Related papers: Particle identification with machine learning in A…
The anomalous magnetic moment of the tau lepton ($a_{\tau}$) is a sensitive probe for the search for deviations from the Standard Model predictions and thus for new physics. This study investigates the feasibility of measuring $a_{\tau}$…
The particle-flow (PF) algorithm, which infers particles based on tracks and calorimeter clusters, is of central importance to event reconstruction in the CMS experiment at the CERN LHC, and has been a focus of development in light of…
The Large Hadron Collider (LHC), the world's largest and most powerful particle accelerator, has been a pivotal tool in advancing our understanding of fundamental physics. By colliding heavy ions (such as lead ions), the LHC recreates…
ALICE is the dedicated heavy-ion experiment at the Large Hadron Collider. The experiment has also a broad program of QCD measurements in proton-proton (pp) collisions, which have two-fold interest: the study of particle production at the…
In LHC Run 3, ALICE will increase the data taking rate significantly to 50 kHz continuous read-out of minimum bias Pb-Pb collisions. The reconstruction strategy of the online-offline computing upgrade foresees a first synchronous online…
The ALICE detector is undergoing an upgrade for Run 3 at the LHC. A new Inner Tracking System (ITS) is part of this upgrade. The upgraded ALICE ITS features the ALPIDE, a Monolithic Active Pixel Sensor. Due to IC fabrication variations and…
The popularity of Machine Learning (ML) has been increasing in the last decades in almost every area, being the commercial and scientific fields the most notorious ones. Concerning particle physics, ML has been proved as a useful resource…
The ALICE detector has excellent Particle IDentification (PID) capabilities in the central barrel ($\lvert \eta \rvert <$ 0.9). This allows identified hadron production to be measured over a wide transverse momentum ($p_{\rm{T}}$) range,…
The ALICE experiment at LHC is dedicated to study matter formed in heavy-ion collisions, but also has a strong physics program for $pp$ collisions. In these collisions, protons will collide at energies never reached before under laboratory…
We present studies of electron identification (eID) in the MPD experiment at NICA using machine learning techniques. The goal is to improve electron identification efficiency while preserving high purity, which is crucial for dielectron…
The charged particle multiplicity distribution is one of the first measurements that ALICE will be able to perform. The knowledge of this basic property at a new energy is needed to configure Monte Carlo generators correctly with the aim of…
Active Learning (AL) is a family of machine learning (ML) algorithms that predates the current era of artificial intelligence. Unlike traditional approaches that require labeled samples for training, AL iteratively selects unlabeled samples…
Physics-Informed Neural Networks (PINNs) are machine learning tools that approximate the solution of general partial differential equations (PDEs) by adding them in some form as terms of the loss/cost function of a Neural Network. Most…
We demonstrate transfer learning capabilities in a machine-learned algorithm trained for particle-flow reconstruction in high energy particle colliders. This paper presents a cross-detector fine-tuning study, where we initially pretrain the…
Heavy quarks are produced in the early stages of ultra-relativistic heavy-ion collisions, and their number is preserved throughout the subsequent evolution of the system. Therefore, they constitute ideal probes for characterising the…
First experimental results are presented on event-by-event net-proton fluctuation measurements in Pb- Pb collisions at $\sqrt{s_{NN}}$ = 2.76 TeV, recorded by the ALICE detector at the CERN LHC. The ALICE detector is well suited for such…
We demonstrate a smart laser-diffraction analysis technique for particle mixture identification. We retrieve information about the size, geometry, and ratio concentration of two-component heterogeneous particle mixtures with an efficiency…
ALICE (A Large Heavy Ion Experiment) is one of the four major experiments at the Large Hadron Collider (LHC) at CERN, which is today the most powerful particle accelerator worldwide. The High Level Trigger (HLT) is an online compute farm of…
The ALICE muon spectrometer studies the production of quarkonia and open heavy- flavour particles. It is equipped with a Trigger System composed of Resistive Plate Chambers which, by applying a transverse-momentum-based muon selection,…
After several software and hardware upgrades during LS2, ALICE records 50 KHz of minimum bias Pb--Pb collisions in continuous readout mode. To cope with the high data rate of 3.5 TB/s from the detectors, multiple stages of compression are…