scholarly journals On characterization of the sharp Strichartz inequality for the Schrödinger equation

2016 ◽  
Vol 9 (2) ◽  
pp. 353-361 ◽  
Author(s):  
Jin-Cheng Jiang ◽  
Shuanglin Shao
2014 ◽  
Vol 15 (2) ◽  
Author(s):  
Weslley Florentino de Oliveira ◽  
Giancarlo Queiroz Pellegrino

<em>Chaotic sequences are sequences generated by chaotic maps. A particle moving in a one-dimensional space has its behavior modeled according to the time-independent Schrödinger equation. The tight-binding approximation enables the use of chaotic sequences as the simulation of quantum potentials in the discretized version of the Schrödinger equation. The present work consists of the generation and characterization of spectral curves and eigenvectors of the Schrödinger operator with potentials generated by chaotic sequences, as  well as their comparison with the curves generated by periodic, peneperiodic and random sequences.</em> <em>This comparison is made by calculating in each case the inverse participation ratio as a function of the system size.</em>


2018 ◽  
Vol 370 (8) ◽  
pp. 5617-5633 ◽  
Author(s):  
Jonathan Bennett ◽  
Neal Bez ◽  
Taryn C. Flock ◽  
Susana Gutiérrez ◽  
Marina Iliopoulou

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Nicola Amoroso ◽  
Loredana Bellantuono ◽  
Saverio Pascazio ◽  
Angela Lombardi ◽  
Alfonso Monaco ◽  
...  

Abstract We propose a characterization of complex networks, based on the potential of an associated Schrödinger equation. The potential is designed so that the energy spectrum of the Schrödinger equation coincides with the graph spectrum of the normalized Laplacian. Crucial information is retained in the reconstructed potential, which provides a compact representation of the properties of the network structure. The median potential over several random network realizations, which we call ensemble potential, is fitted via a Landau-like function, and its length scale is found to diverge as the critical connection probability is approached from above. The ruggedness of the ensemble potential profile is quantified by using the Higuchi fractal dimension, which displays a maximum at the critical connection probability. This demonstrates that this technique can be successfully employed in the study of random networks, as an alternative indicator of the percolation phase transition. We apply the proposed approach to the investigation of real-world networks describing infrastructures (US power grid). Curiously, although no notion of phase transition can be given for such networks, the fractality of the ensemble potential displays signatures of criticality. We also show that standard techniques (such as the scaling features of the largest connected component) do not detect any signature or remnant of criticality.


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