Metastable states of an asymmetric spin-glass with one stored pattern

1994 ◽  
Vol 94 (1-2) ◽  
pp. 187-193
Author(s):  
U. Geppert ◽  
M. Schreckenberg ◽  
J. Zittartz
Keyword(s):  
Spin Glass ◽  
Metastable States

scholarly journals Dynamics within metastable states in a mean-field spin glass

1996 ◽  
Vol 29 (5) ◽  
pp. L81-L87 ◽  
Author(s):  
A Barrat ◽  
R Burioni ◽  
M Mézard
Keyword(s):  
Spin Glass ◽  
Mean Field ◽  
Metastable States

The Number of Metastable States in Potts Spin Glass with p = 3

1992 ◽  
Vol 17 (2) ◽  
pp. 109-112 ◽  
Author(s):  
E. A Lutchinskaia ◽  
E. E Tareyeva
Keyword(s):  
Spin Glass ◽  
Metastable States

scholarly journals Stochastic tunneling across fitness valleys can give rise to a logarithmic long-term fitness trajectory

2019 ◽  
Vol 5 (7) ◽  
pp. eaav3842 ◽  
Author(s):  
Yipei Guo ◽  
Marija Vucelja ◽  
Ariel Amir
Keyword(s):  
Spin Glass ◽  
Fitness Landscape ◽  
Fitness Function ◽  
Metastable States ◽  
Hill Climbing ◽  
Type Model ◽  
Logarithmic Average ◽  
Glass Type ◽  
Average Fitness

Adaptation, where a population evolves increasing fitness in a fixed environment, is typically thought of as a hill-climbing process on a fitness landscape. With a finite genome, such a process eventually leads the population to a fitness peak, at which point fitness can no longer increase through individual beneficial mutations. Instead, the ruggedness of typical landscapes due to epistasis between genes or DNA sites suggests that the accumulation of multiple mutations (via a process known as stochastic tunneling) can allow a population to continue increasing in fitness. However, it is not clear how such a phenomenon would affect long-term fitness evolution. By using a spin-glass type model for the fitness function that takes into account microscopic epistasis, we find that hopping between metastable states can mechanistically and robustly give rise to a slow, logarithmic average fitness trajectory.

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