A Deep Neural Network for Simultaneous Estimation of b Jet Energy and Resolution
We describe a method to obtain point and dispersion estimates for the energies of jets arising from b quarks produced in proton–proton collisions at an energy of √ s = 13 TeV at the CERN LHC. The algorithm is trained on a large sample of simulated b jets and validated on data recorded by the CMS de...
| Main Authors: | , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
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Springer International Publishing
2021
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| Online Access: | https://hdl.handle.net/1721.1/129404 |
| _version_ | 1826192095137759232 |
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| author | Abercrombie, Daniel Robert Allen, Benjamin E. Baty, Austin Alan Bi, Ran Brandt, Stephanie Akemi Busza, Wit Cali, Ivan Amos D'Alfonso, Mariarosaria Gomez-Ceballos, Guillelmo Goncharov, Maxim Harris, Philip Coleman Hsu, David Hu, Miao Klute, Markus Kovalskyi, Dmytro Lee, Youjin Luckey Jr, P David Maier, Benedikt Marini, Andrea Carlo McGinn, Christopher Francis Mironov, Camelia Maria Narayanan, Sruthi Annapoorny Niu, Xinmei Paus, Christoph M. E. Rankin, Dylan Sheldon Roland, Christof E Roland, Gunther M Shi, Zhenhua Stephans, George S. F. Sumorok, Konstanty C Tatar, Kaya Velicanu, Dragos Alexandru Wang, J. Wang, Tianwen Wyslouch, Boleslaw |
| author2 | Massachusetts Institute of Technology. Department of Physics |
| author_facet | Massachusetts Institute of Technology. Department of Physics Abercrombie, Daniel Robert Allen, Benjamin E. Baty, Austin Alan Bi, Ran Brandt, Stephanie Akemi Busza, Wit Cali, Ivan Amos D'Alfonso, Mariarosaria Gomez-Ceballos, Guillelmo Goncharov, Maxim Harris, Philip Coleman Hsu, David Hu, Miao Klute, Markus Kovalskyi, Dmytro Lee, Youjin Luckey Jr, P David Maier, Benedikt Marini, Andrea Carlo McGinn, Christopher Francis Mironov, Camelia Maria Narayanan, Sruthi Annapoorny Niu, Xinmei Paus, Christoph M. E. Rankin, Dylan Sheldon Roland, Christof E Roland, Gunther M Shi, Zhenhua Stephans, George S. F. Sumorok, Konstanty C Tatar, Kaya Velicanu, Dragos Alexandru Wang, J. Wang, Tianwen Wyslouch, Boleslaw |
| author_sort | Abercrombie, Daniel Robert |
| collection | MIT |
| description | We describe a method to obtain point and dispersion estimates for the energies of jets arising from b quarks produced in proton–proton collisions at an energy of √ s = 13 TeV at the CERN LHC. The algorithm is trained on a large sample of simulated b jets and validated on data recorded by the CMS detector in 2017 corresponding to an integrated luminosity of 41 fb⁻¹. A multivariate regression algorithm based on a deep feed-forward neural network employs jet composition and shape information, and the properties of reconstructed secondary vertices associated with the jet. The results of the algorithm are used to improve the sensitivity of analyses that make use of b jets in the final state, such as the observation of Higgs boson decay to b[overline b].
