Green's function of the generalized Dirac equation for plane electromagnetic and longitudinal electrical wave fields

1985 ◽  
Vol 28 (1) ◽  
pp. 36-39
Author(s):  
P. V. Strokov ◽  
G. I. Flesher
Keyword(s):  
Dirac Equation ◽  
Green’S Function ◽  
Green's Function ◽  
Wave Fields ◽  
Generalized Dirac Equation

Green's function of a generalized Dirac equation for constant fields

1980 ◽  
Vol 23 (11) ◽  
pp. 973-976
Author(s):  
P. M. Lavrov ◽  
G. I. Flesher
Keyword(s):  
Dirac Equation ◽  
Green’S Function ◽  
Green's Function ◽  
Generalized Dirac Equation

scholarly journals Green's function method for the single-particle resonances in a deformed Dirac equation

2020 ◽  
Vol 101 (1) ◽  
Author(s):  
T.-T. Sun ◽  
L. Qian ◽  
C. Chen ◽  
P. Ring ◽  
Z. P. Li
Keyword(s):  
Dirac Equation ◽  
Green’S Function ◽  
Green's Function ◽  
Single Particle ◽  
Function Method ◽  
Green’S Function Method

Green's function for the Dirac equation with nonsingular central potential and complex energy. Estimation algorithm

1990 ◽  
Vol 33 (8) ◽  
pp. 653-660
Author(s):  
L. N. Ivanov ◽  
E. P. Ivanova ◽  
G. G. Zaridze
Keyword(s):  
Dirac Equation ◽  
Green’S Function ◽  
Green's Function ◽  
Estimation Algorithm ◽  
Complex Energy ◽  
Energy Estimation ◽  
Central Potential

Green's function method in quantum chemistry: New numerical algorithm for the Dirac equation with complex energy and Fermi-model nuclear potential

2009 ◽  
Vol 109 (8) ◽  
pp. 1717-1727 ◽  
Author(s):  
A. V. Glushkov ◽  
S. V. Malinovskaya ◽  
O. Yu. Khetselius ◽  
A. V. Loboda ◽  
D. E. Sukharev ◽  
...  
Keyword(s):  
Dirac Equation ◽  
Quantum Chemistry ◽  
Green’S Function ◽  
Green's Function ◽  
Numerical Algorithm ◽  
Function Method ◽  
Nuclear Potential ◽  
Complex Energy ◽  
Green’S Function Method ◽  
Fermi Model

Green’s Function of the Dirac Equation with Complex Energy and Non-singular Central Nuclear Potential

2010 ◽  
Author(s):  
A. A. Svinarenko ◽  
A. V. Glushkov ◽  
A. V. Loboda ◽  
D. E. Sukharev ◽  
Yu. V. Dubrovskaya ◽  
...  
Keyword(s):  
Dirac Equation ◽  
Green’S Function ◽  
Green's Function ◽  
Nuclear Potential ◽  
Complex Energy

scholarly journals On the Green's function emergence from interferometry of seismic wave fields generated in high-melt glaciers: implications for passive imaging and monitoring

2020 ◽  
Vol 14 (3) ◽  
pp. 1139-1171 ◽  
Author(s):  
Amandine Sergeant ◽  
Małgorzata Chmiel ◽  
Fabian Lindner ◽  
Fabian Walter ◽  
Philippe Roux ◽  
...  
Keyword(s):  
Green’S Function ◽  
Wave Field ◽  
Green's Function ◽  
Seismic Wave ◽  
Ambient Noise ◽  
Cross Correlation ◽  
Noise Sources ◽  
Wave Fields ◽  
Seismic Scattering ◽  
The Cross

Abstract. Ambient noise seismology has revolutionized seismic characterization of the Earth's crust from local to global scales. The estimate of Green's function (GF) between two receivers, representing the impulse response of elastic media, can be reconstructed via cross-correlation of the ambient noise seismograms. A homogenized wave field illuminating the propagation medium in all directions is a prerequisite for obtaining an accurate GF. For seismic data recorded on glaciers, this condition imposes strong limitations on GF convergence because of minimal seismic scattering in homogeneous ice and limitations in network coverage. We address this difficulty by investigating three patterns of seismic wave fields: a favorable distribution of icequakes and noise sources recorded on a dense array of 98 sensors on Glacier d'Argentière (France), a dominant noise source constituted by a moulin within a smaller seismic array on the Greenland Ice Sheet, and crevasse-generated scattering at Gornergletscher (Switzerland). In Glacier d'Argentière, surface melt routing through englacial channels produces turbulent water flow, creating sustained ambient seismic sources and thus favorable conditions for GF estimates. Analysis of the cross-correlation functions reveals non-equally distributed noise sources outside and within the recording network. The dense sampling of sensors allows for spatial averaging and accurate GF estimates when stacked on lines of receivers. The averaged GFs contain high-frequency (>30 Hz) direct and refracted P waves in addition to the fundamental mode of dispersive Rayleigh waves above 1 Hz. From seismic velocity measurements, we invert bed properties and depth profiles and map seismic anisotropy, which is likely introduced by crevassing. In Greenland, we employ an advanced preprocessing scheme which includes match-field processing and eigenspectral equalization of the cross spectra to remove the moulin source signature and reduce the effect of inhomogeneous wave fields on the GFs. At Gornergletscher, cross-correlations of icequake coda waves show evidence for homogenized incident directions of the scattered wave field. Optimization of coda correlation windows via a Bayesian inversion based on the GF cross coherency and symmetry further promotes the GF estimate convergence. This study presents new processing schemes on suitable array geometries for passive seismic imaging and monitoring of glaciers and ice sheets.

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