相关论文: SFitter: Reconstructing the MSSM Lagrangian from L…

We present the first detailed, large-scale study of the Minimal Supersymmetric Standard Model (MSSM) at a $\sqrt s=500$ GeV International Linear Collider, including full Standard Model backgrounds and detector simulation. We investigate 242…

We analyze the potential of the first LHC physics run, assuming 1/fb at sqrt[s] = 7 TeV, to discover Supersymmetry (SUSY). The results are based on SUSY parameter fits following a frequentist approach. They include the experimental…

We calculate Bayes factors to quantify how the feasibility of the constrained minimal supersymmetric standard model (CMSSM) has changed in the light of a series of observations. This is done in the Bayesian spirit where probability reflects…

Fitting a data set with a parametrized model can be seen geometrically as finding the global minimum of the chi^2 hypersurface, depending on a set of parameters {P_i}. This is usually done using the Levenberg-Marquardt algorithm. The main…

We address the question whether the ILC can resolve the LHC Inverse Problem within the framework of the MSSM. We examine 242 points in the MSSM parameter space which were generated at random and were found to give indistinguishable…

Fine-tuning all parameters of Large Language Models (LLMs) is computationally expensive. Parameter-Efficient Fine-Tuning (PEFT) methods address this by selectively fine-tuning specific parameters. Most of the parameter efficient fine-tuning…

Different ways of extracting parameters of interest from combined data sets of separate experiments are investigated accounting for the systematic errors. It is shown, that the frequentist approach may yield larger $\chi^2$ values when…

Shuffled linear regression (SLR) seeks to estimate latent features through a linear transformation, complicated by unknown permutations in the measurement dimensions. This problem extends traditional least-squares (LS) and Least Absolute…

A descriptive summary is given of the results to-date from the framed standard model (FSM) which: (i) assigns geometric meaning to the Higgs field and to fermion generations, hence offering an explanation for the observed mass and mixing…

We introduce a simplified low-energy effective Lagrangian description of the phenomenology of heavy vector resonances in the minimal composite Higgs model, based on the coset SO(5)/SO(4), analysing in detail their interaction with lighter…

We evaluate all two-body decay modes of the heavy scalar top quark in the Minimal Supersymmetric Standard Model with complex parameters (cMSSM) and no generation mixing. The evaluation is based on a full one-loop calculation of all decay…

A new method for analyzing high-dimensional categorical data, Linear Latent Structure (LLS) analysis, is presented. LLS models belong to the family of latent structure models, which are mixture distribution models constrained to satisfy the…

In anticipation of data from the Large Hadron Collider (LHC) and the potential discovery of supersymmetry, in this work we seek an answer to the following: What are the chances that supersymmetry will be found at the LHC? Will the LHC data…

Supersymmetric models with low electroweak fine-tuning are more prevalent on the string landscape than fine-tuned models. We assume a fertile patch of landscape vacua containing the minimal supersymmetric standard model (MSSM) as a…

We investigate the capability of TianQin and LISA to reconstruct the model parameters in the Lagrangian of new physics scenarios that can generate an electroweak SFOPT. Taking the dimension-six Higgs operator extension of the Standard Model…

Low rank matrix factorisation is often used in recommender systems as a way of extracting latent features. When dealing with large and sparse datasets, traditional recommendation algorithms face the problem of acquiring large, unrestrained,…

Symmetry in neutrino oscillation serves for a better understanding of the physical properties of the phenomenon. We present a systematic way of finding symmetry in neutrino oscillation, which we call Symmetry Finder (SF). By extending the…

We study theoretical and computational aspects of the least squares fit (LSF) of circles and circular arcs. First we discuss the existence and uniqueness of LSF and various parametrization schemes. Then we evaluate several popular circle…

Estimating reliable geometric model parameters from the data with severe outliers is a fundamental and important task in computer vision. This paper attempts to sample high-quality subsets and select model instances to estimate parameters…

In this paper, we provide novel algorithms with identifiability guarantees for simplex-structured matrix factorization (SSMF), a generalization of nonnegative matrix factorization. Current state-of-the-art algorithms that provide…