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| first_indexed | 2024-09-23T09:06:11Z |
| format | Article |
| id | mit-1721.1/129404 |
| institution | Massachusetts Institute of Technology |
| language | English |
| last_indexed | 2024-09-23T09:06:11Z |
| publishDate | 2021 |
| publisher | Springer International Publishing |
| record_format | dspace |
| spelling | mit-1721.1/1294042022-09-30T13:26:24Z A Deep Neural Network for Simultaneous Estimation of b Jet Energy and Resolution Abercrombie, Daniel Robert Allen, Benjamin E. Baty, Austin Alan Bi, Ran Brandt, Stephanie Akemi Busza, Wit Cali, Ivan Amos D'Alfonso, Mariarosaria Gomez-Ceballos, Guillelmo Goncharov, Maxim Harris, Philip Coleman Hsu, David Hu, Miao Klute, Markus Kovalskyi, Dmytro Lee, Youjin Luckey Jr, P David Maier, Benedikt Marini, Andrea Carlo McGinn, Christopher Francis Mironov, Camelia Maria Narayanan, Sruthi Annapoorny Niu, Xinmei Paus, Christoph M. E. Rankin, Dylan Sheldon Roland, Christof E Roland, Gunther M Shi, Zhenhua Stephans, George S. F. Sumorok, Konstanty C Tatar, Kaya Velicanu, Dragos Alexandru Wang, J. Wang, Tianwen Wyslouch, Boleslaw Massachusetts Institute of Technology. Department of Physics Massachusetts Institute of Technology. Department of Nuclear Science and Engineering Massachusetts Institute of Technology. Laboratory for Nuclear Science Lincoln Laboratory We describe a method to obtain point and dispersion estimates for the energies of jets arising from b quarks produced in proton–proton collisions at an energy of √ s = 13 TeV at the CERN LHC. The algorithm is trained on a large sample of simulated b jets and validated on data recorded by the CMS detector in 2017 corresponding to an integrated luminosity of 41 fb⁻¹. A multivariate regression algorithm based on a deep feed-forward neural network employs jet composition and shape information, and the properties of reconstructed secondary vertices associated with the jet. The results of the algorithm are used to improve the sensitivity of analyses that make use of b jets in the final state, such as the observation of Higgs boson decay to b[overline b]. . 2021-01-13T17:04:43Z 2021-01-13T17:04:43Z 2020-10 2019-12 2021-01-03T04:16:35Z Article http://purl.org/eprint/type/JournalArticle 2510-2044 2510-2036 https://hdl.handle.net/1721.1/129404 Sirunyan, A. M. et al. "A Deep Neural Network for Simultaneous Estimation of b Jet Energy and Resolution." Computing and Software for Big Science 4, 10 (October 2020): doi.org/10.1007/s41781-020-00041-z. © 2020 The Author(s) en https://doi.org/10.1007/s41781-020-00041-z Computing and Software for Big Science Creative Commons Attribution https://creativecommons.org/licenses/by/4.0/ The Author(s) application/pdf Springer International Publishing Springer International Publishing |
| spellingShingle | Abercrombie, Daniel Robert Allen, Benjamin E. Baty, Austin Alan Bi, Ran Brandt, Stephanie Akemi Busza, Wit Cali, Ivan Amos D'Alfonso, Mariarosaria Gomez-Ceballos, Guillelmo Goncharov, Maxim Harris, Philip Coleman Hsu, David Hu, Miao Klute, Markus Kovalskyi, Dmytro Lee, Youjin Luckey Jr, P David Maier, Benedikt Marini, Andrea Carlo McGinn, Christopher Francis Mironov, Camelia Maria Narayanan, Sruthi Annapoorny Niu, Xinmei Paus, Christoph M. E. Rankin, Dylan Sheldon Roland, Christof E Roland, Gunther M Shi, Zhenhua Stephans, George S. F. Sumorok, Konstanty C Tatar, Kaya Velicanu, Dragos Alexandru Wang, J. Wang, Tianwen Wyslouch, Boleslaw A Deep Neural Network for Simultaneous Estimation of b Jet Energy and Resolution |
| title | A Deep Neural Network for Simultaneous Estimation of b Jet Energy and Resolution |
| title_full | A Deep Neural Network for Simultaneous Estimation of b Jet Energy and Resolution |
| title_fullStr | A Deep Neural Network for Simultaneous Estimation of b Jet Energy and Resolution |
| title_full_unstemmed | A Deep Neural Network for Simultaneous Estimation of b Jet Energy and Resolution |
| title_short | A Deep Neural Network for Simultaneous Estimation of b Jet Energy and Resolution |
| title_sort | deep neural network for simultaneous estimation of b jet energy and resolution |
| url | https://hdl.handle.net/1721.1/129404 |
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