相关论文: New developments in SModelS
The ATLAS and CMS experiments at the Large Hadron Collider (LHC) at CERN have searched for signals of new physics, in particular for supersymmetry. The data collected until 2012 at center-of-mass energies of 7 and 8 TeV and integrated…
We study the fully automated amortised analysis of purely functional data structures like skew heaps, as well as weight- and rank-biased leftist heaps. For that we generalise earlier works on automated amortised resource analysis by…
A concise review of precision measurements in the Higgs sector of the Standard Model (SM) of particle physics is given using ATLAS and CMS data. The results are based on LHC Run-2 data, taken between 2015 and 2018. Impressive progress has…
With the LHC successfully collecting data at 7 TeV, plans are actively advancing for a series of upgrades leading eventually to about five times the LHC design-luminosity some 10-years from now in the High-Luminosity LHC (HL-LHC) project.…
The formal analysis of automated systems is an important and growing industry. This activity routinely requires new verification frameworks to be developed to tackle new programming features, or new considerations (bugs of interest). Often,…
We present a python-based program for phenomenological investigations in particle physics using machine learning algorithms, called \verb"MLAnalysis". The program is able to convert LHE and LHCO files generated by \verb"MadGraph5_aMC@NLO"…
In the high luminosity scenario of the LHC (HL-LHC), which will bring the instantaneous luminosity up to 7.5\,$\times$\,$10^{34}$\,cm$^{-2}$s$^{-1}$, ATLAS and CMS will need to operate at up to 200 interactions per 25\,ns beam crossing and…
The Cosmology and Astrophysics with MachinE Learning Simulations (CAMELS) project was developed to combine cosmology with astrophysics through thousands of cosmological hydrodynamic simulations and machine learning. CAMELS contains 4,233…
ATLAS is a multipurpose experiment at the LHC. The tracking system of ATLAS, embedded in a 2 T solenoidal field, is composed of different technologies: silicon planar sensors (pixel and microstrips) and drift-tubes. The procedure used to…
Large language models (LLMs) and transformer-based architectures are increasingly utilized for source code analysis. As software systems grow in complexity, integrating LLMs into code analysis workflows becomes essential for enhancing…
The MadGraph5 aMC@NLO framework aims to automate all types of leading- and next-to-leading-order-accurate simulations for any user-defined model that stems from a renormalisable Lagrangian. In this paper, we present all of the key…
Several recently devised machine learning (ML) algorithms have shown improved accuracy for various predictive problems. Model searches, which explore to find an optimal ML algorithm and hyperparameter values for the target problem, play a…
We introduce a family of interpretable machine learning models, with two broad additions: Linearised Additive Models (LAMs) which replace the ubiquitous logistic link function in General Additive Models (GAMs); and SubscaleHedge, an expert…
Searches for new physics at the Large Hadron Collider have constrained many models of physics beyond the Standard Model. Many searches also provide resources that allow them to be reinterpreted in the context of other models. We describe a…
Biomedical research results are being published at a high rate, and with existing search engines, the vast amount of published work is usually easily accessible. However, reproducing published results, either experimental data or…
In this talk, we present the program Lilith, a python package for constraining new physics from Higgs measurements. We discuss the usage of signal strength results in the latest published version of Lilith, which allows for constraining…
The investigation of the electroweak symmetry breaking is one of the primary tasks of the experiments at the CERN Large Hadron Collider (LHC). The potential of the ATLAS experiment for the discovery of the Higgs boson(s) in Standard Model…
In recent years, machine learning (ML) has gained significant popularity in the field of chemical informatics and electronic structure theory. These techniques often require researchers to engineer abstract "features" that encode chemical…
Events containing a pair of high energy hadronic jet can provide clear signatures in the search for new physics at high energy hadron colliders. The ATLAS and CMS experiments collected the data from LHC collisions at $\sqrt{s}$= 13 TeV…
A summary of the sensitivity of the ATLAS and CMS experiments at the LHC to discover a Standard Model Higgs boson is presented. Some prospects for Minimal Supersymmetric Standard Model Higgs searches at LHC are also included.