Restoration of a potential from noisy spectral data
- Authors: Ternovskii V.V.1, Khapaeva T.M.1, Khapaev M.M.1
 - 
							Affiliations: 
							
- Faculty of Computational Mathematics and Cybernetics
 
 - Issue: Vol 96, No 1 (2017)
 - Pages: 403-405
 - Section: Mathematical Physics
 - URL: https://journals.rcsi.science/1064-5624/article/view/225341
 - DOI: https://doi.org/10.1134/S1064562417040251
 - ID: 225341
 
Cite item
Abstract
Interest in the inverse Sturm–Liouville problem is motivated by its numerous applications in mathematics and computational physics. To solve a complete inverse problem, one needs two exact spectra, which are usually not known in experimental spectroscopy. Accordingly, a problem of interest is to restore the potential from a finite set of noisy spectral data. A new variational method for solving inverse spectral problems is proposed, which is based on the regularization of ill-posed problems. The method takes into account the measurement error of the spectrum and restores the potential without using simplifying assumptions that it belongs to a certain functional class. The method has been tested on potentials involving smooth segments and jump discontinuities.
About the authors
V. V. Ternovskii
Faculty of Computational Mathematics and Cybernetics
							Author for correspondence.
							Email: vladimir@chatrovlette.com
				                					                																			                												                	Russian Federation, 							Moscow, 119992						
T. M. Khapaeva
Faculty of Computational Mathematics and Cybernetics
														Email: vladimir@chatrovlette.com
				                					                																			                												                	Russian Federation, 							Moscow, 119992						
M. M. Khapaev
Faculty of Computational Mathematics and Cybernetics
														Email: vladimir@chatrovlette.com
				                					                																			                												                	Russian Federation, 							Moscow, 119992						
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