Machine-learned electron correlation model based on frozen core approximation

2020 ◽  
Vol 153 (18) ◽  
pp. 184108
Author(s):  
Yasuhiro Ikabata ◽  
Ryo Fujisawa ◽  
Junji Seino ◽  
Takeshi Yoshikawa ◽  
Hiromi Nakai
Keyword(s):  
Electron Correlation ◽  
Correlation Model ◽  
Model Based ◽  
Core Approximation

Machine-learned electron correlation model based on correlation energy density at complete basis set limit

2019 ◽  
Vol 151 (2) ◽  
pp. 024104 ◽  
Author(s):  
Takuro Nudejima ◽  
Yasuhiro Ikabata ◽  
Junji Seino ◽  
Takeshi Yoshikawa ◽  
Hiromi Nakai
Keyword(s):  
Energy Density ◽  
Electron Correlation ◽  
Correlation Energy ◽  
Basis Set ◽  
Correlation Model ◽  
Model Based ◽  
Complete Basis ◽  
Complete Basis Set ◽  
Complete Basis Set Limit

Spatial Correlation Interpretation of Effects of As+ Implantation on the Raman Spectra of GaAs

1983 ◽  
Vol 27 ◽  
Author(s):  
D.E. Aspnes ◽  
K.K. Tiong ◽  
P.M. Amirtharaj ◽  
F.H. Pollak
Keyword(s):  
Spatial Correlation ◽  
Raman Spectra ◽  
Selection Rule ◽  
Phonon Mode ◽  
Red Shift ◽  
Correlation Model ◽  
Model Based ◽  
Ion Implanted

ABSTRACTThe red shift and asymmetric broadening of the LO phonon mode of ion-implanted GaAs are both described quantitatively by a spatial correlation model based on a damage-induced relaxation of the momentum selection rule previously used by Richter, Wang, and Ley to describe similar effects in microcrystalline Si. The success of the model for a qualitatively different disorder microstructure suggests it may be possible to evaluate average sizes of crystallographically perfect regions in semiconductors from the phonon lineshapes of their Raman spectra.

A New Spatial Correlation Model Based on the Distributed RC-∏ Model

2014 ◽  
Vol 989-994 ◽  
pp. 2204-2207
Author(s):  
Xiao Xiao Liu ◽  
Jing Bo Shao ◽  
Ling Ling Zhao
Keyword(s):  
Gaussian Process ◽  
Spatial Correlation ◽  
Process Variations ◽  
Deep Submicron ◽  
Correlation Model ◽  
Crosstalk Noise ◽  
Model Based ◽  
Reduction Techniques ◽  
Non Gaussian ◽  
Tree Branch

To solve the crosstalk noise question in deep-submicron technologies, a new spatial correlation model based on the distributed RC-π model is proposed in this paper. Quiet aggressor net and tree branch reduction techniques are introduced to the distributed RC-π model, and a new spatial correlation model of both Gaussian and non-Gaussian process variations among segments is created. Experimental results show that our method maintains the efficiency of past approaches, and significantly improves on their accuracy.

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