Review of unfolding methods

被引:0
|
作者
Bogomolov, Yu V. [1 ,2 ]
Alekseev, V. V. [1 ,2 ]
Levanova, O. A. [1 ,2 ]
Mayorov, A. G. [2 ]
Malakhov, V. V. [2 ]
机构
[1] Demidov Yaroslavl State Univ, Ul Sovetskaya 14, Yaroslavl 150003, Russia
[2] Natl Res Nucl Univ, MEPhI Moscow Engn Phys Inst, Kashirskoe Shosse 31, Moscow 115409, Russia
基金
俄罗斯科学基金会;
关键词
unfolding; deconvolution; spectrum restoration methods; statistical estimates; Bayesian methods; regularization; binning-free methods; machine learning; COSMIC-RAY PROTON; INTENSITY DISTRIBUTION; NEUTRON-SPECTRA; ENERGY-SPECTRA; SPECTROMETER; DETECTOR; ACTIVATION; DENSITY;
D O I
10.3367/UFNe.2022.05.039189
中图分类号
O4 [物理学];
学科分类号
0702 ;
摘要
Very high accuracy and sensitivity have become attainable by modern instruments for experimental measurements of physical quantities in various scientific fields. Yet it is still impossible to completely eliminate the influence of instrumental effects on the result. The measured values of a physical quantity inevitably differ, sometimes significantly, from the true ones. The question therefore arises of restoring the true distributions from the measured ones, taking the specific features of the experiment and the characteristics of scientific instruments into account. Different approaches are in use based on a mathematical model of the instrument and the formulation of the deconvolution problem. We describe this problem, key ideas and methods for its solution, and features and implementation details using the example of elementary particle physics and space physics experiments.
引用
收藏
页码:628 / 642
页数:15
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