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Title: Data-directed search for new physics based on symmetries of the SM

Journal Article · · European Physical Journal. C, Particles and Fields (Online)
ORCiD logo [1];  [2];  [1];  [1];  [1];  [1]
  1. Weizmann Inst. of Science, Rehovot (Israel)
  2. Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Univ. of California, Berkeley, CA (United States)
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We propose exploiting symmetries (exact or approximate) of the Standard Model (SM) to search for physics Beyond the Standard Model (BSM) using the data-directed paradigm (DDP). Symmetries are very powerful because they provide two samples that can be compared without requiring simulation. Focusing on the data, exclusive selections which exhibit significant asymmetry can be identified efficiently and marked for further study. Using a simple and generic test statistic which compares two matrices already provides good sensitivity, only slightly worse than that of the profile likelihood ratio test statistic which relies on the exact knowledge of the signal shape. This can be exploited for rapidly scanning large portions of the measured data, in an attempt to identify regions of interest. We also demonstrate that weakly supervised Neural Networks could be used for this purpose as well.

Research Organization:
Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)
Sponsoring Organization:
USDOE Office of Science (SC), High Energy Physics (HEP); Israel Science Foundation; German Israeli Foundation
Grant/Contract Number:
AC02-05CH11231
OSTI ID:
1878108
Journal Information:
European Physical Journal. C, Particles and Fields (Online), Journal Name: European Physical Journal. C, Particles and Fields (Online) Journal Issue: 6 Vol. 82; ISSN 1434-6052
Publisher:
Springer NatureCopyright Statement
Country of Publication:
United States
Language:
English

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