相关论文: SFitter: Reconstructing the MSSM Lagrangian from L…
The determination of supersymmetric parameters at the LHC in favorable as well as difficult scenarios is presented. If discovered and measured at the LHC and the ILC, supersymmetry may provide a link between collider physics and cosmology.
Supervised fine-tuning (SFT) is a standard approach to adapting large language models (LLMs) to new domains. In this work, we improve the statistical efficiency of SFT by selecting an informative subset of training examples. Specifically,…
A new statistical technique for constructing linear latent structure (LLS) models from available data, supported by well established theoretical results and an efficient algorithm, is presented. The method reduces the problem of estimating…
Search for supersymmetry is carried out in the framework of the Minimal Supersymmetric Standard Model (MSSM). Using the software programs SOFTSUSY and PROSPINO, the mass spectrum and the production cross-sections of superpartners are…
We develop a general framework for estimating the $L_\infty(\mathbb{T}^d)$ error for the approximation of multivariate periodic functions belonging to specific reproducing kernel Hilbert spaces (RHKS) using approximants that are…
Supervised fine-tuning (SFT) is a critical step in aligning large language models (LLMs) with human instructions and values, yet many aspects of SFT remain poorly understood. We trained a wide range of base models on a variety of datasets…
Filtering and parameter estimation under partial information for multiscale problems is studied in this paper. After proving mean square convergence of the nonlinear filter to a filter of reduced dimension, we establish that the conditional…
Filter convergence of vector lattice-valued measures is considered, in order to deduce theorems of convergence for their decompositions. First the $\sigma$-additive case is studied, without particular assumptions on the filter; later the…
We discuss the potential of combined analyses at the Large Hadron Collider and the planned International Linear Collider to explore low-energy supersymmetry in a difficult region of the parameter space characterized by masses of the scalar…
The LHC has started to constrain supersymmetry-breaking parameters by setting bounds on possible colored particles at the weak scale. Moreover, constraints from Higgs physics, flavor physics, the anomalous magnetic moment of the muon, as…
The ability of the LHC to make statements about the dark matter problem is considered, with a specific focus on supersymmetry. After reviewing the current strategies for supersymmetry searches at the LHC (in both CMS and ATLAS), some key…
Supervised fine-tuning (SFT) is crucial for adapting Large Language Models (LLMs) to specific tasks. In this work, we demonstrate that the order of training data can lead to significant training imbalances, potentially resulting in…
We study the complementarity between dark matter experiments (direct detection and indirect detections) and accelerator facilities (the CERN LHC and a $\sqrt{s}= 1$ TeV $e^+e^-$ Linear Collider) in the framework of the constrained Minimal…
We developed a least squares fitter used for extracting expected physics parameters from the correlated experimental data in high energy physics. This fitter considers the correlations among the observables and handles the nonlinearity…
There are many low-energy models of supersymmetry breaking parameters which are motivated by theoretical and experimental considerations. Here, we discuss some of the lesser-known theories of low-energy supersymmetry, and outline their…
Run 1 of the LHC has provided three new motivations for supersymmetry: the need to stabilize the electroweak vacuum, the mass of the Higgs boson, and the fact that its couplings are Standard Model-like (so far). The prospects for…
Supersymmetric particles can be produced copiously at future colliders. From the high-precision data taken at e+e- linear colliders, TESLA in particular, and combined with results from LHC, and CLIC later, the low-energy parameters of the…
We discuss various phenomenological aspects of supersymmetric models beyond the MSSM. A particular focus is on models which can correctly explain neutrino data and the possiblities of LHC to identify the underlying scenario.
An exploit of the Sequential Importance Sampling (SIS) algorithm using Differential Algebra (DA) techniques is derived to develop an efficient particle filter. The filter creates an original kind of particles, called scout particles, that…
Hyper-spectral data can be analyzed to recover physical properties at large planetary scales. This involves resolving inverse problems which can be addressed within machine learning, with the advantage that, once a relationship between…