ML4Jets2023

Session

Reconstruction

6 Nov 2023, 14:00

Seminarraum 4a/b

Conveners

Reconstruction

• Jeremi Niedziela (Deutsches Elektronen-Synchrotron (DE))

Presentation materials

Zoom link

121. Event Reconstruction with GNNs at the FCC

Dolores Garcia (CERN)

06/11/2023, 14:00

The FCC will deliver a large dataset thanks to its unprecedented luminosity. Improving the quality of the event reconstruction at different levels will allow to increase the accuracy of the physics measurements we can achieve. For example, at the particle-level reconstruction, where information from different sub-detectors e.g tracker and calorimeter is available, ML shows promise to improve...

115. Time-of-Flight Estimation using Machine Learning Techniques

Konrad Helms

06/11/2023, 14:15

Time-of-flight (TOF) reconstruction is under investigation as a method to enhance the particle identification capabilities of detectors proposed for future Higgs factories. By utilising time measurements based on energy deposits of showers in the calorimeter system, the TOF of the particle can be inferred. The focus of our studies is the International Large Detector (ILD), a proposed detector...

56. Set2Tree: Particle decay reconstruction via GNN

Dmitrii Kobylianskii (Weizmann Institute of Science (IL))

06/11/2023, 14:30

Tree structure is a natural way to represent particle decays in high energy physics. The possibility of reconstructing the entire decay tree that ends in stable particles entering the detector is an interesting and potentially beneficial task. [The interesting and extremely helpful task is to reconstruct the entire decay process, starting from the leaf nodes, which are the reconstructed...

48. End-to-end analysis with jointly optimized particle identification and analysis optimization objectives

Matthias Vigl (Technische Universitat Munchen (DE))

06/11/2023, 14:45

Most searches at the LHC employ an analysis pipeline consisting of various discrete components, each individually optimized and later combined to provide relevant features used to discriminate SM background from potential signal. These are typically high-level features constructed from particle four-momenta. However, the combination of individually optimized tasks doesn't guarantee an optimal...

21. ν²-Flows: Fast and improved neutrino reconstruction in multi-neutrino final states with conditional normalizing flows

Johnny Raine (Universite de Geneve (CH)), Mr Matthew Leigh (University of Geneva)

06/11/2023, 15:00

In this work we introduce ν²-Flows, an extension of the ν-Flows method to final states containing multiple neutrinos. The architecture can natively scale for all combinations of object types and multiplicities in the final state for any desired neutrino multiplicities. In ttbar dilepton events, the momenta of both neutrinos and correlations between them are reconstructed more accurately than...

19. Reconstructing ALP properties and optimizing experimental design with simulation-based inference

Alessandro Morandini

06/11/2023, 15:15

Axion-like particles (ALPs) arise in beyond the Standard Model theories with global symmetry breaking. Several experiments have been constructed and proposed to look for them at different energy scales. We focus here on beam-dump experiments looking for GeV scale ALPs with macroscopic decay lengths. In this work we show that using ML we can reconstruct the ALP properties (mass and lifetime)...