Related papers: CompHEP/SUSY package
Atomic-level simulations are widely used to study biomolecules and their dynamics. A common goal in such studies is to compare simulations of a molecular system under several conditions -- for example, with various mutations or bound…
The emergence of foundation models, such as the Segment Anything Model (SAM), has sparked interest in Parameter-Efficient Fine-Tuning (PEFT) methods that tailor these large models to application domains outside their training data. However,…
\susy23 is a Monte-Carlo package for generating supersymmetric (SUSY) processes at $e^+e^-$ colliders. Twenty-three types of SUSY processes with 2 or 3 final state particles at tree level are included in version 2.0. {\susy23} addresses…
This paper deals with feature selection procedures for spatial point processes intensity estimation. We consider regularized versions of estimating equations based on Campbell theorem derived from two classical functions: Poisson likelihood…
SPheno is a program that accurately calculates the supersymmetric particle spectrum within a high scale theory, such as minimal supergravity, gauge mediated supersymmetry breaking, anomaly mediated supersymmetry breaking, or string…
Messenger RNA translation is often studied by means of statistical-mechanical models based on the Asymmetric Simple Exclusion Process (ASEP), which considers hopping particles (the ribosomes) on a lattice (the polynucleotide chain). In this…
We present a bottom-up approach to the question of supersymmetry breaking in the MSSM. Starting with the experimentally measurable low-energy supersymmetry breaking parameters, which can take any values consistent with present experimental…
Neutrinoless double beta decay ($\znbb$) induced by superparticle exchange is investigated. Such a supersymmetric (SUSY) mechanism of $\znbb$ decay arises within SUSY theories with R-parity non-conservation (\rp). We consider the minimal…
The ``Snowmass Points and Slopes'' (SPS) are a set of benchmark points and parameter lines in the MSSM parameter space corresponding to different scenarios in the search for Supersymmetry at present and future experiments. This set of…
In this article, we argue that models based on machine learning (ML) can be very effective in estimating the non-linear matter power spectrum ($P(k)$). We employ the prediction ability of the supervised ML algorithms to build an estimator…
Supersymmetry (SUSY) provides elegant solutions to several problems in the Standard Model and searches for SUSY particles are an important component of the LHC physics program. The latest results from electroweak and strong SUSY searches…
This paper studies a classic maximum entropy sampling problem (MESP), which aims to select the most informative principal submatrix of a prespecified size from a covariance matrix. MESP has been widely applied to many areas, including…
Obtaining high quality particle distribution representing clean geometry in pre-processing is essential for the simulation accuracy of the particle-based methods. In this paper, several level-set based techniques for cleaning up `dirty'…
We present a novel algorithm to identify potential dispersed signals of new physics in the slew of published LHC results. It employs a random walk algorithm to introduce sets of new particles, dubbed "proto-models", which are tested against…
Unlike molecular crystals, soft self-assembled fibres, micelles, vesicles, etc., exhibit a certain order in the arrangement of their constitutive monomers, but also high structural dynamicity and variability. Defects and disordered local…
In the framework of the Minimal Supersymmetric Standard Model we compute the one-loop effective action for the electroweak bosons obtained after integrating out the different sleptons, squarks, neutralinos and charginos, and present the…
In this paper, partition-based distributed state estimation of general linear systems is considered. A distributed moving horizon state estimation scheme is developed via decomposing the entire system model into subsystem models and…
The learning objective is integral to collaborative filtering systems, where the Bayesian Personalized Ranking (BPR) loss is widely used for learning informative backbones. However, BPR often experiences slow convergence and suboptimal…
Tree ensembles are powerful models that achieve excellent predictive performances, but can grow to unwieldy sizes. These ensembles are often post-processed (pruned) to reduce memory footprint and improve interpretability. We present…
For the search for electroweak particles in the Minimal Supersymmetric Standard Model (MSSM) as well as for future precision analyses of these particles an accurate knowledge of their production and decay properties is mandatory. We review…