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Reliable data quality monitoring is a key asset in delivering collision data suitable for physics analysis in any modern large-scale High Energy Physics experiment. This paper focuses on the use of artificial neural networks for supervised…

Data Analysis, Statistics and Probability · Physics 2018-08-03 Adrian Alan Pol , Gianluca Cerminara , Cecile Germain , Maurizio Pierini , Agrima Seth

Compared with the start-of-art energy integration detectors (EIDs), photon-counting detectors (PCDs) with energy discrimination capabilities have demonstrated great potentials in various applications of medical x-ray radiography and…

Medical Physics · Physics 2018-05-01 Ruibin Feng , David Rundle , Ge Wang

Axions and axion-like particles are hypothetical particles predicted in extensions of the standard model and are promising cold dark matter candidates. The Any Light Particle Search (ALPS II) experiment is a light-shining-through-the-wall…

The ALICE experiment features multiple particle identification systems. The measurement of the identified charged hadron $p_{t}$ spectra in proton-proton collisions at $\sqrt{s}=900$ GeV will be discussed. In the central rapidity region…

High Energy Physics - Experiment · Physics 2019-08-14 L. Milano

We describe a new neural-network technique developed for an automated recognition of solar filaments visible in the hydrogen H-alpha line full disk spectroheliograms. This technique allows neural networks learn from a few image fragments…

Neural and Evolutionary Computing · Computer Science 2007-05-23 V. V. Zharkova , V. Schetinin

The production of prompt photons at high transverse momentum in proton-proton collisions (p-p) is a useful tool to study perturbative Quantum-Chromo-Dynamics (pQCD). In particular, they yield valuable information about parton distribution…

High Energy Physics - Experiment · Physics 2011-03-23 Raphaelle Ichou

We study the electron/pion identification performance of the ALICE Transition Radiation Detector (TRD) prototypes using a neural network (NN) algorithm. Measurements were carried out for particle momenta from 2 to 6 GeV/c. An improvement in…

Instrumentation and Detectors · Physics 2012-08-27 ALICE TRD Collaboration

Although some non-trivial photon number resolving detectors exist, it may still be convenient to discriminate photon number states with the method of multiplexed detection. Multiplexing can be performed with paths in real space, with paths…

Quantum Physics · Physics 2016-01-25 Filippo. M. Miatto , Akbar Safari , Robert W. Boyd

A pulse-shape discrimination method based on artificial neural networks was applied to pulses simulated for different background, signal and signal-like interactions inside a germanium detector. The simulated pulses were used to investigate…

Instrumentation and Detectors · Physics 2015-09-02 A. Caldwell , F. Cossavella , B. Majorovits , D. Palioselitis , O. Volynets

This contribution discusses the measurements of direct photons in pp and Pb--Pb collisions from the LHC Run 2, as recorded by the ALICE experiment. Specifically, we focus on the isolated photons results obtained at $\sqrt{s_{\rm NN}}$ =…

Nuclear Experiment · Physics 2023-12-18 Carolina Arata

The particle identification capabilities of the ALICE experiment are unique among the four major LHC experiments. The working principles and excellent performance of the central barrel detectors in a high-multiplicity environment are…

High Energy Physics - Experiment · Physics 2019-08-13 Alexander Kalweit

The application of cryogenic single photon detectors has found great use in high precision particle physics experiments such as ALPS (Any Light Particle Search) II, which implements it for fundamental studies to search for new particles.…

Instrumentation and Detectors · Physics 2021-10-22 Rikhav Shah , Katharina-Sophie Isleif , Friederike Januschek , Axel Lindner , Matthias Schott

The algorithms used by the ATLAS Collaboration to reconstruct and identify prompt photons are described. Measurements of the photon identification efficiencies are reported, using 4.9 fb$^{-1}$ of pp collision data collected at the LHC at…

High Energy Physics - Experiment · Physics 2016-12-14 ATLAS Collaboration

Pulse shape discrimination plays a key role in improving the signal-to-background ratio in NEOS analysis by removing fast neutrons. Identifying particles by looking at the tail of the waveform has been an effective and plausible approach…

In this contribution the latest measurements of real and virtual photons in Pb-Pb collisions at $\sqrt{s_{\rm NN}} = 5.02$ TeV from the ALICE Collaboration are presented. The extracted photon spectra are compared to predictions from…

Nuclear Experiment · Physics 2022-11-23 Sebastian Scheid

In high energy hadron collisions, direct photons can be produced in various processes and are of particular interest to study the hot QCD medium since they escape it without being affected. In these proceedings are presented the latest…

High Energy Physics - Experiment · Physics 2019-04-04 Erwann Masson

We present two analysis techniques for distinguishing background events induced by neutrons from photon signal events in the search for the rare $K^0_L\rightarrow\pi^0\nu\bar{\nu}$ decay at the J-PARC KOTO experiment. These techniques…

High Energy Physics - Experiment · Physics 2026-04-22 Y. -C. Tung , J. Li , Y. B. Hsiung , C. Lin , H. Nanjo , T. Nomura , J. C. Redeker , N. Shimizu , S. Shinohara , K. Shiomi , Y. W. Wah , T. Yamanaka

The strong electromagnetic fields surrounding the Pb-ions accelerated at the CERN Large Hadron Collider (LHC) allow two-photon and photonuclear interactions to be studied in a so far unexplored kinematic regime. Exclusive photoproduction of…

Nuclear Experiment · Physics 2013-03-11 Joakim Nystrand

Recently, deep learning-based denoising approaches have led to dramatic improvements in low sample-count Monte Carlo rendering. These approaches are aimed at path tracing, which is not ideal for simulating challenging light transport…

Graphics · Computer Science 2020-04-28 Shilin Zhu , Zexiang Xu , Henrik Wann Jensen , Hao Su , Ravi Ramamoorthi

In this paper, detection of deception attack on deep neural network (DNN) based image classification in autonomous and cyber-physical systems is considered. Several studies have shown the vulnerability of DNN to malicious deception attacks.…

Image and Video Processing · Electrical Eng. & Systems 2020-07-10 Darpan Kumar Yadav , Kartik Mundra , Rahul Modpur , Arpan Chattopadhyay , Indra Narayan Kar