Open AccessRegularization methods for ill-posed problems of general physics
Author(s) -
V. M. Starkov
Publication year - 2021
Publication title -
fìziko-matematične modelûvannâ ta ìnformacìjnì tehnologìï/fìzìko-matematične modelûvannâ ta ìnformacìjnì tehnologìï
Language(s) - English
Resource type - Journals
eISSN - 2617-5258
pISSN - 1816-1545
DOI - 10.15407/fmmit2021.33.148
Subject(s) - tikhonov regularization , regularization (linguistics) , well posed problem , mathematics , operator (biology) , hadamard transform , countable set , inverse problem , mathematical analysis , pure mathematics , computer science , biochemistry , chemistry , repressor , artificial intelligence , transcription factor , gene
On the example of a specific physical problem of noise reduction associated with losses, dark counts, and background radiation, a summary of methods for regularizing ill-posed problems is given in the statistics of photocounts of quantum light. The mathematical formulation of the problem is presented by an operator equation of the first kind. The operator is generated by a matrix with countable elements. In the sense of Hadamard, the problem of reconstructing the number of photons of quantum light is due to the compactness of the operator of the mathematical model. A rigorous definition of a regularizing operator (regularizer) is given. The problem of stable approximation to the exact solution of the operator equation with inaccurately given initial data can be overcome by one of the most well-known regularization methods, the theoretical foundations of which were laid in the works of A.N. Tikhonov. The selection of an important class of regularizing algorithms is based on the construction of a parametric family of functions that are Borel measurable on the semiaxis and satisfy some additional conditions. The set of regularizers in this family includes most of the known regularization methods. The main ones are given in the work.