Kinematic edge detection using finite impulse response filters

作     者：Berggren, M. Caiazza, S. Chera, M. List, J. 

作者机构：DESY Notkestr 85 D-22607 Hamburg Germany Univ Hamburg Dept Phys Luruper Chaussee 149 D-22761 Hamburg Germany 

出 版 物：《NUCLEAR INSTRUMENTS & METHODS IN PHYSICS RESEARCH SECTION A-ACCELERATORS SPECTROMETERS DETECTORS AND ASSOCIATED EQUIPMENT》 (物理学研究中的核仪器与方法，A辑：加速器，分光仪，检测器和相关设备)

年 卷 期：2021年第1010卷

页      面：165555-165555页

核心收录：

学科分类：08[工学] 0804[工学-仪器科学与技术] 0827[工学-核科学与技术] 0702[理学-物理学] 

基　　金：Deutsche Forschungsgemeinschaft (DFG)  Germany through the Collaborative Research Centre SFB 676 "Particles  Strings and the Early Universe" 

主　　题：Edge detection FIR filter e(+)e(-) collider Supersymmetry Analysis algorithm Mass reconstruction 

摘      要：Various physics observables can be determined from the localization of distinct edge-like features in distributions of measurement values. In this paper, we address the observation that neither differentiating nor fitting the measured distributions is robust against significant fluctuations in the experimental data. We propose the application of Finite Impulse Response (FIR) filters instead . To demonstrate the method, we consider the typical case in particle physics in which the precise localization of kinematic edges, often blurred by e.g. background contributions and detector effects, is crucial for determining particle masses. We show that even for binned data, typical for high energy physics, the optimal FIR filter kernel can be approximated by the first derivative of a Gaussian (FDOG). We study two highly complementary supersymmetric scenarios that, if realized in nature, could be observed at a future high-energy e(+)e(-) collider such as the International Linear Collider (ILC) or the Compact Linear Collider (CLIC). The first scenario considers the production of (e) over tilde (+/-)-pairs while the second focuses on the (chi) over tilde (+/-)(1) and (chi) over tilde (0)(2)-pair production. We demonstrate that the FIR filter method for edge extraction is superior to previously employed methods in terms of robustness and precision.