Related papers: Machine-learning-based particle identification wit…
Physics-informed neural networks (PINNs) have been proposed to solve two main classes of problems: data-driven solutions and data-driven discovery of partial differential equations. This task becomes prohibitive when such data is highly…
The ALICE detector was designed to identify hadrons over a wide range of transverse momentum at mid-rapidity. Here measurements of light charged ({\pi}, K, p) and neutral ({\Lambda}, K0S) hadrons in Pb-Pb collisions at sqrt(s_NN) = 2.76 TeV…
ALICE has been specifically optimized to study heavy-ion collisions at the LHC, up to a charged particle density of 8000 per unit of rapidity in central heavy-ion collisions at $\sqrt{s_{NN}}$ = 5.5 TeV. The High Momentum Particle…
Simulating detector responses is a crucial part of understanding the inner workings of particle collisions in the Large Hadron Collider at CERN. Such simulations are currently performed with statistical Monte Carlo methods, which are…
Collisions at high-energy particle colliders are a traditionally fruitful source of exotic particle discoveries. Finding these rare particles requires solving difficult signal-versus-background classification problems, hence machine…
Particle identification in large high-energy physics experiments typically relies on classifiers obtained by combining many experimental observables. Predicting the probability density function (pdf) of such classifiers in the multivariate…
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…
The ALICE experiment is devoted to the study of heavy-ion collisions at the CERN LHC collider. We present the results of a feasibility study for the detection of D^0 \to K^-\pi^+ decays in Pb-Pb collisions with ALICE.
High-intensity laser plasma interactions create complex computational problems because they involve both fluid and kinetic regimes, which need models that maintain physical precision while keeping computational speed. The research…
The correct identification of charged hadrons plays a crucial role in flavor-physics measurements. The final detector configurations at the proposed Future Circular Collider are yet to be determined and this study aims to contribute to this…
Machine learning models are increasingly being utilized across various fields and tasks due to their outstanding performance and strong generalization capabilities. Nonetheless, their success hinges on the availability of large volumes of…
The present document discusses plans for a compact, next-generation multi-purpose detector at the LHC as a follow-up to the present ALICE experiment. The aim is to build a nearly massless barrel detector consisting of truly cylindrical…
The ALICE experiment is a dedicated heavy ion physics detector at the LHC with unique capabilities for studying identified particle production. In this proceeding preliminary results for RAA for pi and K+p (sum), are reported, based on…
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…
The ALICE Transition Radiation Detector (TRD) significantly enlarges the scope of physics observables studied in ALICE, because it allows due to its electron identification capability to measure open heavy-flavour production and quarkonium…
After close to 20 years of preparation, the dedicated heavy ion experiment ALICE took first data at the CERN LHC accelerator with proton collisions at the end of 2009 and with lead nuclei at the end of 2010. After a short introduction into…
This work aims at the performance of the ALICE detector for the measurement of high-energy jets at mid-pseudo-rapidity in ultra-relativistic nucleus--nucleus collisions at LHC and their potential for the characterization of the partonic…
Using the unique capabilities of the ALICE detectors for particle identification, different measurements have been performed to study the properties of the hot and dense matter created in the Pb-Pb collisions at sqrt(sNN)= 2.76 TeV. The…
Azimuthal di-hadron correlations play important role in the characterization of the medium created in heavy-ion collisions at RHIC. Moreover, as a novel phenomenon, strong modification of the away-side correlation is observed in Au+Au with…
ALICE is the CERN LHC experiment optimised for the study of the strongly interacting matter produced in heavy-ion collisions and devoted to the characterisation of the quark-gluon plasma. To achieve the physics program for LHC Run 3, a…