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The latest BaBar measurements of the ratios ${\cal R}(D^{(*)})=\displaystyle{\frac{{\cal B}(B \to D^{(*)} \tau {\bar \nu}_\tau)}{{\cal B}(B \to D^{(*)} \mu {\bar \nu}_\mu)}}$ deviate from the Standard Model predictions at the global level…

High Energy Physics - Phenomenology · Physics 2014-11-07 Fulvia De Fazio

Recently, several indications of lepton non-universality observables have been perceived in semileptonic $B$ meson decay processes, both in the neutral-current ($b \to s ll $) and charged-current ($b \to c l \bar \nu_l$) transitions.…

High Energy Physics - Phenomenology · Physics 2025-07-16 Aishwarya Bhatta , Rukmani Mohanta

For a general $H_b\to H_c\tau\bar\nu_\tau$ decay we analyze the role of the $\tau$ polarization vector ${\cal P}^\mu$ in the context of lepton flavor universality violation studies. We use a general phenomenological approach that includes,…

High Energy Physics - Phenomenology · Physics 2021-07-07 N. Penalva , E. Hernández , J. Nieves

Heavy quark decays provide a very advantageous investigation to test the Standard Model (SM). Recently, promising experiments with \textit{b} quark, as well as the analysis of the huge data sets produced at the B factories, have led to an…

High Energy Physics - Phenomenology · Physics 2015-05-14 Wanwei Wu

We propose a new framework for Hamiltonian Monte Carlo (HMC) on truncated probability distributions with smooth underlying density functions. Traditional HMC requires computing the gradient of potential function associated with the target…

Machine Learning · Statistics 2017-09-12 Kexin Yi , Finale Doshi-Velez

Hamiltonian Monte Carlo (HMC) is a state of the art method for sampling from distributions with differentiable densities, but can converge slowly when applied to challenging multimodal problems. Running HMC with a time varying Hamiltonian,…

Machine Learning · Statistics 2026-02-26 Reuben Cohn-Gordon , Uroš Seljak , Dries Sels

The semileptonic decay of heavy flavor mesons offers a clean environment for extraction of the Cabibbo-Kobayashi-Maskawa (CKM) matrix elements, which describes the CP-violating and flavor changing process in the Standard Model. The involved…

High Energy Physics - Phenomenology · Physics 2021-03-17 Lu Zhang , Xian-Wei Kang , Xin-Heng Guo , Ling-Yun Dai , Tao Luo , Chao Wang

Bayesian formulation of modern day signal processing problems has called for improved Markov chain Monte Carlo (MCMC) sampling algorithms for inference. The need for efficient sampling techniques has become indispensable for high…

Computation · Statistics 2025-10-28 Apratim Shukla , Dootika Vats , Eric C. Chi

The hybrid Monte Carlo (HMC) algorithm is arguably the most efficient sampling method for general probability distributions of continuous variables. Together with exact Fourier acceleration (EFA) the HMC becomes equivalent to direct…

High Energy Physics - Lattice · Physics 2025-07-23 Johann Ostmeyer

Hamiltonian Monte Carlo (HMC) is widely used for sampling from high dimensional target distributions with densities known up to proportionality. While HMC exhibits favorable scaling properties in high dimensions, it struggles with strongly…

Computation · Statistics 2025-07-30 Joonha Park

With the recently increased interest in probabilistic models, the efficiency of an underlying sampler becomes a crucial consideration. Hamiltonian Monte Carlo (HMC) is one popular option for models of this kind. Performance of the method,…

We investigate the $\Lambda_c \to \Lambda \ell^{+} \nu_\ell$ decay with a focus on potential new physics (NP) effects in the $\ell = \mu$ channel. We employ an effective Hamiltonian within the framework of the Standard Model Effective Field…

High Energy Physics - Phenomenology · Physics 2024-09-16 Fernando Alvarado , Luis Alvarez-Ruso , Eliecer Hernandez , Juan Nieves , Neus Penalva

We introduce a variant of the Hybrid Monte Carlo (HMC) algorithm to address large-deviation statistics in stochastic hydrodynamics. Based on the path-integral approach to stochastic (partial) differential equations, our HMC algorithm…

Computational Physics · Physics 2019-10-29 G. Margazoglou , L. Biferale , R. Grauer , K. Jansen , D. Mesterházy , T. Rosenow , R. Tripiccione

In the context of lepton flavor universality violation (LFUV) studies, we fully derive a general tensor formalism to investigate the role that left- and right-handed neutrino new-physics (NP) terms may have in $b\to c \tau\bar\nu_\tau$…

High Energy Physics - Phenomenology · Physics 2021-11-03 N. Penalva , E. Hernández , J. Nieves

Recently, several hints of lepton non-universality have been observed in the semileptonic B meson decays in terms of both in the neutral current ($b\to s l \bar{l}$) and charged current ($b\to c l \bar{\nu_{l}}$) transitions. Motivated by…

High Energy Physics - Phenomenology · Physics 2020-10-07 Jin-Huan Sheng , Jie Zhu , Xiao-Nan Li , Quan-Yi Hu , Ru-Min Wang

We introduce the Hamming Ball Sampler, a novel Markov Chain Monte Carlo algorithm, for efficient inference in statistical models involving high-dimensional discrete state spaces. The sampling scheme uses an auxiliary variable construction…

Methodology · Statistics 2015-05-05 Michalis K. Titsias , Christopher Yau

Considering the recent experimental results on exclusive semileptonic $B$ meson decays showing sizable departure from their Standard Model prediction of lepton flavor universality and keeping ongoing and proposed non-standard Higgs searches…

High Energy Physics - Phenomenology · Physics 2019-07-25 Aritra Biswas , Dilip Kumar Ghosh , Sunando Kumar Patra , Avirup Shaw

We derive a robust sum rule among the branching fractions of $\Lambda_b \to \Lambda \nu \bar\nu$ and $B \to K^{(\ast)} \nu\bar\nu$, assuming that right-handed neutrinos are decoupled. Despite the presence of 18 independent Wilson…

High Energy Physics - Phenomenology · Physics 2026-04-23 Teppei Kitahara , Manas Kumar Mohapatra , Kota Sasaki

The goal of this article is to introduce the Hamiltonian Monte Carlo (HMC) method -- a Hamiltonian dynamics-inspired algorithm for sampling from a Gibbs density $\pi(x) \propto e^{-f(x)}$. We focus on the "idealized" case, where one can…

Data Structures and Algorithms · Computer Science 2021-08-30 Nisheeth K. Vishnoi

A novel method for extracting physical parameters from experimental and simulation data is presented. The method is based on statistical concepts and it relies on Monte Carlo simulation techniques. It identifies and determines with maximal…

High Energy Physics - Phenomenology · Physics 2012-05-31 C. N. Papanicolas , E. Stiliaris