English
Related papers

Related papers: Particle identification with machine learning in A…

200 papers

Since 2015, with the restart of the LHC for its second run of data taking, the LHCb experiment has been empowered with a dedicated computing model to select and analyse calibration samples to measure the performance of the particle…

The production of $\pi^+$, $\pi^-$, $K^+$, $K^-$, p, and pbar at mid-rapidity has been measured in proton-proton collisions at $\sqrt{s} = 900$ GeV with the ALICE detector. Particle identification is performed using the specific energy loss…

High Energy Physics - Experiment · Physics 2017-09-29 ALICE Collaboration

The ALICE HMPID (High Momentum Particle IDentification) detector has been designed to identify charged pions and kaons in the range 1 < p < 3 GeV/c and protons in the range 1.5 < p < 5 GeV/c. It consists of seven identical proximity…

Instrumentation and Detectors · Physics 2009-11-18 Giacomo Volpe

We use machine learning models to predict ion density and electron temperature from visible emission spectra, in a high energy density pulsed-power-driven aluminum plasma, generated by an exploding wire array. Radiation transport…

Plasma Physics · Physics 2023-09-01 Rishabh Datta , Faez Ahmed , Jack D Hare

The pseudorapidity density and multiplicity distributions of charged particles have been the first measurements carried out with the ALICE detector at the LHC. After an introduction on the experiment and some details on the subdetectors…

High Energy Physics - Experiment · Physics 2022-03-02 Domenico Elia

The ALICE Collaboration at CERN developed a 3D visualisation tool capable of displaying a representation of collected collision data (particle trajectories, clusters and calorimeter towers) called the Event Display. The Event Display is…

Instrumentation and Detectors · Physics 2023-09-25 Piotr Nowakowski , Przemysław Rokita , Łukasz Graczykowski

ALICE is the dedicated heavy-ion experiment at the Large Hadron Collider (LHC). It is designed to provide excellent capabilities to study the quark-gluon plasma (QGP) in the highest energy density regime opened up by the LHC. Quarkonia are…

High Energy Physics - Experiment · Physics 2019-08-13 Frederick Kramer

In this study, the first-of-its-kind use of active learning (AL) framework in thermal spray is adapted to improve the prediction accuracy of the in-flight particle characteristics and uses Gaussian Process (GP) ML model as a surrogate that…

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…

Nuclear Experiment · Physics 2008-11-26 L. Molnar

The ALICE Experiment has replaced its Inner Tracking System with a 7-layer pixel-only tracker made out of more than 24000 monolithic active pixel sensor chips, in order to fulfill the requirements of the physics program of the LHC Run 3.…

Instrumentation and Detectors · Physics 2023-02-02 Andrea Sofia Triolo

ALICE analyses mostly deal with large datasets using the distributed Grid infrastructure. In LHC running periods 1 and 2, ALICE developed a system of analysis trains (so-called $"$LEGO trains$"$) that allowed the user to configure analysis…

Instrumentation and Detectors · Physics 2021-09-21 Raquel Quishpe , Jan Fiete Grosse-Oetringhaus , Raluca Cruceru , Costin Grigoras

The ALICE TPC provides excellent charged particle tracking for the study of pp and Pb-Pb collisions at LHC. The TPC also allows particle identification via the measurement of the specific ionisation dE/dx. At high pT (pT > 3 GeV/c) this is…

High Energy Physics - Experiment · Physics 2019-08-13 L. Bryngemark

ALICE is the dedicated heavy-ion experiment at the CERN Large Hadron Collider (LHC). Its main tracking and particle-identification detector is a large volume Time Projection Chamber (TPC). The TPC has been designed to perform well in the…

Instrumentation and Detectors · Physics 2022-03-22 Mesut Arslandok , Ernst Hellbär , Marian Ivanov , Robert Helmut Münzer , Jens Wiechula

Parameter estimation remains a challenging task across many areas of engineering. Because data acquisition can often be costly, limited, or prone to inaccuracies (noise, uncertainty) it is crucial to identify sensor configurations that…

Machine Learning · Statistics 2025-11-20 Georgios Venianakis , Constantinos Theodoropoulos , Michail Kavousanakis

AMS-02 is a detector currently in operation onboard the International Space Station (ISS). One of the main scientific goals of the spectrometer is the measurement of charged particle fluxes. The detector design makes possible the…

Instrumentation and Detectors · Physics 2025-04-28 Georgi Vasilev , Galina Vankova-Kirilova , Galina Bozhkova

