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Related papers: Curvature Correction in the Strutinsky's Method

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Using a perturbation technique, we derive a new approximate filtering and smoothing methodology generalizing along different directions several existing approaches to robust filtering based on the score and the Hessian matrix of the…

Methodology · Statistics 2023-06-06 Giuseppe Buccheri , Giacomo Bormetti , Fulvio Corsi , Fabrizio Lillo

The moment of inertia for nuclear collective rotations was derived within the semiclassical approach based on the cranking model and the Strutinsky shell-correction method by using the non-perturbative periodic-orbit theory in the phase…

Nuclear Theory · Physics 2014-11-25 D. V. Gorpinchenko , A. G. Magner , J. Bartel , J. P. Blocki

We analyze the ground state energy and spin of quantum dots obtained from spin density functional theory (SDFT) calculations. First, we introduce a Strutinsky-type approximation, in which quantum interference is treated as a correction to a…

Mesoscale and Nanoscale Physics · Physics 2007-05-23 Denis Ullmo , Hong Jiang , Weitao Yang , Harold U. Baranger

A quantum-mechanical calculation of the single-particle level (s.p.l.) density $g(\epsilon)$ is carried on by using the connection with the single-particle Green's function. The relation between the imaginary part of Green's function and…

Nuclear Theory · Physics 2007-05-23 I. Stetcu

We prove a suite of asymptotically sharp quadratic curvature pinching estimates for mean curvature flow in the sphere which generalize Simons' rigidity theorem for minimal hypersurfaces. We then obtain derivative estimates for the second…

Differential Geometry · Mathematics 2020-09-03 Mat Langford , Huy The Nguyen

We suggest an approach to detect the conformation of single molecule by using the photon counting statistics. The generalized Smoluchoswki equation is employed to describe the dynamical process of conformational change of single molecule.…

Chemical Physics · Physics 2014-11-13 Yonggang Peng , Zhen-Dong Sun , Chuanlu Yang , Yujun Zheng

We propose novel smooth approximations to the classical rounding function, suitable for differentiable optimization and machine learning applications. Our constructions are based on two approaches: (1) localized sigmoid window functions…

Machine Learning · Computer Science 2025-04-29 Stanislav Semenov

In state space models, smoothing refers to the task of estimating a latent stochastic process given noisy measurements related to the process. We propose an unbiased estimator of smoothing expectations. The lack-of-bias property has…

Methodology · Statistics 2018-09-07 Pierre E. Jacob , Fredrik Lindsten , Thomas B. Schön

The method proposed by T. I. Zelenjak is applied to the mean curvature flow in the plane. A new type of monotonicity formula for star-shaped curves is obtained.

Analysis of PDEs · Mathematics 2022-07-20 Hayk Mikayelyan

Lagrangian smoothed particle hydrodynamics (SPH) is a well-established approach to model fluids in astrophysical problems, thanks to its geometric flexibility and ability to automatically adjust the spatial resolution to the clumping of…

Cosmology and Nongalactic Astrophysics · Physics 2015-05-14 S. Hess , V. Springel

We introduce an estimator for the curvature of curves and surfaces by using finite sample points drawn from sampling a probability distribution that has support on the curve or surface. First we give an algorithm for estimation of the…

Differential Geometry · Mathematics 2025-07-03 R. Mirzaie

Curvature has received increased attention as an important alternative to length based regularization in computer vision. In contrast to length, it preserves elongated structures and fine details. Existing approaches are either inefficient,…

Computer Vision and Pattern Recognition · Computer Science 2014-04-17 Claudia Nieuwenhuis , Eno Toeppe , Lena Gorelick , Olga Veksler , Yuri Boykov

Smoothed particle hydrodynamics is a particle-based, fully Lagrangian, method for fluid-flow simulations. In this work, fundamental concepts of the method are first briefly recalled. Then, we present a thorough comparison of three different…

Fluid Dynamics · Physics 2012-08-22 Kamil Szewc , Jacek Pozorski , Jean-Pierre Minier

An error control technique aimed to assess the quality of smoothed finite element approximations is presented in this paper. Finite element techniques based on strain smoothing appeared in 2007 were shown to provide significant advantages…

In microgravity, a partially filled cylindrical tank is generally bounded by a curved equilibrium meniscus rather than by an almost flat free surface. This modifies both the bulk liquid inertia and the capillary restoring force, so…

Fluid Dynamics · Physics 2026-05-04 Gianni Cassoni

In this paper the problem of consistency of smoothed particle hydrodynamics (SPH) is solved. A novel error analysis is developed in $n$-dimensional space using the Poisson summation formula, which enables the treatment of the kernel and…

Computational Physics · Physics 2019-04-09 Leonardo Di G. Sigalotti , Otto Rendón , Jaime Klapp , Carlos A. Vargas , Kilver Campos

Singular source terms expressed as weighted summations of Dirac-delta functions are regularized through approximation theory with convolution operators. We consider the numerical solution of scalar and one-dimensional hyperbolic…

Numerical Analysis · Mathematics 2016-11-18 Jean-Piero Suarez , Gustaaf Jacobs

We introduce adaptive particle refinement for compressible smoothed particle hydrodynamics (SPH). SPH calculations have the natural advantage that resolution follows mass, but this is not always optimal. Our implementation allows the user…

Instrumentation and Methods for Astrophysics · Physics 2024-09-19 Rebecca Nealon , Daniel Price

For the purpose of uncertainty quantification with collocation, a method is proposed for generating families of one-dimensional nested quadrature rules with positive weights and symmetric nodes. This is achieved through a reduction…

Numerical Analysis · Mathematics 2020-04-20 L. M. M. van den Bos , B. Koren , R. P. Dwight

Normalizing flows are a promising tool for modeling probability distributions in physical systems. While state-of-the-art flows accurately approximate distributions and energies, applications in physics additionally require smooth energies…

Machine Learning · Statistics 2021-12-01 Jonas Köhler , Andreas Krämer , Frank Noé