Deuteron identification via time of flight with LHCb

TL;DR

This paper demonstrates a new method using LHCb's timing capabilities and neural networks to identify deuterons in high-energy collisions, enabling detailed studies of light ion production.

Contribution

It introduces a novel particle identification technique combining time of flight estimation and neural networks for deuterons at LHCb.

Findings

Successful deuteron identification in proton-helium collisions

Observation of deuteron and triton production

Potential to study light ion production across energies

Abstract

It is shown that the timing capabilities of the LHCb detector operated during the LHC Run 2 can be used to identify light ion particles with momenta of a few GeV/$c$. This is achieved by estimating the particle time of flight through a newly developed technique. A dedicated reconstruction procedure and a neural-network-based estimator of the particle speed have been developed to enable deuteron identification by suppressing the abundant background from lighter particles. The performance of the identification procedure is demonstrated in a sample of proton-helium collisions at $\sqrt{s_{\text{NN}}}=110$ GeV, where the production of deuteron and triton particles is observed. This novel approach opens the way to study deuteron and antideuteron production for different collision systems at different energy scales, exploiting the rich dataset collected by the LHCb experiment.