The next generation of particle physics experiments will face a new era of challenges in data acquisition, due to unprecedented data rates and volumes along with extreme environments and operational constraints. Harnessing this data for…

Instrumentation and Detectors · Physics 2026-03-12 Julia Gonski , Jenni Ott , Shiva Abbaszadeh , Sagar Addepalli , Matteo Cremonesi , Jennet Dickinson , Giuseppe Di Guglielmo , Erdem Yigit Ertorer , Lindsey Gray , Ryan Herbst , Christian Herwig , Tae Min Hong , Benedikt Maier , Maryam Bayat Makou , David Miller , Mark S. Neubauer , Cristián Peña , Dylan Rankin , Seon-Hee , Seo , Giordon Stark , Alexander Tapper , Audrey Corbeil Therrien , Ioannis Xiotidis , Keisuke Yoshihara , G Abarajithan , Sagar Addepalli , Nural Akchurin , Carlos Argüelles , Saptaparna Bhattacharya , Lorenzo Borella , Christian Boutan , Tom Braine , James Brau , Martin Breidenbach , Antonio Chahine , Talal Ahmed Chowdhury , Yuan-Tang Chou , Seokju Chung , Alberto Coppi , Mariarosaria D'Alfonso , Abhilasha Dave , Chance Desmet , Angela Di Fulvio , Karri DiPetrillo , Javier Duarte , Auralee Edelen , Jan Eysermans , Yongbin Feng , Emmett Forrestel , Dolores Garcia , Loredana Gastaldo , Julián García Pardiñas , Lino Gerlach , Loukas Gouskos , Katya Govorkova , Carl Grace , Christopher Grant , Philip Harris , Ciaran Hasnip , Timon Heim , Abraham Holtermann , Tae Min Hong , Gian Michele Innocenti , Koji Ishidoshiro , Miaochen Jin , Jyothisraj Johnson , Stephen Jones , Andreas Jung , Georgia Karagiorgi , Ryan Kastner , Nicholas Kamp , Doojin Kim , Kyoungchul Kong , Katie Kudela , Jelena Lalic , Bo-Cheng Lai , Yun-Tsung Lai , Tommy Lam , Jeffrey Lazar , Aobo Li , Zepeng Li , Haoyun Liu , Vladimir Lončar , Luca Macchiarulo , Christopher Madrid , Benedikt Maier , Zhenghua Ma , Prashansa Mukim , Mark S. Neubauer , Victoria Nguyen , Sungbin Oh , Isobel Ojalvo , Hideyoshi Ozaki , Simone Pagan Griso , Myeonghun Park , Christoph Paus , Santosh Parajuli , Benjamin Parpillon , Sara Pozzi , Ema Puljak , Benjamin Ramhorst , Amy Roberts , Larry Ruckman , Kate Scholberg , Sebastian Schmitt , Noah Singer , Eluned Anne Smith , Alexandre Sousa , Michael Spannowsky , Sioni Summers , Yanwen Sun , Daniel Tapia Takaki , Antonino Tumeo , Caterina Vernieri , Belina von Krosigk , Yash Vora , Linyan Wan , Michael H. L. S. Wang , Amanda Weinstein , Andy White , Simon Williams , Felix Yu

Recently, the ALICE Collaboration reported an enhancement of the yield ratio of strange and multi-strange hadrons to charged pions as a function of multiplicity at mid-rapidity in proton-proton, proton-lead, lead-lead, and xenon-xenon…

High Energy Physics - Phenomenology · Physics 2020-10-08 Luis A. Anchordoqui , Carlos Garcia Canal , Sergio J. Sciutto , Jorge F. Soriano

The ALICE detector at the LHC (A Large Ion Collider Experiment) will carry out comprehensive measurements of high energy nucleus-nucleus collisions, in order to study QCD matter under extreme conditions and the phase transtion between…

Instrumentation and Detectors · Physics 2019-08-14 Rene Bellwied

ALICE is the Large Hadron Collider (LHC) experiment dedicated to the study of heavy ion collisions. The main purpose of ALICE is to investigate the properties of a new state of deconfined nuclear matter, the Quark Gluon Plasma (QGP).…

Nuclear Experiment · Physics 2019-08-13 Pereira Da Costa Hugo

Physics-informed neural networks (PINNs) as a means of discretizing partial differential equations (PDEs) are garnering much attention in the Computational Science and Engineering (CS&E) world. At least two challenges exist for PINNs at…

Computational Physics · Physics 2023-01-23 Michael Penwarden , Shandian Zhe , Akil Narayan , Robert M. Kirby