Publications related to Beam Measurements and Machine Learning at the CERN Large Hadron Collider

Related publications (31)

Search for Fractionally Charged Particles in Proton-Proton Collisions at (Formula presented)

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

A search is presented for fractionally charged particles with charges below (Formula presented), using their small energy loss in the tracking detector as a key variable to observe a signal. The analyzed dataset corresponds to an integrated luminosity of ( ...

American Physical Society (APS)2025

Optimizing fairness and utility in healthcare machine learning models

Gökhan Özbulak

Demographic fairness or equity is a crucial aspect of machine learning models, particularly in critical domains such as healthcare, where errors can have severe consequences. A fair model avoids making distinctions between groups with different sensitive o ...

2025

Study of Ds1(2460)+→Ds+π+π- in B→D¯(*)Ds+π+π- decays

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, 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, Esteban Curras Rivera, Yifei Song, Roberto Ribatti, Alexandre Brea Rodriguez, Rita De Sousa Ataíde Da Silva, Spencer Edward Collaviti

An amplitude analysis of the Ds1(2460)+→Ds+π+π- transition is performed simultaneously in B0→D-Ds+π+π-, B+→D¯0Ds+π+π-, and B0→D*-Ds+π+π- decays. The study is based on a data sample of proton-proton collisions recorded with the LHCb detector at centre-of-ma ...

2025

Theory and applications of the sum-of-squares technique

Luca Pesce, Giovanni Piccioli, Elisabetta Cornacchia

The sum-of-squares (SOS) approximation method is a technique used in optimization problems to derive lower bounds on the optimal value of an objective function. By representing the objective function as a sum of squares in a feature space, the SOS method t ...

2024

Statistical mechanics of deep learning

Freya Behrens

2024

Socially Intelligent Networks: A framework for decision making over graphs

Ali H. Sayed

By 'social learning,' in this article we refer to mechanisms for opinion formation and decision making over graphs and the study of how agents' decisions evolve dynamically through interactions with neighbors and the environment. The study of social learni ...

2024

Accelerator-driven Data Arrangement to Minimize Transformers Run-time on Multi-core Architectures

David Atienza Alonso, Giovanni Ansaloni, Alireza Amirshahi

The increasing complexity of transformer models in artificial intelligence expands their computational costs, memory usage, and energy consumption. Hardware acceleration tackles the ensuing challenges by designing processors and accelerators tailored for t ...

2024

Neural Redshift: Random Networks are not Random Functions

Valentin Hartmann

Our understanding of the generalization capabilities of neural networks (NNs) is still incomplete. Prevailing explanations are based on implicit biases of gradient descent (GD) but they cannot account for the capabilities of models from gradient-free metho ...

IEEE2024

Reconstruction of decays to merged photons using end-to-end deep learning with domain continuation in the CMS detector

Jian Wang, Matthias Finger, Qian Wang, Yiming Li, João Miguel das Neves Duarte, Varun Sharma, Yi Zhang, Lei Zhang, Tian Cheng, Yixing Chen, Alexis Kalogeropoulos, Ioannis Papadopoulos, Hua Zhang, Siyuan Wang, Jessica Prisciandaro, Xin Chen, Michele Bianco, Sebastiana Gianì, Sun Hee Kim, Davide Di Croce, Guido Andreassi, Arvind Shah, Jian Zhao, Rakesh Chawla, Jan Steggemann, Konstantin Androsov, Federica Legger, Gabriele Grosso

A novel technique based on machine learning is introduced to reconstruct the decays of highly Lorentz boosted particles. Using an end-to-end deep learning strategy, the technique bypasses existing rule-based particle reconstruction methods typically used i ...

American Physical Society2023

Overview of Cryogenic Operation in Nanoscale Technology Nodes

Edoardo Charbon

Cryogenic operation is the backbone of many cutting edge applications. Significant work has been done to characterize and model all cryogenic effects for creating a reliable, robust and efficient cryogenic design across a wide range of technologies and pro ...

IEEE2023

Supplementary datasets for the manuscript "Generative machine learning produces kinetic models that accurately characterize intracellular metabolic states" -Part 2

Vassily Hatzimanikatis, Ljubisa Miskovic, Subham Choudhury, Michaël Roger Germain Moret, Bharath Narayanan, David Michael Moret

Supplementary files containing datasets needed to reproduce the results of the manuscript "Generative machine learning produces kinetic models that accurately characterize intracellular metabolic states" by S. Choudhury et al. The code to use with these da ...

