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A space-time interface-fitted approximation of an inverse source problem for the advection-diffusion equation with moving subdomains is investigated. The problem is reformulated as an optimization problem using Tikhonov regularization. A…

Numerical Analysis · Mathematics 2025-02-11 Thi Thanh Mai Ta , Quang Huy Nguyen , Dinh Nho Hào

An empirical formula for a Shu distribution function that reproduces a thin disc with exponential surface density to good accuracy is presented. The formula has two free parameters that specify the functional form of the velocity…

Astrophysics of Galaxies · Physics 2015-06-16 Sanjib Sharma , Joss Bland-Hawthorn

This paper deals with an inertial proximal algorithm that contains a Tikhonov regularization term, in connection to the minimization problem of a convex lower semicontinuous function $f$. We show that for appropriate Tikhonov regularization…

Optimization and Control · Mathematics 2024-01-09 Szilárd Csaba László

Processing of Diffusion MRI data obtained from High Angular Resolution measurements consists of a series of steps, starting with the estimation of an orientation distribution function (ODF), which is then used as input for e.g. tractography…

Numerical Analysis · Mathematics 2015-12-23 T. Hohage , C. Rügge

In this paper, we apply a new kind of smoothness concept, i.e. H\"older stability estimates for the determination of convergence rates of Tikhonov regularization for linear and non-linear inverse problems in Hilbert spaces. For linear…

Numerical Analysis · Mathematics 2020-11-05 Gaurav Mittal , Ankik Kumar Giri

We investigate the effect that the usually large errors associated with ground-based proper motion (PM) components have on the determination of a star cluster's velocity dispersion (\sv). Rather than histograms, we work with PM distribution…

Astrophysics of Galaxies · Physics 2015-05-27 Charles Bonatto , Eduardo Bica

This paper deals with the rapid stabilization of a degenerate parabolic equation with a right Dirich-let control. Our strategy consists in applying a backstepping strategy, which seeks to find an invertible transformation mapping the…

Analysis of PDEs · Mathematics 2020-10-13 Ludovick Gagnon , Pierre Lissy , Swann Marx

We analyse a Monte Carlo particle method for the simulation of the calibrated Heston-type local stochastic volatility (H-LSV) model. The common application of a kernel estimator for a conditional expectation in the calibration condition…

Computational Finance · Quantitative Finance 2025-04-22 Christoph Reisinger , Maria Olympia Tsianni

We introduce and investigate the asymptotic behaviour of the trajectories of a second order dynamical system with Tikhonov regularization for solving a monotone equation with single valued, monotone and continuous operator acting on a real…

Optimization and Control · Mathematics 2024-11-27 Ernö Robert Csetnek , Szilárd Csaba László

We present a finite element analysis of electrical impedance tomography for reconstructing the conductivity distribution from electrode voltage measurements by means of Tikhonov regularization. Two popular choices of the penalty term, i.e.,…

Numerical Analysis · Mathematics 2015-06-18 Matthias Gehre , Bangti Jin , Xiliang Lu

Regularized kernel methods such as support vector machines (SVM) and support vector regression (SVR) constitute a broad and flexible class of methods which are theoretically well investigated and commonly used in nonparametric…

Methodology · Statistics 2013-05-07 Robert Hable

Tikhonov regularization is a popular approach to obtain a meaningful solution for ill-conditioned linear least squares problems. A relatively simple way of choosing a good regularization parameter is given by Morozov's discrepancy…

Numerical Analysis · Mathematics 2020-06-24 Jeffrey Cornelis , Nick Schenkels , Wim Vanroose

Finding a good regularization parameter for Tikhonov regularization problems is a though yet often asked question. One approach is to use leave-one-out cross-validation scores to indicate the goodness of fit. This utilizes only the noisy…

Numerical Analysis · Mathematics 2021-05-31 Felix Bartel , Ralf Hielscher , Daniel Potts

In a separable Hilbert space, we study the minimization problem of a convex smooth function with Lipschitz continuous gradient whose evaluations are corrupted by random noise. To this end, we associate a stochastic inertial system that…

Optimization and Control · Mathematics 2025-12-18 Chiara Schindler

We study recursive regularized learning algorithms in the reproducing kernel Hilbert space (RKHS) with non-stationary online data streams. We introduce the concept of random Tikhonov regularization path and decompose the tracking error of…

Machine Learning · Computer Science 2025-10-24 Xiwei Zhang , Yan Chen , Tao Li

We present a new approach for quantifying the abundance of galaxy clusters and constraining cosmological parameters using dynamical measurements. In the standard method, galaxy line-of-sight (LOS) velocities, $v$, or velocity dispersions…

Cosmology and Nongalactic Astrophysics · Physics 2017-01-25 M. Ntampaka , H. Trac , J. Cisewski , L. C. Price

Numerical solutions of stationary diffusion equations on the unit sphere with isotropic lognormal diffusion coefficients are considered. H\"older regularity in $L^p$ sense for isotropic Gaussian random fields is obtained and related to the…

Probability · Mathematics 2023-12-06 Lukas Herrmann , Annika Lang , Christoph Schwab

The stellar velocity dispersion ($\sigma$) of massive elliptical galaxies is a key ingredient in breaking the mass-sheet degeneracy and obtaining precise and accurate cosmography from gravitational time delays. The relative uncertainty on…

The power-law disks are a family of infinitesimally thin, axisymmetric stellar disks of infinite extent. The rotation curve can be rising, falling or flat. The self-consistent power-law disks are scale-free, so that all physical quantities…

Astrophysics · Physics 2017-01-04 N. W. Evans , J. C. A. Read

The problem of numerical differentiation can be thought of as an inverse problem by considering it as solving a Volterra equation. It is well known that such inverse integral problems are ill-posed and one requires regularization methods to…

Numerical Analysis · Mathematics 2020-04-15 Abinash Nayak