Image:Ising-tartan.png

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[edit] Overview

This tartan-like graph shows the Ising model probability density P(σ) for the two-sided lattice using the dyadic mapping.

That is, a lattice configuration of length 2N

\sigma=(\sigma_{-N-1},\cdots,\sigma_{-2},\sigma_{-1},\sigma_{0},\sigma_{1},\sigma_{2},\cdots,\sigma_{N})

is understood to consist of a sequence of "spins" \sigma_k=\pm 1. This sequence may be represented by two real numbers 0\le x,y\le 1 with

x(\sigma)=\sum_{k=0}^{N}\left(\frac{\sigma_{k}+1}{2}\right)2^{-(k+1)}

and

y(\sigma)=\sum_{k=0}^{N}\left(\frac{\sigma_{-k-1}+1}{2}\right)2^{-(k+1)}

The energy of a given configuration σ is computed using the classical Hamiltonian,

H(\sigma)=\sum_{k=-N}^N V(\tau^k \sigma)

Here, τ is the shift operator, acting on the lattice by shifting all spins over by one position:

\tau(\cdots,\sigma_{0},\sigma_{1},\sigma_{2},\cdots) = 
(\cdots,\sigma_{-1},\sigma_{0},\sigma_{1},\cdots)

The interaction potential V is given by the Ising model interaction

V(σ) = Jσ0σ1 + Bσ0

Here, the constant J is the interaction strength between two neighboring spins σ0 and σ1, while the constant B may be interpreted as the strength of the interaction between the magnetic field and the magnetic moment of the spin.

The set of all possible configurations Ω = {σ} form a canonical ensemble, with each different configuration occurring with a probability P(σ) given by the Boltzmann distribution

P(\sigma)=\frac{1}{Z(T)} e^{-H(\sigma)/k_B T}

where kB is Boltzmann's constant, T is the temperature, and Z(T) is the partition function. The partition function is defined to be such that the sum over all probabilities adds up to one; that is, so that

Z(T)=\sum_{\sigma\in\Omega} e^{-H(\sigma)/k_B T}

[edit] Image details

The image here shows P(σ) = P(x,y) for the Ising model, with J = 0.3, B = 0 and temperature T = 1 / kB. The lattice is finite sized, with N = 10, so that all 1024\times 1024=2^N \times 2^N lattice configurations are represented, each configuration denoted by one pixel. The color choices here are such that black represents values where P(σ) = P(x,y) are zero, blue are small values, with yellow and red being progressively larger values.

[edit] As an invariant measure

This fractal tartan is invariant under the Baker's map. The shift operator τ on the lattice has an action on the unit square with the following representation:

\tau(x,y)=\left(\frac{x+\left\lfloor 2y\right\rfloor }{2}\,,\,2y-\left\lfloor 2y\right\rfloor \right)

This map (up to a reflection/rotation around the 45-degree axis) is essentially the Baker's map or equivalently the Horseshoe map. As the article on the Horseshoe map explains, the invariant sets have such a tartan pattern (an appropriately deformed Sierpinski carpet). In this case, the invariance arises from the translation invariance of the Gibbs states of the Ising model: that is, the energy H(σ) associated with the state σ is invariant under the action of τ:

H\left(\tau^k\sigma\right) = H(\sigma)

for all integers k. Similarly, the probability density is invariant as well:

P\left(\tau^k\sigma\right) = P(\sigma)

The naive classical treatment given here suffers from conceptual difficulties in the N\to\infty limit. These problems can be remedied by using a more appropriate topology on the set of states that make up the configuration space. This topology is the cylinder set topology, and using it allows one to construct a sigma algebra and thus a measure on the set of states. With this topology, the probability density can be understood to be a translation-invariant measure on the topology. Indeed, there is a certain sense in which the seemingly fractal patterns generated by the iterated Baker's map or horseshoe map can be understood with a conventional and well-behaved topology on a lattice model.

[edit] Licensing

Created by Linas Vepstas User:Linas on 24 September 2006

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current16:14, 24 September 20061,024×1,024 (5 KB)Linas (Talk | contribs) (Created by Linas Vepstas User:Linas on 24 September 2006)

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