@article{b0730c6f5b8241e5a48ec42d209d7392,
title = "Detector signal characterization with a Bayesian network in XENONnT",
abstract = "We developed a detector signal characterization model based on a Bayesian network trained on the waveform attributes generated by a dual-phase xenon time projection chamber. By performing inference on the model, we produced a quantitative metric of signal characterization and demonstrate that this metric can be used to determine whether a detector signal is sourced from a scintillation or an ionization process. We describe the method and its performance on electronic-recoil (ER) data taken during the first science run of the XENONnT dark matter experiment. We demonstrate the first use of a Bayesian network in a waveform-based analysis of detector signals. This method resulted in a 3% increase in ER event-selection efficiency with a simultaneously effective rejection of events outside of the region of interest. The findings of this analysis are consistent with the previous analysis from XENONnT, namely a background-only fit of the ER data.",
author = "{XENON Collaboration} and E. Aprile and K. Abe and {Ahmed Maouloud}, S. and L. Althueser and B. Andrieu and E. Angelino and Angevaare, {J. R.} and Antochi, {V. C.} and {Ant{\'o}n Martin}, D. and F. Arneodo and L. Baudis and Baxter, {A. L.} and M. Bazyk and L. Bellagamba and R. Biondi and A. Bismark and Brookes, {E. J.} and A. Brown and S. Bruenner and G. Bruno and R. Budnik and Bui, {T. K.} and C. Cai and Cardoso, {J. M.R.} and D. Cichon and {Cimental Chavez}, {A. P.} and Colijn, {A. P.} and J. Conrad and Cuenca-Garc{\'i}a, {J. J.} and Cussonneau, {J. P.} and V. D'Andrea and Decowski, {M. P.} and {Di Gangi}, P. and {Di Pede}, S. and S. Diglio and K. Eitel and A. Elykov and S. Farrell and Ferella, {A. D.} and C. Ferrari and H. Fischer and M. Flierman and W. Fulgione and C. Fuselli and P. Gaemers and R. Gaior and {Gallo Rosso}, A. and M. Galloway and F. Gao and R. Glade-Beucke",
note = "Publisher Copyright: {\textcopyright} 2023 authors. Published by the American Physical Society. Published by the American Physical Society under the terms of the {"}https://creativecommons.org/licenses/by/4.0/{"}Creative Commons Attribution 4.0 International license. Further distribution of this work must maintain attribution to the author(s) and the published article's title, journal citation, and DOI. Funded by SCOAP3.",
year = "2023",
month = jul,
day = "1",
doi = "10.1103/PhysRevD.108.012016",
language = "English (US)",
volume = "108",
journal = "Physical Review D",
issn = "2470-0010",
publisher = "American Physical Society",
number = "1",
}