Reformulation of a likelihood approach to fake-lepton estimation in the framework of Bayesian inference

被引：1

作者：

Erdmann, Johannes ^{[1
]}

Grunwald, Cornelius ^{[1
]}

Kroeninger, Kevin ^{[1
]}

La Cagnina, Salvatore ^{[1
]}

Roehrig, Lars ^{[1
]}

Varnes, Erich ^{[2
]}

机构：

[1] TU Dortmund Univ, Expt Phys 4, Dortmund, Germany

[2] Univ Arizona, Dept Phys, Tucson, AZ 85721 USA

来源：

NUCLEAR INSTRUMENTS & METHODS IN PHYSICS RESEARCH SECTION A-ACCELERATORS SPECTROMETERS DETECTORS AND ASSOCIATED EQUIPMENT | 2022年 / 1021卷

关键词：

Bayesian inference; Particle physics; Hadron-collider experiment; Fake-lepton background;

D O I：

10.1016/j.nima.2021.165939

中图分类号：

TH7 [仪器、仪表];

学科分类号：

0804 ; 080401 ; 081102 ;

摘要：

Prompt isolated leptons are essential in many analyses in high-energy particle physics but are subject to fake lepton background, i.e. objects that mimic the lepton signature. The fake-lepton background is difficult to estimate from simulation and is often directly determined from data. A popular method is the matrix method, which however suffers from several limitations. This paper recapitulates an alternative approach based on a likelihood with Poisson constraints and reformulates the problem from a different starting point in the framework of Bayesian statistics. The equality of both approaches is shown and several cases are studied in which the matrix method is limited. In addition, the fake-lepton background is recalculated and compared to the estimate with the matrix method in an example top-quark measurement.

引用

页数：8

共 50 条

[41] An MCMC based Bayesian inference approach to parameter estimation of distributed lag models for forecasting used product returns for remanufacturing
Geda M.
Kwong C.K.
[J]. Journal of Remanufacturing, 2021, 11 (3) : 175 - 194
[42] On estimating the parameters of generalized logistic model from census data: Drawback of classical approach and reliable inference using Bayesian framework
Mestry, Dipali Vasudev
Bhowmick, Amiya Ranjan
[J]. ECOLOGICAL INFORMATICS, 2021, 62
[43] A comparison of salmon escapement estimates using a hierarchical Bayesian approach versus separate maximum likelihood estimation of each year's return
Adkison, MD
Su, ZM
[J]. CANADIAN JOURNAL OF FISHERIES AND AQUATIC SCIENCES, 2001, 58 (08) : 1663 - 1671
[44] Maximum Likelihood Estimation of Regularization Parameters in High-Dimensional Inverse Problems: An Empirical Bayesian Approach Part I: Methodology and Experiments
Vidal, Ana Fernandez
De Bortoli, Valentin
Pereyra, Marcelo
Durmus, Alain
[J]. SIAM JOURNAL ON IMAGING SCIENCES, 2020, 13 (04): : 1945 - 1989
[45] Stochastic event-triggered remote state estimation over Gaussian channels without knowing triggering decisions: A Bayesian inference approach
Deng, Di
Xiong, Junlin
[J]. AUTOMATICA, 2023, 152
[46] Estimation of amino acid residue substitution rates at local spatial regions and application in protein function inference: A Bayesian Monte Carlo approach
Tseng, YY
Liang, J
[J]. MOLECULAR BIOLOGY AND EVOLUTION, 2006, 23 (02) : 421 - 436
[47] Maximum Likelihood Estimation of Regularization Parameters in High-Dimensional Inverse Problems: An Empirical Bayesian Approach. Part II: Theoretical Analysis
De Bortoli, Valentin
Durmus, Alain
Pereyra, Marcelo
Vidal, Ana Fernandez
[J]. SIAM JOURNAL ON IMAGING SCIENCES, 2020, 13 (04): : 1990 - 2028
[48] Comparison of Likelihood-Free Inference Approach and a Formal Bayesian Method in Parameter Uncertainty Assessment: Case Study with a Single-Event Rainfall-Runoff Model
Nourali, Mahrouz
[J]. JOURNAL OF HYDROLOGIC ENGINEERING, 2021, 26 (03)
[49] Parameter estimation of thermal response test: A Bayesian inference using Markov chain Monte Carlo-Metropolis Hastings (MCMC-MH) approach
Bathina, Siva K.
Siddapureddy, Sudheer
[J]. INTERNATIONAL JOURNAL OF THERMAL SCIENCES, 2023, 193
[50] Inverse Approach Using Bio-Inspired Algorithm Within Bayesian Framework for the Estimation of Heat Transfer Coefficients During Solidification of Casting
Vishweshwara, P. S.
Gnanasekaran, N.
Arun, M.
[J]. JOURNAL OF HEAT TRANSFER-TRANSACTIONS OF THE ASME, 2020, 142 (01):

← 1 2 3 4 5 →