papers

Publications (11)

hep-ex2026

A framework and implementation for data-driven trigger efficiency estimation at LHCb

Johannes Albrecht, James Andrew Gooding, Maxim Lysenko +3

Estimations of trigger efficiencies are essential to modern particle physics analyses. A data-driven method provides a framework in which to estimate these efficiencies from the pr…

physics.data-an2025

Scalable Multi-Task Learning for Particle Collision Event Reconstruction with Heterogeneous Graph Neural Networks

William Sutcliffe, Marta Calvi, Simone Capelli +5

The growing luminosity frontier at the Large Hadron Collider is challenging the reconstruction and analysis of particle collision events. Increased particle multiplicities are stra…

hep-ph2021

A general effective field theory description of lepton universality ratios

Gino Isidori, Davide Lancierini, Abhijit Mathad +3

We construct an expression for a general lepton flavour universality (LFU) ratio, , in decays in terms of a series of hadronic quantities which can be treat…

physics.data-an2021

Efficient description of experimental effects in amplitude analyses

Abhijit Mathad, Daniel O'Hanlon, Anton Poluektov +1

Amplitude analysis is a powerful technique to study hadron decays. A significant complication in these analyses is the treatment of instrumental effects, such as background and sel…

hep-ex2026

Minimising Event Size, Maximising Physics: Inclusive Particle Isolation for LHCb's Run 3

Marta Calvi, Tommaso Fulghesu, George Hallett +12

The Run 3 of the LHC brings unprecedented luminosity and a surge in data volume to the LHCb detector, necessitating a critical reduction in the size of each reconstructed event wit…

hep-ph2020

Probing effects of new physics in decays

Martina Ferrillo, Abhijit Mathad, Patrick Owen +1

We present, for the first time, the six-fold differential decay density expression for , taking into account the polarisation of the bary…