A Deep Neural Network for Simultaneous Estimation of b Jet Energy and Resolution

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...

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Bibliographic Details
Main Authors: 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
Other Authors: Massachusetts Institute of Technology. Department of Physics
Format: Article
Language:English
Published: Springer International Publishing 2021
Online Access:https://hdl.handle.net/1721.1/129404

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