Application of machine learning techniques at the CERN Large Hadron Collider

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Scientific Machine Learning (SciML) is a recently emerged research field which combines physics-based and data-driven models for the numerical approximation of differential problems. Physics-based models rely on the physical understanding of the problem at ...

Non-invasive beam diagnostics are essential for operating modern high-intensity accelerators such as the Large Hadron Collider (LHC). Among these diagnostics, Schottky monitors stand out for their ability to measure tune, chromaticity, momentum spread, and ...

A search for heavy neutral gauge bosons (Z ') decaying into a pair of tau leptons is performed in proton-proton collisions at root s = 13 TeV at the CERN LHC. The data were collected with the CMS detector and correspond to an integrated luminosity of 138 f ...

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The TOTEM Roman pot detectors are used to reconstruct the transverse momentum of scattered protons and to estimate the transverse location of the primary interaction. This paper presents new methods of track reconstruction, measurements of strip-level dete ...

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The first measurement of the CP asymmetry of the decay rate (A(CP)) and the CP average (Sigma A(FB)) and CP asymmetry (Delta A(FB)) of the forward-backward asymmetry in the muon system of Lambda(+)(c) -> p mu(+) mu(-) decays is reported. The measurement is ...

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The branching fraction of the decay B + → ψ ( 2 S ) ϕ ( 1020 ) K + , relative to the topologically similar decay B + → J / ψ ϕ ( 1020 ) K + , is measured using proton-proton collision data collected by the LHCb experiment at center-of-mass energies of 7, 8 ...

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Application of machine learning techniques at the CERN Large Hadron Collider

Chat with Graph Search

Combining physics-based and data-driven models: advancing the frontiers of research with scientific machine learning

Schottky Spectrum Modelling for High Intensity Bunched Particle Beams and Experimental Applications

Search for Heavy Neutral Resonances Decaying to Tau Lepton Pairs in Proton-proton Collisions at √s=13 Tev

Machine learning-enabled estimation of cardiac output from peripheral waveforms is independent of blood pressure measurement location in an in silico population

Proton reconstruction with the TOTEM Roman pot detectors for high-β∗ LHC data

Image steganalysis using active learning and hyperparameter optimization

Application of Deep Learning and Geospatial Analysis in Soil Loss Risk in the Moulouya Watershed, Morocco

Slope Deformation Prediction Combining Particle Swarm Optimization-Based Fractional-Order Grey Model and K-Means Clustering

On the added value of sequential deep learning for the upscaling of evapotranspiration

Retrieval of Surface Solar Radiation through Implicit Albedo Recovery from Temporal Context

A Study on Quantum Graph Neural Networks Applied to Molecular Physics

Machine Learning in Decision-Making Systems: Fairness, Robustness, and Data Bias

Search for Resonance-enhanced Cp and Angular Asymmetries in the Λc+ → Pμ+ Μ- Decay at Lhcb

Integer Linear Programming for Unsupervised Training Set Selection in Molecular Machine Learning

MetaCap: Meta-learning Priors from Multi-view Imagery for Sparse-View Human Performance Capture and Rendering

Branching fraction measurement of the decay B+→ψ(2S)ϕ(1020)K+

One Code to Predict Them All: Universal Encoding for Inquiry Modeling

Vehicle Trajectory Dataset from Drone-Collected Data at Three Swiss Roundabouts

Enhancing skin lesion classification: a CNN approach with human baseline comparison