Publications associées à Application of machine learning techniques at the CERN Large Hadron Collider

Publications associées (19)

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

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 ...

2025

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

Christophe Emmanuel R. Lannoy

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 ...

EPFL2025

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

Jan Steggemann, Konstantin Androsov, Anna Mascellani, Joanna Malgorzata Wanczyk

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 ...

AMER PHYSICAL SOC2025

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

Ramin Mohammadi, Nikolaos Stergiopoulos, Georgios Rovas, Lydia Aslanidou, Sokratis Anagnostopoulos

Monitoring of cardiac output (CO) is a mainstay of hemodynamic management in the acutely or critically ill patient. Invasive determination of CO using thermodilution, albeit regarded as the gold standard, is cumbersome and bears risks inherent to catheteri ...

2025

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

Jan Steggemann, Konstantin Androsov, Anna Mascellani, Joanna Malgorzata Wanczyk, Paul Théodore Gabriel Pablo De Bryas Dexmiers d'Archiac

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 ...

2025

Image steganalysis using active learning and hyperparameter optimization

Zaffar Ahmed Shaikh

Image steganalysis, detecting hidden data in digital images, is essential for enhancing digital security. Traditional steganalysis methods typically rely on large, pre-labeled image datasets, which are difficult and costly to compile. To address this, this ...

Springer Science and Business Media LLC2025

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

Jérôme Chenal, Baraka Jean-Claude Munyaka

This study integrates deep learning and geospatial analysis to enhance soil loss estimation in the Moulouya Watershed, a region prone to erosion due to diverse topography and climatic conditions. Traditional models like the Universal Soil Loss Equation (US ...

AIP Publishing2025

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

Sen Zheng

Slope deformation poses significant risks to infrastructure, ecosystems, and human safety, making early and accurate predictions essential for mitigating slope failures and landslides. In this study, we propose a novel approach that integrates a fractional ...

2025

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

Devis Tuia

Estimating ecosystem-atmosphere fluxes such as evapotranspiration (ET) in a robust manner and at a global scale remains a challenge. Methods based on machine learning (ML) have shown promising results in achieving such upscaling, providing a complementary ...

2025

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

Michael Lehning, Devis Tuia, Yael Frischholz

To retrieve Surface Solar Radiation (SSR) from satellite images, a baseline reflectance of the observed ground in clear-sky conditions, also called background reflectance, is necessary to distinguish atmospheric absorption and scattering effects from surfa ...

2025

A Study on Quantum Graph Neural Networks Applied to Molecular Physics

Su Yeon Chang

This paper introduces a novel architecture for Quantum Graph Neural Networks, which is significantly different from previous approaches found in the literature. The proposed approach produces similar outcomes with respect to previous models but with fewer ...

IOP Publishing Ltd2025

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

Yves Rychener

Machine learning is increasingly integrated with decision making by powering automated systems and informing human decision makers in applications such as CV screening, portfolio allocation, loan risk assessment, and insurance approval. In this thesis, I e ...

EPFL2025

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

Olivier Schneider, Aurelio Bay, Guido Haefeli, Tatsuya Nakada, Frédéric Blanc, Lesya Shchutska, Elena Graverini, Marie Theres Christin Bachmayer, Ettore Zaffaroni, Aravindhan Venkateswaran, Yunxuan Song, Vitalii Lisovskyi, Federico Ronchetti, Radoslav Marchevski, Anni Matilda Kauniskangas, Dimitrios Kaminaris, Raphaël van Laak, Pierre Paul Louis Mayencourt, Brianna Leililani Thielen, Arnaud Merlin Gauthey, Gianluca Zunica, Abdul-Kerim Guseinov, Roberto Ribatti, Louis André Marie Jean Henry, Spencer Edward Collaviti, Julius Christian Daniel Schulte

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 ...

AMER PHYSICAL SOC2025

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

Anne-Clémence Corminboeuf, Friedrich Eisenbrand, Rubén Laplaza Solanas, Puck Elisabeth van Gerwen, Ksenia Briling, Jan Weinreich, Matthieu Nicolas Haeberle

Integer linear programming (ILP) is an elegant approach to solve linear optimization problems, naturally described using integer decision variables. Within the context of physics-inspired machine learning (ML) applied to chemistry, we demonstrate the relev ...

IOP Publishing Ltd2025

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

Pascal Fua

Faithful human performance capture and free-view rendering from sparse RGB observations is a long-standing problem in Vision and Graphics. The main challenges are the lack of observations and the inherent ambiguities of the setting, e.g. occlusions and dep ...

Springer Science and Business Media Deutschland GmbH2025

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

Olivier Schneider, Aurelio Bay, Guido Haefeli, Tatsuya Nakada, Frédéric Blanc, Lesya Shchutska, Elena Graverini, Sebastian Schulte, Marie Theres Christin Bachmayer, Serhii Cholak, Ettore Zaffaroni, Aravindhan Venkateswaran, Luis Miguel Garcia Martin, Yunxuan Song, Vitalii Lisovskyi, Sonia Amina Bouchiba, Federico Ronchetti, Radoslav Marchevski, Anni Matilda Kauniskangas, Dimitrios Kaminaris, Raphaël van Laak, Pierre Paul Louis Mayencourt, Andrea Merli, Gianluca Zunica, Abdul-Kerim Guseinov, Roberto Ribatti, Spencer Edward Collaviti

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 ...

American Physical Society (APS)2025

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

Valentine Marie Delevaux, Tanja Christina Käser Jacober, Jade Maï L Cock

Interactive simulations enhance science education and foster inquiry skills, but their open-ended nature can be cognitively overloading. While adaptive systems offer timely support, research on predicting conceptual understanding in these environments is l ...

Springer Science and Business Media Deutschland GmbH2025

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

Nikolaos Geroliminis, Emmanouil Barmpounakis, Robert Fonod, Jasso Espadaler Clapés

Overview This dataset provides high-resolution, georeferenced vehicle trajectories collected via drone footage at three roundabouts located in the municipalities of Frick and Laufenburg, Canton of Aargau, Switzerland. The data were collected as part of a ...

Zenodo2025

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

Zaffar Ahmed Shaikh

This study presents an augmented hybrid approach for improving the diagnosis of malignant skin lesions by combining convolutional neural network (CNN) predictions with selective human interventions based on prediction confidence. The algorithm retains high ...

PeerJ2025