English
Related papers

Related papers: Connection between the "Strutinsky level density" …

200 papers

Mass calculations carried out by Strutinsky's shell correction method are based on the notion of smooth single particle level density. The smoothing procedure is always performed using curvature correction. In the presence of curvature…

Nuclear Theory · Physics 2014-11-20 P. Salamon , A. T. Kruppa

Strutinsky's method is reviewed through a new understanding. This method depends on two free parameters: The smoothing parameter and the order of the curvature correction. It turns out that this method is nothing but a compromise between…

Nuclear Theory · Physics 2019-09-24 B. Mohammed-Azizi

The main purpose of this paper is to rigorously establish the Strutinsky method from the least squares principle. Thus, it is the mathematical basis of this method (aspect often neglected) which is revisited in an extensive way. Some…

Nuclear Theory · Physics 2021-04-01 B. Mohammed-Azizi

Reviewing the semiclassical theory for the parametric level density fluctuations, we show that for large parametric changes the density correlation function, after rescaling, becomes universal and coincides with the leading asymptotic term…

Nuclear level density is calculated with the combinatorial method based on the relativistic density functional theory including pairing correlations. The Strutinsky method is adopted to smooth the total state density in order to refine the…

Nuclear Theory · Physics 2024-01-18 Xiao-Fei Jiang , Xin-Hui Wu , Peng-Wei Zhao , Jie Meng

In this paper, we investigate the convergence in probability of a stochastic symplectic scheme for stochastic nonlinear Schr\"{o}dinger equation with quadratic potential and an additive noise. Theoretical analysis shows that our symplectic…

Numerical Analysis · Mathematics 2018-03-06 Jialin Hong , Lijun Miao , Liying Zhang

Level density $\rho(E,A)$ is derived for a one-component nucleon system with a given energy $E$ and particle number $A$ within the mean-field semiclassical periodic-orbit theory beyond the saddle-point method of the Fermi gas model. We…

Nuclear Theory · Physics 2021-10-20 A. G. Magner , A. I. Sanzhur , S. N. Fedotkin , A. I. Levon , S. Shlomo

In this paper we present a rigorous asymptotic analysis for stochastic systems with two fast relaxation times. The mathematical model analyzed in this paper consists of a Langevin equation for the particle motion with time-dependent force…

Mathematical Physics · Physics 2007-05-23 G. A. Pavliotis , A. M. Stuart

Level density $\rho$ is derived for a finite system with strongly interacting nucleons at a given energy E, neutron N and proton Z particle numbers, projection of the angular momentum M, and other integrals of motion, within the…

Nuclear Theory · Physics 2023-08-22 A. G. Magner , A. I. Sanzhur , S. N. Fedotkin , A. I. Levon , U. V. Grygoriev , S. Shlomo

The Woods-Saxon-Strutinsky method (the microscopic-macroscopic method) combined with Kruppa's prescription for positive energy levels, which is necessary to treat neutron rich nuclei, is studied to clarify the reason for its success and to…

Nuclear Theory · Physics 2014-11-21 Naoki Tajima , Yoshifumi R. Shimizu , Satoshi Takahara

In this paper, we consider a semi-linear stochastic strongly damped wave equation driven by additive Gaussian noise. Following a semigroup framework, we establish existence, uniqueness and space-time regularity of a mild solution to such…

Numerical Analysis · Mathematics 2020-08-10 Ruisheng Qi , Xiaojie Wang

The empirical measure of an interacting particle system is a purely atomic random probability measure. In the limit as the number of particles grows to infinity, we show for McKean-Vlasov systems with common noise that this measure becomes…

Probability · Mathematics 2025-09-01 Robert Alexander Crowell

Statistical level density $\rho(E,A)$ is derived for nucleonic system with a given energy $E$, particle number $A$ and other integrals of motion in the micro-macroscopic approximation beyond the standard saddle-point method of the Fermi gas…

Nuclear Theory · Physics 2022-03-08 A. G. Magner , A. I. Sanzhur , S. N. Fedotkin , A. I. Levon , S. Shlomo

This paper examines the asymptotic convergence properties of Lipschitz interpolation methods within the context of bounded stochastic noise. In the first part of the paper, we establish probabilistic consistency guarantees of the classical…

Optimization and Control · Mathematics 2023-10-12 Julien Walden Huang , Stephen Roberts , Jan-Peter Calliess

We consider an agent trying to bring a system to an acceptable state by repeated probabilistic action. Several recent works on algorithmizations of the Lovasz Local Lemma (LLL) can be seen as establishing sufficient conditions for the agent…

Discrete Mathematics · Computer Science 2016-11-29 Dimitris Achlioptas , Fotis Iliopoulos , Nikos Vlassis

In the nonlinear diffusion framework, stochastic processes of McKean-Vlasov type play an important role. In some cases they correspond to processes attracted by their own probability distribution: the so-called self-stabilizing processes.…

Probability · Mathematics 2014-09-04 Samuel Herrmann , Julian Tugaut

We consider the stochastic nonlinear Schroedinger equation driven by a multiplicative noise in a semiclassical regime, where the Plank constant is small. In this regime, the solution of the equation exhibits high-frequency oscillations. We…

Numerical Analysis · Mathematics 2024-08-20 Lihai Ji , Zhihui Liu

Stochastic wave equations appear in several models for evolutionary processes subject to random forces, such as the motion of a strand of DNA in a liquid or heat flow around a ring. Semilinear stochastic wave equations can typically not be…

Probability · Mathematics 2021-11-09 Ladislas Jacobe de Naurois , Arnulf Jentzen , Timo Welti

We analyze a semi-discrete splitting method for conservation laws driven by a semilinear noise term. Making use of fractional $BV$ estimates, we show that the splitting method produces a compact sequence of approximate solutions converging…

Analysis of PDEs · Mathematics 2016-08-23 Erlend B. Storrøsten , Kenneth H. Karlsen

We present for the first time an asymptotic convergence analysis of two time-scale stochastic approximation driven by "controlled" Markov noise. In particular, the faster and slower recursions have non-additive controlled Markov noise…

Machine Learning · Computer Science 2020-12-03 Prasenjit Karmakar
‹ Prev 1 2 3 10 Next ›