scholarly journals Note on the pragmatic mode-sum regularization method: Translational-splitting in a cosmological background

2021 ◽  
Vol 103 (10) ◽  
Author(s):  
Pau Beltrán-Palau ◽  
Adrián del Río ◽  
Sergi Nadal-Gisbert ◽  
José Navarro-Salas
2020 ◽  
Vol 18 (1) ◽  
pp. 1685-1697
Author(s):  
Zhenyu Zhao ◽  
Lei You ◽  
Zehong Meng

Abstract In this paper, a Cauchy problem for the Laplace equation is considered. We develop a modified Tikhonov regularization method based on Hermite expansion to deal with the ill posed-ness of the problem. The regularization parameter is determined by a discrepancy principle. For various smoothness conditions, the solution process of the method is uniform and the convergence rate can be obtained self-adaptively. Numerical tests are also carried out to verify the effectiveness of the method.


Author(s):  
Prashant Shukla ◽  
Abhishek ◽  
Shekhar Verma ◽  
Manish Kumar

2021 ◽  
Vol 2021 (5) ◽  
Author(s):  
Peng Wang ◽  
Houwen Wu ◽  
Haitang Yang ◽  
Shuxuan Ying

Abstract It was proved more than three decades ago, that the first order α′ correction of string effective theory could be written as the Gauss-Bonnet term, which is the quadratic term of Lovelock gravity. In cosmological background, with an appropriate field redefinition, we reorganize the infinite α′ corrections of string effective action into a finite term expression for any specific dimension. This finite term expression matches Lovelock gravity exactly and thus fix the couplings of Lovelock gravity by the coefficients of string effective action. This result thus provides a strong support to string theory.


Mathematics ◽  
2021 ◽  
Vol 9 (4) ◽  
pp. 405
Author(s):  
Alexander Yeliseev ◽  
Tatiana Ratnikova ◽  
Daria Shaposhnikova

The aim of this study is to develop a regularization method for boundary value problems for a parabolic equation. A singularly perturbed boundary value problem on the semiaxis is considered in the case of a “simple” rational turning point. To prove the asymptotic convergence of the series, the maximum principle is used.


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