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Author Herrero, V.; Toledo, J.; Catala, J.M.; Esteve, R.; Gil, A.; Lorca, D.; Monzo, J.M.; Sanchis, F.; Verdugo, A. doi  openurl
  Title Readout electronics for the SiPM tracking plane in the NEXT-1 prototype Type Journal Article
  Year 2012 Publication Nuclear Instruments & Methods in Physics Research A Abbreviated Journal Nucl. Instrum. Methods Phys. Res. A  
  Volume 695 Issue Pages 229-232  
  Keywords Neutrino less double beta decay; Xenon gas TPC; SiPM readout; Front-end electronics; Gated integrator  
  Abstract NEXT is a new experiment to search for neutrinoless double beta decay using a 100 kg radio-pure high-pressure gaseous xenon TPC with electroluminescence readout. A large-scale prototype with a SiPM tracking plane has been built. The primary electron paths can be reconstructed from time-resolved measurements of the light that arrives to the SiPM plane. Our approach is to measure how many photons have reached each SiPM sensor each microsecond with a gated integrator. We have designed and tested a 16-channel front-end board that includes the analog paths and a digital section. Each analog path consists of three different stages: a transimpedance amplifier, a gated integrator and an offset and gain control stage. Measurements show good linearity and the ability to detect single photoelectrons.  
  Address (up) [Herrero, V.; Toledo, J.; Catala, J. M.; Esteve, R.; Monzo, J. M.; Sanchis, F.] Univ Politecn Valencia, CIEMAT, Ctr Mixto, I3M, Valencia 46022, Spain, Email: jtoledo@eln.upv.es  
  Corporate Author Thesis  
  Publisher Elsevier Science Bv Place of Publication Editor  
  Language English Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 0168-9002 ISBN Medium  
  Area Expedition Conference  
  Notes WOS:000311469900049 Approved no  
  Is ISI yes International Collaboration no  
  Call Number IFIC @ pastor @ Serial 1237  
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Author Khosa, C.K.; Mars, L.; Richards, J.; Sanz, V. url  doi
openurl 
  Title Convolutional neural networks for direct detection of dark matter Type Journal Article
  Year 2020 Publication Journal of Physics G Abbreviated Journal J. Phys. G  
  Volume 47 Issue 9 Pages 095201 - 20pp  
  Keywords dark matter; dark matter detection; neural networks; xenon1T; WIMPs  
  Abstract The XENON1T experiment uses a time projection chamber (TPC) with liquid xenon to search for weakly interacting massive particles (WIMPs), a proposed dark matter particle, via direct detection. As this experiment relies on capturing rare events, the focus is on achieving a high recall of WIMP events. Hence the ability to distinguish between WIMP and the background is extremely important. To accomplish this, we suggest using convolutional neural networks (CNNs); a machine learning procedure mainly used in image recognition tasks. To explore this technique we use XENON collaboration open-source software to simulate the TPC graphical output of dark matter signals and main backgrounds. A CNN turns out to be a suitable tool for this purpose, as it can identify features in the images that differentiate the two types of events without the need to manipulate or remove data in order to focus on a particular region of the detector. We find that the CNN can distinguish between the dominant background events (ER) and 500 GeV WIMP events with a recall of 93.4%, precision of 81.2% and an accuracy of 87.2%.  
  Address (up) [Khosa, Charanjit K.; Mars, Lucy; Richards, Joel; Sanz, Veronica] Univ Sussex, Dept Phys & Astron, Brighton BN1 9QH, E Sussex, England, Email: charanjit.kaur@sussex.ac.uk;  
  Corporate Author Thesis  
  Publisher Iop Publishing Ltd Place of Publication Editor  
  Language English Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 0954-3899 ISBN Medium  
  Area Expedition Conference  
  Notes WOS:000555607800001 Approved no  
  Is ISI yes International Collaboration yes  
  Call Number IFIC @ pastor @ Serial 4485  
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Author NEXT Collaboration (Renner, J. et al); Alvarez, V.; Carcel, S.; Cervera-Villanueva, A.; Diaz, J.; Ferrario, P.; Gil, A.; Gomez-Cadenas, J.J.; Laing, A.; Liubarsky, I.; Lorca, D.; Martin-Albo, J.; Martinez, A.; Monrabal, F.; Monserrate, M.; Muñoz Vidal, J.; Nebot-Guinot, M.; Rodriguez, J.; Serra, L.; Simon, A.; Sorel, M.; Yahlali, N. url  doi
openurl 
  Title Ionization and scintillation of nuclear recoils in gaseous xenon Type Journal Article
  Year 2015 Publication Nuclear Instruments & Methods in Physics Research A Abbreviated Journal Nucl. Instrum. Methods Phys. Res. A  
  Volume 793 Issue Pages 62-74  
  Keywords Dark matter; High pressure xenon gas; WIMP; Neutrino less double beta decay; Nuclear recoils  
  Abstract Ionization and scintillation produced by nuclear recoils in gaseous xenon at approximately 14 bar have been simultaneously observed in an electroluminescent time projection chamber. Neutrons from radioisotope a-Be neutron sources were used to induce xenon nuclear recoils, and the observed recoil spectra were compared to a detailed Monte Carlo employing estimated ionization and scintillation yields for nuclear recoils. The ability to discriminate between electronic and nuclear recoils using the ratio of ionization to primary scintillation is demonstrated. These results encourage further investigation on the use of xenon in the gas phase as a detector medium in dark matter direct detection experiments.  
  Address (up) [Renner, J.; Gehman, V. M.; Goldschmidt, A.; Matis, H. S.; Miller, T.; Nakajima, Y.; Nygren, D.; Oliveira, C. A. B.; Shuman, D.] LBNL, Berkeley, CA 94720 USA, Email: jrenner@lbl.gov  
  Corporate Author Thesis  
  Publisher Elsevier Science Bv Place of Publication Editor  
  Language English Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 0168-9002 ISBN Medium  
  Area Expedition Conference  
  Notes WOS:000355774500011 Approved no  
  Is ISI yes International Collaboration yes  
  Call Number IFIC @ pastor @ Serial 2247  
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