arXiv subjects

Hanae Tilquin

Publications and source records attributed to Hanae Tilquin.

4 recordsLinked to original sources

arXiv2026

Rare and very rare decays at the LHCb experiment

Rare and very rare decays of third-generation particles, including $b$-hadrons and $τ$ leptons, provide sensitive probes of physics beyond the Standard Model (SM). Unlike direct searches limited by collider energies, they probe new physics at much higher energy scales. Many of these decays have SM-predicted branching fractions below the sensitivity of current detectors. These proceedings report on recent LHCb searches, including several first searches and results setting the most stringent limits to date. In particular, searches for $b \to s τ^+τ^-$, $b \to s τ^\pm e^\mp$, $b \to s μ^\pm e^\mp$, and $τ^- \to μ^-μ^+μ^-$ are presented, alongside searches for lepton-number-violating processes and loop-suppressed annihilation decays.

hep-ex↗

arXiv2026

Towards replacing detector simulation with heterogeneous GNNs in flavour physics analyses

Driven by the increasing volume of recorded data, the demand for simulation from experiments based at the Large Hadron Collider will rise sharply in the coming years. Addressing this demand solely with existing computationally intensive workflows is not feasible. This paper introduces a new fast simulation tool designed to address this demand at the LHCb experiment. This tool emulates the detector response to arbitrary multibody decay topologies at LHCb. Rather than memorising specific decay channels, the model learns generalisable patterns within the response, allowing it to interpolate to channels not present in the training data. Novel heterogeneous graph neural network architectures are employed that are designed to embed the physical characteristics of the task directly into the network structure. We demonstrate the performance of the tool across a range of decay topologies, showing the networks can correctly model the relationships between complex variables. The architectures and methods presented are generic and could readily be adapted to emulate workflows at other simulation-intensive particle physics experiments.

hep-ex↗

arXiv2025

Leveraging Reinforcement Learning, Genetic Algorithms and Transformers for background determination in particle physics

Experimental studies of beauty hadron decays face significant challenges due to a wide range of backgrounds arising from the numerous possible decay channels with similar final states. For a particular signal decay, the process for ascertaining the most relevant background processes necessitates a detailed analysis of final state particles, potential misidentifications, and kinematic overlaps, which, due to computational limitations, is restricted to the simulation of only the most relevant backgrounds. Moreover, this process typically relies on the physicist's intuition and expertise, as no systematic method exists. This paper has two primary goals. First, from a particle physics perspective, we present a novel approach that utilises Reinforcement Learning (RL) to overcome the aforementioned challenges by systematically determining the critical backgrounds affecting beauty hadron decay measurements. While beauty hadron physics serves as the case study in this work, the proposed strategy is broadly adaptable to other types of particle physics measurements. Second, from a Machine Learning perspective, we introduce a novel algorithm which exploits the synergy between RL and Genetic Algorithms (GAs) for environments with highly sparse rewards and a large trajectory space. This strategy leverages GAs to efficiently explore the trajectory space and identify successful trajectories, which are used to guide the RL agent's training. Our method also incorporates a transformer architecture for the RL agent to handle token sequences representing decays.

cs.LG↗

arXiv2025

Luminosity measurement with the LHCb RICH detectors in Run 3

The LHCb Ring-Imaging Cherenkov detectors are built to provide charged hadron identification over a large range of momentum. The upgraded detectors are also capable of providing an independent measurement of the luminosity for the LHCb experiment during LHC Run 3. The modelling of the opto-electronics chain, the application of the powering strategy during operations, the calibration procedures and the proof of principle of a novel technique for luminosity determination are presented. In addition, the preliminary precision achieved during the 2023 data-taking year for real-time and offline luminosity measurements is reported.

hep-ex↗