Experimental Study of Energy-Level Statistics in a Regime of Regular Classical Motion

1989 ◽  
Vol 62 (8) ◽  
pp. 893-896 ◽  
Author(s):  
George R. Welch ◽  
Michael M. Kash ◽  
Chun-ho Iu ◽  
Long Hsu ◽  
Daniel Kleppner
Keyword(s):  
Experimental Study ◽  
Energy Level ◽  
Classical Motion ◽  
Level Statistics

Arithmetical chaos and violation of universality in energy level statistics

1992 ◽  
Vol 69 (15) ◽  
pp. 2188-2191 ◽  
Author(s):  
J. Bolte ◽  
G. Steil ◽  
F. Steiner
Keyword(s):  
Energy Level ◽  
Level Statistics

scholarly journals Energy-level statistics and localization of 2d electrons in random magnetic fields

1998 ◽  
Vol 249-251 ◽  
pp. 792-795 ◽  
Author(s):  
M. Batsch ◽  
L. Schweitzer ◽  
B. Kramer
Keyword(s):  
Magnetic Fields ◽  
Energy Level ◽  
Level Statistics

Effects of bifurcations on the energy level statistics for oval billiards

1999 ◽  
Vol 59 (4) ◽  
pp. 4026-4035 ◽  
Author(s):  
H. Makino ◽  
T. Harayama ◽  
Y. Aizawa
Keyword(s):  
Energy Level ◽  
Level Statistics

scholarly journals GAP PROBABILITY OF A ONE-DIMENSIONAL GAS MODEL

1996 ◽  
Vol 10 (16) ◽  
pp. 1989-1997
Author(s):  
Y. CHEN ◽  
S.M. MANNING
Keyword(s):  
Energy Level ◽  
Thermodynamic Limit ◽  
Gap Formation ◽  
Mobility Edge ◽  
One Dimensional ◽  
Disordered Solids ◽  
Formation Probability ◽  
Level Statistics ◽  
Correct Form ◽  
Gap Probability

We investigate the gap formation probability of the effective one-dimensional gas model recently proposed for the energy level statistics for disordered solids at the mobility edge. It is found that in order to get the correct form for the gap probability of this model, the thermodynamic limit must be taken very carefully.

USING STRATEGY IMPROVEMENT TO STAY ALIVE

2012 ◽  
Vol 23 (03) ◽  
pp. 585-608 ◽  
Author(s):  
LUBOŠ BRIM ◽  
JAKUB CHALOUPKA
Keyword(s):  
Experimental Study ◽  
Energy Level ◽  
Initial Energy ◽  
Minimum Amount ◽  
Usual Sense ◽  
Mean Payoff Games ◽  
Mean Payoff ◽  
Novel Algorithm

We design a novel algorithm for solving Mean-Payoff Games (MPGs). Besides solving an MPG in the usual sense, our algorithm computes more information about the game, information that is important with respect to applications. The weights of the edges of an MPG can be thought of as a gained/consumed energy – depending on the sign. For each vertex, our algorithm computes the minimum amount of initial energy that is sufficient for player Max to ensure that in a play starting from the vertex, the energy level never goes below zero. Our algorithm is not the first algorithm that computes the minimum sufficient initial energies, but according to our experimental study it is the fastest algorithm that computes them. The reason is that it utilizes the strategy improvement technique which is very efficient in practice.

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