dc.contributor.author | Aydın, Güral | |
dc.contributor.author | Sarıgül, Mehmet | |
dc.contributor.author | Sarıgül, Hasan | |
dc.date.accessioned | 2020-05-24T15:32:20Z | |
dc.date.available | 2020-05-24T15:32:20Z | |
dc.date.issued | 2020 | |
dc.identifier.citation | Aydın, G., Sarıgül, M., Sarıgül, H. (2020) . Position resolution study at high energies of a sampling electromagnetic calorimeter whose active material is a scintillator with Peroxide-cured polysiloxane base. Nuclear Instruments and Methods in Physics Research, Section A: Accelerators,
Spectrometers, Detectors and Associated Equipment, 955, art. no. 163341.
https://doi.org/10.1016/j.nima.2019.163341 | en_US |
dc.identifier.issn | 0168-9002 | |
dc.identifier.issn | 1872-9576 | |
dc.identifier.uri | https://doi.org/10.1016/j.nima.2019.163341 | |
dc.identifier.uri | https://hdl.handle.net/20.500.12508/1266 | |
dc.description | WOS: 000508940400030 | en_US |
dc.description.abstract | This study is based on the simulation for the position resolution performances of a sampling electromagnetic calorimeter with a Peroxide-cured polysiloxane based scintillator as an active material. Various algorithms and corrections were applied to reconstruct hit positions. Energy deposition in the center tower and neighboring towers were used to reconstruct the beam impact position in a detector tower module consisted of a 3 x 3 array matrix. Linear weights, corrected linear weights, logarithmic weights, and corrected logarithmic weights were the different algorithms to reconstruct beam hit positions through energy weighted tower positions. Moreover, the iterative weighting method based on the logarithmic weights were applied. The re-weighting algorithm based on the iterative weighting method was seen to improve the results necessarily at relatively low beam energies. Additionally, deep neural network structures were applied over the linear weights without using any logarithmic weights or correction to improve the position resolutions. | en_US |
dc.language.iso | eng | en_US |
dc.publisher | Elsevier | en_US |
dc.relation.isversionof | 10.1016/j.nima.2019.163341 | en_US |
dc.rights | info:eu-repo/semantics/closedAccess | en_US |
dc.subject | Sampling calorimeter | en_US |
dc.subject | Geant4 | en_US |
dc.subject | Logarithmic weight | en_US |
dc.subject | Iterative weighting method | en_US |
dc.subject | Deep neural network | en_US |
dc.subject.other | Calorimeters | en_US |
dc.subject.other | Curing | en_US |
dc.subject.other | Deep neural networks | en_US |
dc.subject.other | Magnetic materials | en_US |
dc.subject.other | Oxidation | en_US |
dc.subject.other | Particle detectors | en_US |
dc.subject.other | Peroxides | en_US |
dc.subject.other | Readout systems | en_US |
dc.subject.other | Scintillation counters | en_US |
dc.subject.other | Silicones | en_US |
dc.subject.other | Towers | en_US |
dc.subject.other | Electromagnetic calorimeter | en_US |
dc.subject.other | Energy depositions | en_US |
dc.subject.other | Logarithmic weight | en_US |
dc.subject.other | Neural network structures | en_US |
dc.subject.other | Position resolution | en_US |
dc.subject.other | Sampling calorimeters | |
dc.subject.other | Weighting methods | en_US |
dc.subject.other | Iterative methods | en_US |
dc.title | Position resolution study at high energies of a sampling electromagnetic calorimeter whose active material is a scintillator with Peroxide-cured polysiloxane base | en_US |
dc.type | article | en_US |
dc.relation.journal | Nuclear Instruments & Methods In Physics Research Section A: Accelerators Spectrometers Detectors and Associated Equipment | en_US |
dc.contributor.department | Mühendislik ve Doğa Bilimleri Fakültesi -- Bilgisayar Mühendisliği Bölümü | en_US |
dc.identifier.volume | 955 | en_US |
dc.relation.publicationcategory | Makale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı | en_US |
dc.contributor.isteauthor | Sarıgül, Mehmet | en_US |
dc.relation.index | Web of Science - Scopus | en_US |
dc.relation.index | Web of Science Core Collection - Science Citation Index Expanded | en_US |