Zenodo2023

Validating functional redundancy with mixed generative adversarial networks

Quoc Viet Hung Nguyen, Thành Tâm Nguyên, Thanh Trung Huynh

Data redundancy has been one of the most important problems in data-intensive applications such as data mining and machine learning. Removing data redundancy brings many benefits in efficient data updating, effective data storage, and error-free query proc ...

ELSEVIER2023

Personalized predictions of adverse side effects of the COVID-19 vaccines

Nahal Mansouri, Sahand Jamal Rahi

Background: Misconceptions about adverse side effects are thought to influence public acceptance of the Coronavirus disease 2019 (COVID-19) vaccines negatively. To address such perceived disadvantages of vaccines, a novel machine learning (ML) approach was ...

ELSEVIER SCI LTD2023

Data-based model maintenance in the era of industry 4.0: A methodology

Dimitrios Kyritsis, Foivos Psarommatis Giannakopoulos

Despite the high number of investments for data-based models in the expansion of Industry 4.0, too little effort has been made to ensure the maintenance of those models. In a data-streaming environment, data-based models are subject to concept drifts. A co ...

ELSEVIER SCI LTD2022

Self-Supervised Generative Style Transfer for One-Shot Medical Image Segmentation

Jean-Philippe Thiran, Seyedbehzad Bozorgtabar, Mohammad Saeed Rad, Guillaume Marc Georges Vray, Devavrat Tomar

In medical image segmentation, supervised deep networks' success comes at the cost of requiring abundant labeled data. While asking domain experts to annotate only one or a few of the cohort's images is feasible, annotating all available images is impracti ...

IEEE COMPUTER SOC2022

Bayesian Automatic Relevance Determination for Utility Function Specification in Discrete Choice Models

Michel Bierlaire, Nicola Marco Ortelli

Specifying utility functions is a key step towards applying the discrete choice framework for understanding the behaviour processes that govern user choices. However, identifying the utility function specifications that best model and explain the observed ...

IEEE Institute of Electrical and Electronics Engineers2022

Cryogenic InGaAs HEMT-Based Switches For Quantum Signal Routing

Christian Enz, Hung-Chi Han

We demonstrate cryogenic switching devices based on HEMT technology for scalable quantum computer (QC) control and readout signal routing. The switches are implemented in a quantum well network design without metal contacts between gates, and exhibit extre ...

IEEE2022

Energy hub-based optimal planning framework for user-level integrated energy systems: Considering synergistic effects under multiple uncertainties

Chengzhou Li, François Maréchal

The design of user-level integrated energy systems is challenged by a variety of combinations of energy converters, complex cascade utilization of multiple energy flows, as well as sequential matching between stochastic energy resources and periodic energy ...

ELSEVIER SCI LTD2022

Recent Advances in Piezoelectric Materials for Electromechanical Transducer Applications

Dragan Damjanovic

Ferroelectricity has made a huge impact on science and technology since Joseph Valasek (then a Ph.D. student at the University of Minnesota) discovered it in 1920, a little longer than 100 years ago. Whereas Dr. Valasek's original research was motivated by ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2022

Evidence for a New Structure in the J/ψp and J/ψ¯p Systems in B0s→J/ψp¯p Decays

Olivier Schneider, Aurelio Bay, Guido Haefeli, Tatsuya Nakada, Frédéric Blanc, Lesya Shchutska, Elena Graverini, Michel De Cian, Vladimir Macko, Federico Leo Redi, Sebastian Schulte, Donal Patrick Hill, Tara Nanut, Minh Tâm Tran, Guillaume Max Pietrzyk, Maria Vieites Diaz, Marie Theres Christin Bachmayer, Lino Ferreira Lopes, Matthieu Philippe Luther Marinangeli, Serhii Cholak, Veronica Sølund Kirsebom, Ettore Zaffaroni, Maria Elena Stramaglia, Surapat Ek-In, Ana Bárbara Rodrigues Cavalcante, Sara Celani, Carina Trippl, Sonia Amina Bouchiba, Thi Dung Nguyen, Alison Maria Tully, Mâu Chung Nguyên, Maarten Willibrord Uriël Van Dijk

An amplitude analysis of flavor-untagged B0s→J/ψp¯p decays is performed using a sample of 797±31 decays reconstructed with the LHCb detector. The data, collected in proton-proton collisions between 2011 and 2018, correspond to an integrated luminosity of 9 ...

2022