In this problem you will use the mean field approximation to analyse the behaviour of the Ising model near the critical point.

(a) Prove that, when x1,tanhxx-13x3

(b) Use the result of part (a) to find an expression for the magnetisation of the Ising model, in the mean field approximation, when T is very close to the critical temperature. You should find MTc-Tβ¯,whereβ(not to be confused with 1/kT) is a critical exponent, analogous to the f defined for a fluid in Problem 5.55. Onsager's exact solution shows that β=1/8in two dimensions, while experiments and more sophisticated approximations show that β1/3in three dimensions. The mean field approximation, however, predicts a larger value.

(c) The magnetic susceptibility χis defined as χ(M/B)T. The behaviour of this quantity near the critical point is conventionally written as χT-Tc-γ , where y is another critical exponent. Find the value of in the mean field approximation, and show that it does not depend on whether T is slightly above or slightly below Te. (The exact value of y in two dimensions turns out to be 7/4, while in three dimensions γ1.24.)

Short Answer

Expert verified

Hence proved that when x1,tanhxx-13x3

b)β=0.5c)γ=1

Step by step solution

01

Given information

In this problem we will use the mean field approximation to analyse the behaviour of the Ising model near the critical point.

02

Explanation

a) The function tanh x has the following definition:

tanhx=e2x-1e2x+1ex1+x+x22+x36+tanhx1+2x+(2x)22+(2x)36-11+2x+12x+(2x)22+(2x)362+2xx+2x22+4x361+x;(1+x)-11-xx+x2+2x33(1-x)=x-x2+x2-x3+2x33=x-x33

(b)This expression will now be used to expand relation 8.50:

role="math" s¯=tanh(βϵns¯)Tc=nϵk,β=1kT,βnϵ=TcTTcT·s¯-s¯Tc/T33s¯=TcT·s¯1-Tc/T23·s¯2TTc=1-Tc/T23·s¯2Tc23T2·s¯2=1-TTcTc23T2·s¯2=1-TTc/·3T2Tc2s¯2=3·T2Tc2·1-TTcs¯=3·T2Tc21-TTc,TTc-=3·T2Tc2Tc-TTc,t=T-TcTc=-3t(1+t)2,|t|<<1,(1+t)21+2r-3t(1+2t)-3t=-3T-TcTcs¯~Tc-Tβ=0.5

We may conclude that the same critical exponent applies to magnetisation because it is proportional to s.

03

Explanation

(c) To calculate susceptibility, we must differentiate the non-approximate formula for sin relation to B, which we shall manually insert:

s¯=tanh(β(ϵns¯+B))/ddBχ=β(1+ϵnχcosh2[β(ϵns¯+B)]

We can get χby setting B = 0 and rearranging terms:

χ=β(1+ϵnχ)cosh2[βϵns¯]χ=βcosh2[βϵns¯]-βϵnβϵn=TcTs¯(3|t|)0.5forTTc-cosh(x)1+x22cosh2TcTs¯1+Tc/T2·3|t|221+3Tc2T2|t|χβ1+3Tc2T2|t|-TcT1+3Tc2T2|t|-TcT=3Tc2T2|t|+1-TcT=3Tc2T2|t|-|t|=|t|3Tc2T2-1=|t|·3Tc2-T2T2χβ|t|·3Tc2-T2T21kBT·T2|t|·3Tc2-T21kB·T|t|·3Tc2-T2TTc1kB·Tc|t|·2Tc2χ12kB·1|t|TcχT-Tc-1γ=1

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Most popular questions from this chapter

In this section I've formulated the cluster expansion for a gas with a fixed number of particles, using the "canonical" formalism of Chapter 6. A somewhat cleaner approach, however, is to use the "grand canonical" formalism introduced in Section 7.1, in which we allow the system to exchange particles with a much larger reservoir.

(a) Write down a formula for the grand partition function (Z) of a weakly interacting gas in thermal and diffusive equilibrium with a reservoir at fixed T andµ. Express Z as a sum over all possible particle numbers N, with each term involving the ordinary partition function Z(N).

(b) Use equations 8.6 and 8.20 to express Z(N) as a sum of diagrams, then carry out the sum over N, diagram by diagram. Express the result as a sum of similar diagrams, but with a new rule 1 that associates the expression (>./vQ) J d3ri with each dot, where >. = e13µ,. Now, with the awkward factors of N(N - 1) · · · taken care of, you should find that the sum of all diagrams organizes itself into exponential form, resulting in the formula

Note that the exponent contains all connected diagrams, including those that can be disconnected by removal of a single line.

(c) Using the properties of the grand partition function (see Problem 7.7), find diagrammatic expressions for the average number of particles and the pressure of this gas.

(d) Keeping only the first diagram in each sum, express N(µ) and P(µ) in terms of an integral of the Mayer /-function. Eliminate µ to obtain the same result for the pressure (and the second virial coefficient) as derived in the text.

(e) Repeat part (d) keeping the three-dot diagrams as well, to obtain an expression for the third virial coefficient in terms of an integral of /-functions. You should find that the A-shaped diagram cancels, leaving only the triangle diagram to contribute to C(T).

Use a computer to plot s¯ as a function of kT/ε, as predicted by mean field theory, for a two-dimensional Ising model (with a square lattice).

Modify the ising program to compute the average energy of the system over all iterations. To do this, first add code to the initialise subroutine compute the initial energy of the lattice; then, whenever a dipole is flipped, change the energy variable by the appropriate amount. When computing the average energy, be sure to average over all iterations, not just those iterations in which a dipole is actually flipped (why?). Run the program for a 5 x 5 lattice for T values from 4 down to l in reasonably small intervals, then plot the average energy as a function of T. Also plot the heat capacity. Use at least 1000 iterations per dipole for each run, preferably more. If your computer is fast enough, repeat for a 10x 10 lattice and for a 20 x 20 lattice. Discuss the results. (Hint: Rather than starting over at each temperature with a random initial state, you can save time by starting with the final state generated at the previous, nearby temperature. For the larger lattices you may wish to save time by considering only a smaller temperature interval, perhaps from 3 down to 1.5.)

Implement the ising program on your favourite computer, using your favourite programming language. Run it for various lattice sizes and temperatures and observe the results. In particular:

(a) Run the program with a 20 x 20 lattice at T = 10, 5, 4, 3, and 2.5, for at least 100 iterations per dipole per run. At each temperature make a rough estimate of the size of the largest clusters.

(b) Repeat part (a) for a 40 x 40 lattice. Are the cluster sizes any different? Explain. (c) Run the program with a 20 x 20 lattice at T = 2, 1.5, and 1. Estimate the average magnetisation (as a percentage of total saturation) at each of these temperatures. Disregard runs in which the system gets stuck in a metastable state with two domains.

(d) Run the program with a 10x 10 lattice at T = 2.5. Watch it run for 100,000 iterations or so. Describe and explain the behaviour.

(e) Use successively larger lattices to estimate the typical cluster size at temperatures from 2.5 down to 2.27 (the critical temperature). The closer you are to the critical temperature, the larger a lattice you'll need and the longer the program will have to run. Quit when you realise that there are better ways to spend your time. Is it plausible that the cluster size goes to infinity as the temperature approaches the critical temperature?

Consider an Ising model of 100 elementary dipoles. Suppose you wish to calculate the partition function for this system, using a computer that can compute one billion terms of the partition function per second. How long must you wait for the answer?

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