相关论文: Eta, Eta' and eLSM
Large language models (LLMs) are transforming electronic design automation (EDA) by enhancing design stages such as schematic design, simulation, netlist synthesis, and place-and-route. Existing methods primarily focus these optimisations…
I briefly discuss the current state of the art for models with extended scalar sectors and give examples for corresponding investigations, with a focus on processes at lepton colliders.
In this paper, we are concerned with a branch of evolutionary algorithms termed estimation of distribution (EDA), which has been successfully used to tackle derivative-free global optimization problems. For existent EDA algorithms, it is a…
This paper re-examines the density for sums of independent exponential, Erlang and gamma random variables. By using a divided difference perspective, the paper provides a unified approach to finding closed-form formulae for such…
Recent results on total cross-section measurements in gamma-gamma and gamma*-gamma* collisions at LEP are reported. Phenomenological fits to the data are presented.
The Expectation--Maximization (EM) algorithm is a simple meta-algorithm that has been used for many years as a methodology for statistical inference when there are missing measurements in the observed data or when the data is composed of…
Some aspects and applications of $ \sigma$-models in particle and condensed matter physics are briefly reviewed.
Latent Class Models (LCMs) are used to cluster multivariate categorical data, commonly used to interpret survey responses. We propose a novel Bayesian model called the Equivalence Set Restricted Latent Class Model (ESRLCM). This model…
Biomedical triple extraction systems aim to automatically extract biomedical entities and relations between entities. The exploration of applying large language models (LLM) to triple extraction is still relatively unexplored. In this work,…
We obtain an error estimate between viscosity solutions and \delta-viscosity solutions of nonhomogeneous fully nonlinear uniformly elliptic equations. The main assumption, besides uniform ellipticity, is that the nonlinearity is…
Beam polarization at e+ e- linear colliders will be a powerful tool for high precision analyses. Often it is assumed that the full information from polarization effects is provided by polarization of the electron beam and no further…
The general features of the Moller scattering and its use as an electron polarimeter are described and studied in view of the planned future high energy e^+e^- linear colliders. In particular the study concentrates on the TESLA collider…
We present further tests and applications of the new eta-eta' mixing scheme recently proposed by us. The particle states are decomposed into orthonormal basis vectors in a light-cone Fock representation. Because of flavor symmetry breaking…
We test $E_6$ realisations of a generic $U(1)'$ extended Minimal Supersymmetric Standard Model (UMSSM), parametrised in terms of the mixing angle pertaining to the new $U(1)'$ sector, $\theta_{E_6}$, against all currently available data,…
Intensive quest for the eta and eta' bound states is currently ongoing at both theoretical and experimental levels e.g. at COSY, ELSA, GSI, JINR, JPARC, LPI, and MAMI. These studies were already supported by data provided by the COSY-11…
The linear sigma model with broken U3xU3 is compared with data on the lightest scalar and pseudoscalar mesons. When 5 of the 6 parameters are fixed by the pseudoscalar masses and decay constants one finds that, already at the tree level, a…
We present a dispersive representation of the $\eta'$ transition form factor that allows one to account, in a consistent way, for the effects of $\rho$-$\omega$ mixing in both the isoscalar and the isovector contributions. Using this…
Extreme learning machine (ELM), proposed by Huang et al., has been shown a promising learning algorithm for single-hidden layer feedforward neural networks (SLFNs). Nevertheless, because of the random choice of input weights and biases, the…
Time series forecasting plays a significant role in finance, energy, meteorology, and IoT applications. Recent studies have leveraged the generalization capabilities of large language models (LLMs) to adapt to time series forecasting,…
We analyze the diagonal and transition magnetic and electric dipole moments of charged leptons in extended technicolor (ETC) models, taking account of the multiscale nature of the ETC gauge symmetry breaking, conformal (walking) behavior of…