Statistical Analysis and Information Theory of Screened Kratzer-Hellmann Potential Model

• URL: http://arxiv.org/abs/2001.08429v1
• Date: Thu, 23 Jan 2020 10:04:34 GMT
• Title: Statistical Analysis and Information Theory of Screened Kratzer-Hellmann Potential Model
• Authors: Gabriel T. Osobonye, Uduakobong S. Okorie, Precious O. Amadi, Akpan N. Ikot
• Abstract summary: The radial Schrodinger equation for a newly proposed screened Kratzer-Hellmann potential model was studied. Results were employed to evaluate the rotational-vibrational partition function and other thermodynamic properties for the screened Kratzer-Hellmann potential.
• Score: 0.0
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: In this research, the radial Schrodinger equation for a newly proposed screened Kratzer-Hellmann potential model was studied via the conventional Nikiforov-Uvarov method. The approximate bound state solution of the Schrodinger equation was obtained using the Greene-Aldrich approximation, in addition to the normalized eigenfunction for the new potential model both analytically and numerically. These results were employed to evaluate the rotational-vibrational partition function and other thermodynamic properties for the screened Kratzer-Hellmann potential. We have discussed the results obtained graphically. Also, the normalized eigenfunction has been used to calculate some information-theoretic measures including Shannon entropy and Fisher information for low lying states in both position and momentum spaces numerically. We observed that the Shannon entropy results agreed with the Bialynicki-Birula and Mycielski inequality, while the Fisher information results obtained agreed with the Stam, Crammer-Rao inequality. From our results, we observed alternating increasing and decreasing localization across the screening parameter in the both eigenstates.

Related papers

• Hellinger-Kantorovich Gradient Flows: Global Exponential Decay of Entropy Functionals [52.154685604660465]
  We investigate a family of gradient flows of positive and probability measures, focusing on the Hellinger-Kantorovich (HK) geometry. A central contribution is a complete characterization of global exponential decay behaviors of entropy functionals under Otto-Wasserstein and Hellinger-type gradient flows.
  arXiv  Detail & Related papers  (2025-01-28T16:17:09Z)
• von Mises Quasi-Processes for Bayesian Circular Regression [57.88921637944379]
  We explore a family of expressive and interpretable distributions over circle-valued random functions. The resulting probability model has connections with continuous spin models in statistical physics. For posterior inference, we introduce a new Stratonovich-like augmentation that lends itself to fast Markov Chain Monte Carlo sampling.
  arXiv  Detail & Related papers  (2024-06-19T01:57:21Z)
• Robust Gaussian Process Regression with Huber Likelihood [2.7184224088243365]
  We propose a robust process model in the Gaussian process framework with the likelihood of observed data expressed as the Huber probability distribution. The proposed model employs weights based on projection statistics to scale residuals and bound the influence of vertical outliers and bad leverage points on the latent functions estimates.
  arXiv  Detail & Related papers  (2023-01-19T02:59:33Z)
• Tomography in Loop Quantum Cosmology [0.0]
  We analyze the tomographic representation for the Friedmann-Robertson-Walker (FRW) model within the Loop Quantum Cosmology framework. We focus on the Wigner quasi-probability distributions associated with Gaussian and Schr"odinger cat states.
  arXiv  Detail & Related papers  (2021-04-20T02:31:52Z)
• Nishimori meets Bethe: a spectral method for node classification in sparse weighted graphs [53.13327158427103]
  This article unveils a new relation between the Nishimori temperature parametrizing a distribution P and the Bethe free energy on random Erdos-Renyi graphs with edge weights distributed according to P. A numerical method is proposed to accurately estimate the Nishimori temperature from the eigenvalues of the Bethe Hessian matrix of the weighted graph.
  arXiv  Detail & Related papers  (2021-03-05T09:45:56Z)
• Leveraging Global Parameters for Flow-based Neural Posterior Estimation [90.21090932619695]
  Inferring the parameters of a model based on experimental observations is central to the scientific method. A particularly challenging setting is when the model is strongly indeterminate, i.e., when distinct sets of parameters yield identical observations. We present a method for cracking such indeterminacy by exploiting additional information conveyed by an auxiliary set of observations sharing global parameters.
  arXiv  Detail & Related papers  (2021-02-12T12:23:13Z)
• Approximate solutions of the Schrodinger equation with Hulthen-Hellmann Potentials for a Quarkonium system [0.0]
  Hulth'en plus Hellmann potentials are adopted as the quark-antiquark interaction potential. Four special cases were considered when some of the potential parameters were set to zero.
  arXiv  Detail & Related papers  (2021-01-02T00:02:41Z)
• Analytical solutions of the Schr\"odinger equation with Kratzer-screened Coulomb potential to the Quarkonium systems [0.0]
  We obtain the Schr"odinger equation solutions for the Kratzer potential plus screened Coulomb potential model. The energy eigenvalues is obtained in non-relativistic regime and the corresponding unnormalized eigenfunction.
  arXiv  Detail & Related papers  (2021-01-01T23:55:23Z)
• Eigensolutions of the N-dimensional Schr\"odinger equation interacting with Varshni-Hulth\'en potential model [0.0]
  Solution of the N-dimensional Schr"odinger equation for the newly proposed Varshni-Hulth'en potential is presented. numerical energy eigenvalues and the corresponding normalized eigenfunctions are obtained in terms of Jacobis.
  arXiv  Detail & Related papers  (2020-12-26T22:54:13Z)
• SLEIPNIR: Deterministic and Provably Accurate Feature Expansion for Gaussian Process Regression with Derivatives [86.01677297601624]
  We propose a novel approach for scaling GP regression with derivatives based on quadrature Fourier features. We prove deterministic, non-asymptotic and exponentially fast decaying error bounds which apply for both the approximated kernel as well as the approximated posterior.
  arXiv  Detail & Related papers  (2020-03-05T14:33:20Z)
• Fast approximations in the homogeneous Ising model for use in scene analysis [61.0951285821105]
  We provide accurate approximations that make it possible to numerically calculate quantities needed in inference. We show that our approximation formulae are scalable and unfazed by the size of the Markov Random Field. The practical import of our approximation formulae is illustrated in performing Bayesian inference in a functional Magnetic Resonance Imaging activation detection experiment, and also in likelihood ratio testing for anisotropy in the spatial patterns of yearly increases in pistachio tree yields.
  arXiv  Detail & Related papers  (2017-12-06T14:24:34Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.