相关论文: Eta, Eta' and eLSM
We introduce a new approach to a linear-circular regression problem that relates multiple linear predictors to a circular response. We follow a modeling approach of a wrapped normal distribution that describes angular variables and angular…
It is shown how a recent method to systematically extrapolate and resum the loop expansion for nonlinear sigma-models is related to solutions of the renormalization group equation. This relation is used to generalize the explicit equations…
This thesis concerns the testing of the SM and its extensions in e+e- collisions, the main emphasis being on neutrino physics (abridged abstract).
We measure the mass of the eta' meson using psi(2S)--> pi+ pi- J/psi, J/psi--> gamma eta' events acquired with the CLEO-c detector operating at the CESR e+e- collider. Using three decay modes, eta'--> rho0 gamma, eta'--> pi+ pi- eta with…
Finite mixture of skew distributions have emerged as an effective tool in modelling heterogeneous data with asymmetric features. With various proposals appearing rapidly in the recent years, which are similar but not identical, the…
The EM algorithm is a popular tool for maximum likelihood estimation but has not been used much for high-dimensional regularization problems in linear mixed-effects models. In this paper, we introduce the EMLMLasso algorithm, which combines…
The nonlinear sigma model (NLSM) epitomises a field-theoretical approach to (interacting) electrons in disordered media. These lectures are aimed at the audience who might have vaguely heard about its existence but know very little of what…
Total cross section for pp->pp eta process has been calculated in meson exchange model. Eta production T-matrices are from our PWA. Initial and final state interactions are disregarded for the moment, due to large uncertainties. Preliminary…
An early-stage version of simulation package ' ELSES' (Extra-Large-Scale Electronic-Structure calculation) is developed for electronic structure and dynamics of large systems, particularly, nm-scale or 10nm-scale systems (www.elses.jp).…
Within the rapidly evolving domain of Electronic Design Automation (EDA), Large Language Models (LLMs) have emerged as transformative technologies, offering unprecedented capabilities for optimizing and automating various aspects of…
In this paper, we take into account the intrinsic charm and gluonic contents into the $\eta-\eta^\prime$ mixing scheme and formulate the tetramixing $\eta-\eta^\prime-G-\eta_c$ to study the mixing properties of $\eta^{(\prime)}$ mesons.…
We propose a new eta-eta' mixing scheme where we start from the quark flavor basis and assume that the decay constants in that basis follow the pattern of particle state mixing. On exploiting the divergences of the axial vector currents -…
Model editing techniques are essential for efficiently updating knowledge in large language models (LLMs). However, the effectiveness of existing approaches degrades in massive editing scenarios, particularly when evaluated with practical…
We have revisited glueball mixing with the pseudoscalar mesons in the MIT bag model scheme. The calculation has been performed in the spherical cavity approximation to the bag using two different fermion propagators, the cavity and the free…
SEMMS (Scalable Empirical-Bayes Model for Marker Selection) is a variable-selection procedure for generalized linear models that uses a three-component normal mixture prior on regression coefficients. In its original form, SEMMS assumes…
A search for rare lepton decays of the eta meson was performed using the WASA detector at CELSIUS. Two candidates for double Dalitz decay eta->e+e-e+e- events are reported with a background of 1.3+/-0.2 events. This allows to set an upper…
Entity matching (EM) is a critical task in data integration, aiming to identify records across different datasets that refer to the same real-world entities. Traditional methods often rely on manually engineered features and rule-based…
Event sequences (ESs) arise in many practical domains including finance, retail, social networks, and healthcare. In the context of machine learning, event sequences can be seen as a special type of tabular data with annotated timestamps.…
The Expectation-Maximization (EM) algorithm is one of the most popular methods used to solve the problem of parametric distribution-based clustering in unsupervised learning. In this paper, we propose to analyze a generalized EM (GEM)…
The TESLA Technical Design Report Part III: Physics at an e+e- Linear Collider