Physics – Condensed Matter – Disordered Systems and Neural Networks
Scientific paper
2007-04-16
Physics
Condensed Matter
Disordered Systems and Neural Networks
8 pages, 8 figures, submitted to Phys. Rev. B; v2: shortened version
Scientific paper
10.1103/PhysRevB.76.174411
We study domain walls in 2d Ising spin glasses in terms of a minimum-weight path problem. Using this approach, large systems can be treated exactly. Our focus is on the fractal dimension $d_f$ of domain walls, which describes via $<\ell >\simL^{d_f}$ the growth of the average domain-wall length with %% systems size $L\times L$. %% 20.07.07 OM %% Exploring systems up to L=320 we yield $d_f=1.274(2)$ for the case of Gaussian disorder, i.e. a much higher accuracy compared to previous studies. For the case of bimodal disorder, where many equivalent domain walls exist due to the degeneracy of this model, we obtain a true lower bound $d_f=1.095(2)$ and a (lower) estimate $d_f=1.395(3)$ as upper bound. Furthermore, we study the distributions of the domain-wall lengths. Their scaling with system size can be described also only by the exponent $d_f$, i.e. the distributions are monofractal. Finally, we investigate the growth of the domain-wall width with system size (``roughness'') and find a linear behavior.
Hartmann Alexander K.
Melchert Oliver
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