4.3 Article

Identification and filtering of uncharacteristic noise in the CMS hadron calorimeter

期刊

JOURNAL OF INSTRUMENTATION
卷 5, 期 -, 页码 -

出版社

IOP PUBLISHING LTD
DOI: 10.1088/1748-0221/5/03/T03014

关键词

Calorimeters; Large detector systems for particle and astroparticle physics

资金

  1. FMSR (Austria)
  2. FNRS (Belgium)
  3. FWO (Belgium)
  4. CNPq (Brazil)
  5. CAPES (Brazil)
  6. FAPERJ (Brazil)
  7. FAPESP (Brazil)
  8. MES (Bulgaria)
  9. CERN
  10. CAS (China)
  11. MoST (China)
  12. NSFC (China)
  13. COLCIEN-CIAS (Colombia)
  14. MSES (Croatia)
  15. RPF (Cyprus)
  16. Academy of Sciences (Estonia)
  17. NICPB (Estonia)
  18. Academy of Finland (Finland)
  19. ME (Finland)
  20. HIP (Finland)
  21. CEA (France)
  22. CNRS/IN2P3 (France)
  23. BMBF (Germany)
  24. DFG (Germany)
  25. HGF (Germany)
  26. GSRT (Greece)
  27. OTKA (Hungary)
  28. NKTH (Hungary)
  29. DAE (India)
  30. DST (India)
  31. IPM (Iran)
  32. SFI (Ireland)
  33. INFN (Italy)
  34. NRF (Korea)
  35. LAS (Lithuania)
  36. CINVESTAV (Mexico)
  37. SEP (Mexico)
  38. UASLP-FAI (Mexico)
  39. PAEC (Pakistan)
  40. SCSR (Poland)
  41. FCT (Portugal)
  42. JINR (Armenia)
  43. JINR (Belarus)
  44. JINR (Georgia)
  45. JINR (Ukraine)
  46. JINR (Uzbekistan)
  47. MST (Russia)
  48. MAE (Russia)
  49. MSTDS (Serbia)
  50. MICINN (Spain)
  51. CPAN (Spain)
  52. Swiss Funding Agencies (Switzerland)
  53. NSC (Taipei)
  54. TUBITAK (Turkey)
  55. TAEK (Turkey)
  56. STFC (United Kingdom)
  57. DOE (USA)
  58. NSF (USA)
  59. European Union
  60. Leventis Foundation
  61. A. P. Sloan Foundation
  62. Alexander von Humboldt Foundation
  63. Science and Technology Facilities Council [PP/D004284/1, GRIDPP, ST/H000992/1, ST/F006748/1, CMS, ST/G502347/1, ST/G502412/1, ST/I002839/1, ST/I002200/1, PP/E002722/1, ST/I000410/1] Funding Source: researchfish
  64. STFC [ST/H000992/1, ST/F006748/1, ST/I000410/1, ST/I002839/1, ST/G502412/1, PP/E002722/1, ST/I002200/1, ST/G502347/1] Funding Source: UKRI

向作者/读者索取更多资源

Commissioning studies of the CMS hadron calorimeter have identified sporadic uncharacteristic noise and a small number of malfunctioning calorimeter channels. Algorithms have been developed to identify and address these problems in the data. The methods have been tested on cosmic ray muon data, calorimeter noise data, and single beam data collected with CMS in 2008. The noise rejection algorithms can be applied to LHC collision data at the trigger level or in the offline analysis. The application of the algorithms at the trigger level is shown to remove 90% of noise events with fake missing transverse energy above 100 GeV, which is sufficient for the CMS physics trigger operation.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.3
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据