Ising Model. Ising Lattice. E. J. Maginn, J. K. Shah

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Ising Lattice E. J. Maginn, J. K. Shah Department of Chemical and Biomolecular Engineering University of Notre Dame Notre Dame, IN 46556 USA Monte Carlo Workshop, Brazil

Ising Lattice Model Consider a 2-D lattice of spins up or down

Ising Lattice Model We replicate in all directions to add periodic boundary conditions

Ising Lattice Model Consider a system of N spins on a lattice. In the presence of an external magnetic field, H, the energy of a particular state ν is E ν = N i=1 Hs i J ij s i s j (1) First term: energy due to individual spins coupling with external field Second term: energy due to interactions between spins. Assume that only nearest neighbors interact J is coupling constant, and describes the interaction energy between pairs. When J > 0, it is energetically favorable for neighboring pairs to be aligned.

Ising Lattice Model If J is large enough (or temperature low enough), the tendency for neighboring spins to align will cause a cooperative phenomena called spontaneous magnetization. Physically: caused by interactions among nearest neighbors propagating throughout the system A given magnetic moment influences alignment of spins separated by a large distance Such long range correlations associated with long range order; lattice can have net magnetization in the absence of external magnetic field. Magnetization defined as < M >= N s i (2) A non zero < M > when H = 0 is called spontaneous magnetization (c) 2011 University of Notre Dame i=1

Ising Lattice Model Temperature where system exhibits spontaneous magnetization is the Curie temperature (or critical temperature), T c T c is the highest temperature for which there can be a non zero magnetization in the absence of an external magnetic field For T c > 0, Ising model undergoes an order disorder transition Similar to a phase transition in a fluid system - simple model of a fluid No order-disorder transition in 1-D only 2-D and 3-D

Ising Lattice Model 1-D Ising model solved analytically by Ernst Ising in his 1924 PhD thesis Historical note: German Jew who fled Europe, ending up in Peoria, IL as physics teacher at Bradley University Never published again after WWII Died in 1998 - see obituary: http://www.bradley.edu/las/phy/personnel/isingobit.html

Ising Lattice Model Lars Onsager showed in the 1940s that for H = 0, the partition function for a two dimensional Ising Lattice is Q(N,β,0) =[2 cosh(βj)e I ] N (3) where π I =(2π) 1 dφ ln( 1 2 [1 +(1 κ2 sin 2 φ) 1/2 ]) 0 with κ = 2 sinh(2βj)/cosh 2 (2βJ) This result was one of the major achievements of modern statistical mechanics

Ising Lattice Model It can be shown that T c = 2.269J/k B (4) Furthermore, for T < T c, the magnetization scales as M N α(t c T ) λ (5) Should be possible to perform Metropolis simulation of this!

Properties of Ising Lattice Physically, Ising lattice shows many of the characteristics of a fluid Magnetic susceptibility, χ =(< M 2 > < M > 2 )/k B T, diverges at critical point Local magnetization fluctuations become very large near critical point, similar to density fluctuations near critical point of a fluid Small variations in k B T /J lead to spontaneous phase changes

Properties of Ising Lattice The correlation length (distance over which local fluctuations are correlated) is unbounded at T c As T approaches T, correlation length increases c Figure: T c is being approached from left to right. The correlation length of like regions (i.e. black and white squares) increases. At T c, an order disorder transition occurs, analogous to condensation

Ising Lattice Algorithm How to simulate the 2-D Ising lattice? 1. Choose an initial state of spins (it will not matter) 2. Choose a site i 3. Calculate the change in energy E if the state if i is changed 4. If energy is lowered by change, accept the change. If not... 5. Generate random number 0 <ζ<1 6. If ζ<exp( β E) accept the change. Otherwise, don t 7. Repeat Compute < M >, < E > and fluctuations versus T. Let s do it!

Ising interactive Algorithm Take a look at the source code ising2d.f Lattice array or 0 or 1: latt(ix,iy) Largest allowable lattice size: 40 X 40 Initialize it in one of four choices Compute the initial energy CALL echeck

Ising interactive Algorithm Core Metropolis algorithm is in routine update do istep=1,nstep CALL update ccc sum E, M and fluctuations emean=emean+etot efluc=efluc+etot*etot rmmean=rmmean+dfloat(mtot) rmfluc=rmfluc+dfloat(mtot) *dfloat(mtot) enddo! istep = 1,nstep

Ising interactive Algorithm Metropolis implementation for an nsize X nsize lattice size=dfloat(nsize) nsize1=nsize-1 ccc Pick a spin at random. Each call to ccc update performs nsizeˆ2 attempts do iflip=1,nsize*nsize ccc (ix,iy) is a random position on lattice ix=int(size*uni())+1 iy=int(size*uni())+1 ccc nhsum is a counter that sums the value ccc of all spins adjacent to (ix,iy) nhsum=0

ccc ccc ccc get positions adjacent to (ix,iy) (remember PBC) do nhbr=1,4 nhx=mod(ix+nhxl(nhbr)+nsize1,nsize)+1 nhy=mod(iy+nhyl(nhbr)+nsize1,nsize)+1 nhsum=nhsum+latt(nhx,nhy) enddo compute energy felt by spin at (ix,iy) itest=nhsum*latt(ix,iy)

Here is the Metropolis algorithm if (itest.le.0) then ccc Automatically accept the move ccc Sum total energy and magnetization mtot=mtot-2*latt(ix,iy) latt(ix,iy)=-latt(ix,iy) else ccc Select a random number on (0,1) ccc Conditional accept (embe is precalculated E) if (test.le.embe(itest)) then etot=etot+dfloat(itest)*rj2 mtot=mtot-2*latt(ix,iy) latt(ix,iy)=-latt(ix,iy) end if ccc Reject the move. Keep everything the same end if

Ising interactive Run Ising interactive at T > T c. Note the value of the magnetization, fluctuations Dump the configuration and look at it. What do you see? Slowly reduce T and approach T c. What happens? Start at low T (T 0.4). What happens? Slowly raise T to approach T c = 2.26 What happens?

Ising batch input file ising.40.10k.log : name of log file 123456 : rdm nbr seed mvst.1 : magnetization vs T filename 75 : unit (don t change) evst.1 : energyvs T filename 76 : unit (don t change) mflucvst.1 : magnetiz fluc vs T filename 77 : unit (don t change) eflucvst.1 : energy fluc vs T filename 78 : unit (don t change) 1 : 1=random,2-inter,3=check,4=read 5000 : number of equilibration steps 2 : n different runs 40 10000 4 : nsize nstep kt/j for run 40 10000 2 : nsize nstep kt/j