scholarly journals Finite-range effects in Efimov physics beyond the separable approximation

2019 ◽  
Vol 99 (1) ◽  
Author(s):  
P. M. A. Mestrom ◽  
T. Secker ◽  
R. M. Kroeze ◽  
S. J. J. M. F. Kokkelmans
2009 ◽  
Vol 80 (1) ◽  
Author(s):  
M. Thøgersen ◽  
D. V. Fedorov ◽  
A. S. Jensen ◽  
B. D. Esry ◽  
Yujun Wang
Keyword(s):  

2015 ◽  
Vol 56 (11-12) ◽  
pp. 881-887
Author(s):  
M. Gattobigio ◽  
A. Kievsky

2021 ◽  
Vol 103 (6) ◽  
Author(s):  
C. Gonzalez-Boquera ◽  
M. Centelles ◽  
X. Viñas ◽  
L. M. Robledo
Keyword(s):  

2021 ◽  
Vol 7 (1) ◽  
Author(s):  
Chih-Chuen Lin ◽  
Phani Motamarri ◽  
Vikram Gavini

AbstractWe present a tensor-structured algorithm for efficient large-scale density functional theory (DFT) calculations by constructing a Tucker tensor basis that is adapted to the Kohn–Sham Hamiltonian and localized in real-space. The proposed approach uses an additive separable approximation to the Kohn–Sham Hamiltonian and an L1 localization technique to generate the 1-D localized functions that constitute the Tucker tensor basis. Numerical results show that the resulting Tucker tensor basis exhibits exponential convergence in the ground-state energy with increasing Tucker rank. Further, the proposed tensor-structured algorithm demonstrated sub-quadratic scaling with system-size for both systems with and without a gap, and involving many thousands of atoms. This reduced-order scaling has also resulted in the proposed approach outperforming plane-wave DFT implementation for systems beyond 2000 electrons.


1996 ◽  
Vol 28 (2) ◽  
pp. 346-355 ◽  
Author(s):  
A. J. Baddeley ◽  
M. N. M. Van Lieshout ◽  
J. Møller

We show that a Poisson cluster point process is a nearest-neighbour Markov point process [2] if the clusters have uniformly bounded diameter. It is typically not a finite-range Markov point process in the sense of Ripley and Kelly [12]. Furthermore, when the parent Poisson process is replaced by a Markov or nearest-neighbour Markov point process, the resulting cluster process is also nearest-neighbour Markov, provided all clusters are non-empty. In particular, the nearest-neighbour Markov property is preserved when points of the process are independently randomly translated, but not when they are randomly thinned.


2000 ◽  
Vol 33 (50) ◽  
pp. L497-L502
Author(s):  
L B Ioffe ◽  
D Sherrington
Keyword(s):  

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