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A Gaussian wave function is used for detailed study of mass spectra of the $B$ and $B_S$ mesons using a Cornell potential incorporated with a $\mathcal{O}(1/m)$ correction in the potential energy term and expansion of the kinetic energy…

High Energy Physics - Phenomenology · Physics 2017-08-17 Virendrasinh Kher , Nayneshkumar Devlani , Ajay Kumar Rai

In the framework of potential models for heavy quarkonium, we compute the mass spectrum of the bottom-charmed $B_{c}$ meson system and spin-dependent splittings from the Schr\"{o}dinger equation using the shifted-large-N expansion…

High Energy Physics - Phenomenology · Physics 2014-11-17 Sameer M. Ikhdair , Ramazan Sever

Bayesian methods for graphical log-linear marginal models have not been developed in the same extent as traditional frequentist approaches. In this work, we introduce a novel Bayesian approach for quantitative learning for such models.…

Methodology · Statistics 2018-07-04 Ioannis Ntzoufras , Claudia Tarantola , Monia Lupparelli

We predict the masses of the lowlying $B_c$ mesons with $J^P = 0^-,\,1^-,\,0^+,\,1^+,\,2^+$, using a flavor dependent interaction pattern which gives an unified successful description of the light, heavy-light and heavy mesons and is also…

High Energy Physics - Phenomenology · Physics 2020-03-11 Muyang Chen , Lei Chang , Yu-xin Liu

We present a study of various $B_{s}$ meson decays, including hadronic and semileptonic final states with different spins and diagram topologies. The covariant confined quark model is employed to describe hadronic effects, and our analysis…

High Energy Physics - Phenomenology · Physics 2025-12-18 Stanislav Dubnička , Anna Zuzana Dubničková , Mikhail A. Ivanov , Andrej Liptaj

Prominent features of simulated moving bed (SMB) chromatography processes in the downstream processing is based on the determination of operating conditions. However, effects of different types of uncertainties have to be studied and…

Computational Engineering, Finance, and Science · Computer Science 2021-07-16 Qiao-Le He , Liming Zhao

We study the most recently observed excited $B_{c}$ states with the Dyson-Schwinger equation and the Bethe-Salpeter equation approach of continuum QCD. The obtained $M_{B^+_{c}(2S)}=6.813(16)\text{GeV}$,…

Nuclear Theory · Physics 2020-10-21 Lei Chang , Muyang Chen , Yu-xin Liu

We give a review and present a comprehensive calculations for the leptonic constant B_{c} of the low-lying pseudoscalar and vector states of B_{c}-meson in the framework of static and QCD-motivated nonrelativistic potential models taking…

High Energy Physics - Phenomenology · Physics 2007-05-23 Sameer M. Ikhdair

We measure the masses, decay widths and relative production rate of orbitally excited B mesons using 1.25 million hadronic Z decays recorded by the L3 detector. B-meson candidates are inclusively reconstructed and combined with charged…

High Energy Physics - Experiment · Physics 2012-08-27 L3 Collaboration

We present bound state masses of the self-conjugate and non-self-conjugate mesons in the context of the Schr\"{o}dinger equation taking into account the relativistic kinematics and the quark spins. We apply the usual interaction by adding…

High Energy Physics - Phenomenology · Physics 2011-03-23 Sameer M. Ikhdair , Ramazan Sever

The low-lying excited states of $^{10}$Be and $^{12}$Be are investigated within a no-core Monte Carlo Shell Model (MCSM) framework employing a realistic potential obtained via the Unitary Correlation Operator Method. The excitation energies…

Nuclear Theory · Physics 2012-11-07 Lang Liu , Takaharu Otsuka , Noritaka Shimizu , Yutaka Utsuno , Robert Roth

We present a scalable approach to performing approximate fully Bayesian inference in generic state space models. The proposed method is an alternative to particle MCMC that provides fully Bayesian inference of both the dynamic latent states…

Machine Learning · Statistics 2019-02-13 Marcel Hirt , Petros Dellaportas

Presented in this paper is a Markov chain Monte Carlo (MCMC) routine for conducting coherent parameter estimation for interferometric gravitational wave observations of an inspiral of binary compact objects using data from multiple…

General Relativity and Quantum Cosmology · Physics 2008-11-26 Christian Röver , Renate Meyer , Nelson Christensen

In this study, a non-relativistic potential model is used to calculate the mass spectrum and decay properties of low lying charmonium states. A stochastic framework is proposed to extract the possible analytical form of the confinement part…

High Energy Physics - Phenomenology · Physics 2026-05-25 Ahmet Bingul , Altug Ozpineci

A novel approach of accurately reconstructing storage ring's linear optics from turn-by-turn (TbT) data containing measurement error is introduced. This approach adopts a Bayesian inference based on the Markov Chain Monte-Carlo (MCMC)…

Accelerator Physics · Physics 2019-07-01 Yue Hao , Yongjun Li , Michael Balcewicz , Leo Neufcourt , Weixing Cheng

We study the computational complexity of Markov chain Monte Carlo (MCMC) methods for high-dimensional Bayesian linear regression under sparsity constraints. We first show that a Bayesian approach can achieve variable-selection consistency…

Statistics Theory · Mathematics 2015-06-01 Yun Yang , Martin J. Wainwright , Michael I. Jordan

We give a review and present a comprehensive calculation for the leptonic constant B_{c} of the low-lying pseudoscalar and vector states of B_{c}-meson in the framework of static and QCD-motivated nonrelativistic potential models taking…

High Energy Physics - Phenomenology · Physics 2008-11-26 Sameer M. Ikhdair , Ramazan Sever

We calculate the $c\bar{b}$ mass spectrum, the splitting values and some other properties in the framework of the semi-relativistic equation by applying the shifted large-N expansion technique. We use seven different central potentials…

High Energy Physics - Phenomenology · Physics 2011-03-23 Sameer M. Ikhdair , Ramazan Sever

Bayesian max-margin models have shown superiority in various practical applications, such as text categorization, collaborative prediction, social network link prediction and crowdsourcing, and they conjoin the flexibility of Bayesian…

Machine Learning · Statistics 2016-10-19 Wenbo Hu , Jun Zhu , Bo Zhang

The framework of phenomenological quark-antiquark potential (Coulomb plus linear confinement) model with the Gaussian wave function is used for detailed study of masses of the ground, orbitally and radially excited states of heavy-light…

High Energy Physics - Phenomenology · Physics 2017-10-04 Virendrasinh Kher , Nayneshkumar Devlani , Ajay Kumar Rai