TY - JOUR
T1 - Improved extrapolation methods of data-driven background estimations in high energy physics
AU - Choi, Suyong
AU - Oh, Hayoung
N1 - Funding Information:
This work was supported in part by the Korean National Research Foundation (NRF) Grants NRF-2018R1A2B6005043 and NRF-2020R1A2B5B02001726.
Publisher Copyright:
© 2021, The Author(s).
PY - 2021/7
Y1 - 2021/7
N2 - Data-driven methods of background estimations are often used to obtain more reliable descriptions of backgrounds. In hadron collider experiments, data-driven techniques are used to estimate backgrounds due to multi-jet events, which are difficult to model accurately. In this article, we propose an improvement on one of the most widely used data-driven methods in the hadron collision environment, the “ABCD” method of extrapolation. We describe the mathematical background behind the data-driven methods and extend the idea to propose improved general methods.
AB - Data-driven methods of background estimations are often used to obtain more reliable descriptions of backgrounds. In hadron collider experiments, data-driven techniques are used to estimate backgrounds due to multi-jet events, which are difficult to model accurately. In this article, we propose an improvement on one of the most widely used data-driven methods in the hadron collision environment, the “ABCD” method of extrapolation. We describe the mathematical background behind the data-driven methods and extend the idea to propose improved general methods.
UR - http://www.scopus.com/inward/record.url?scp=85111106041&partnerID=8YFLogxK
U2 - 10.1140/epjc/s10052-021-09404-1
DO - 10.1140/epjc/s10052-021-09404-1
M3 - Article
AN - SCOPUS:85111106041
VL - 81
JO - European Physical Journal C
JF - European Physical Journal C
SN - 1434-6044
IS - 7
M1 - 643
ER -