS) is a dimensionality reduction technique used as an alternative to ordinary least squares (OLS) in situations where the data is colinear or high dimensional. Both PLS and OLS provide mean based estimates, which…

Methodology · Statistics 2021-10-18 Alvaro Mendez Civieta , M. Carmen Aguilera-Morillo , Rosa E. Lillo

The Gaussian kernel is one of the most important kernels, applicable to many research fields, including scientific computing and data science. In this paper, we present asymptotic analysis of the Gaussian kernel matrix in high dimension…

Statistics Theory · Mathematics 2026-02-11 Kensuke Aishima

We present a graph-based deep learning framework for predicting the magnetic properties of quasi-one-dimensional Ising spin systems. The lattice geometry is encoded as a graph and processed by a graph neural network (GNN) followed by fully…

Disordered Systems and Neural Networks · Physics 2025-07-24 V. Slavin , O. Kryvchikov , D. Laptev

The effect of massive scalar perturbations on neutral black string in de Rham-Gabadadze-Tolley (dRGT) massive gravity is investigated through the study of the quasi-normal modes~(QNMs). Due to the similarity between the equation of motion…

General Relativity and Quantum Cosmology · Physics 2018-08-15 Supakchai Ponglertsakul , Piyabut Burikham , Lunchakorn Tannukij

Full Waveform Inversion (FWI) reconstructs high-resolution subsurface models via multi-variate optimization but faces challenges with solver selection and data availability. Deep Learning (DL) offers a promising alternative, bridging…

Geophysics · Physics 2025-02-27 Christopher Zerafa

We compare different nonlinear approximations to gravitational clustering in the weakly nonlinear regime, using as a comparative statistic the evolution of non-Gaussianity which can be characterised by a set of numbers $S_p$ describing…

Astrophysics · Physics 2009-10-22 Dipak Munshi , Varun Sahni , Alexei A. Starobinsky

Quantum magnetism in low dimensions has been one of the central areas of theoretical research for many decades now. One of the key reasons for the long standing interest in this field has been the existence of simplified models, which serve…

Strongly Correlated Electrons · Physics 2007-05-23 Swapan K. Pati , S. Ramasesha , Diptiman Sen

For helical isotropic turbulence, an improved two-term helical subgrid-scale (SGS) model is proposed and four types of dynamic methods are given to do large-eddy simulation (LES), which include the standard dynamic procedure, the least…

Fluid Dynamics · Physics 2014-08-13 changping Yu

Linear response (LR) is an important tool in the computational chemist's toolbox. It is therefore no surprise that the emergence of quantum computers has led to a quantum version, quantum LR (qLR). However, the current quantum era of…

The study of the quasinormal modes (QNMs) of the 2+1 dimensional rotating draining bathtub acoustic black hole, the closest analogue found so far to the Kerr black hole, is performed. Both the real and imaginary parts of the quasinormal…

General Relativity and Quantum Cosmology · Physics 2009-11-10 Vitor Cardoso , Jose' P. S. Lemos , Shijun Yoshida

We study the stability of black holes that are solutions of the dilaton gravity derived from string-theoretical models in two and five dimensions against to scalar field perturbations, using the Quasinormal Modes (QNMs) approach. In order…

General Relativity and Quantum Cosmology · Physics 2008-11-26 Ramón Becar , Samuel Lepe , Joel Saavedra

Quasi-normal modes (QNMs) of a black hole (BH) are the eigen modes describing the dissipative oscillation of various fields in that spacetime, which can be intrinsically produced by the linear perturbation theory. With the discovery of the…

General Relativity and Quantum Cosmology · Physics 2022-12-02 Yuqian Zhao , Bing Sun , Zhan-Feng Mai , Zhoujian Cao

Purpose: The clinical feasibility and translation of many advanced quantitative MRI (qMRI) techniques are inhibited by their restriction to 'research mode', due to resource-intensive, offline parameter estimation. This work aimed to achieve…

Fault-tolerant quantum computers promise the simulation of complex quantum systems beyond the reach of classical computation. In contrast, current noisy intermediate-scale quantum (NISQ) devices are constrained by hardware noise.…

Both scalar and Dirac quasinormal modes in Garfinkle-Horowitz-Strominger black hole spacetime are studied by using the WKB approximation and the P\"{o}schl-Teller approximation. For scalar field, we find that the QNMs with higher dilatons…

General Relativity and Quantum Cosmology · Physics 2008-11-26 Fu-Wen Shu , You-Gen Shen

In this paper we present a computational procedure that utilizes real-space grids to obtain high precision approximations of electrostatically confined few-electron states such as those that arise in gated semiconductor quantum dots. We use…

Mesoscale and Nanoscale Physics · Physics 2023-01-27 Christopher R. Anderson , Mark F. Gyure , Sam Quinn , Andrew Pan , Richard S. Ross , Andrey A. Kiselev

In this work, we construct a perturbative black hole (BH) solution motivated by renormalization group (RG) improvement and investigate the quasinormal modes (QNMs) of the BH under scalar field perturbations in both Schwarzschild-de Sitter…

General Relativity and Quantum Cosmology · Physics 2026-03-16 Rupam Jyoti Borah , Umananda Dev Goswami

We investigate quasinormal modes (QNMs) of scalar, electromagnetic, and axial gravitational perturbations in slowly rotating Kalb-Ramond (KR) black holes, where an antisymmetric tensor field induces spontaneous Lorentz symmetry breaking.…

General Relativity and Quantum Cosmology · Physics 2025-11-26 Weike Deng , Wentao Liu , Kui Xiao , Jiliang Jing

We studied the use of deep neural networks (DNNs) in the numerical solution of the oscillatory Fredholm integral equation of the second kind. It is known that the solution of the equation exhibits certain oscillatory behaviors due to the…

Numerical Analysis · Mathematics 2024-01-17 Jie Jiang , Yuesheng Xu

We consider the variable selection problem of generalized linear models (GLMs). Stability selection (SS) is a promising method proposed for solving this problem. Although SS provides practical variable selection criteria, it is…

Machine Learning · Statistics 2025-08-06 Takashi Takahashi , Yoshiyuki Kabashima