Configuration integral mean-field

Fig. 21 Plots obtained by mean-field calculations for an EHFMI [24]. Calculations are performed for a two-dimensional 16x16 square lattice with open boundary conditions. Parameters used are U = St and t = —0.2t t denotes the second nearest neighbor transfer integrals tjk)- The number of doped holes is 8 half of them are centers of merons and the rest are centers of antimerons. (a) Plot for spin configuration. Centers of spin vortices are indicated as M for a meron (winding number -H spin vortex) and A for an antimeron (winding number —1 spin vortex), respectively, (b) Plot for current density j (short black arrows) and V x (long orange arrows). M and A here indicate centers of counterclockwise and clockwise loop currents, respectively (c) Plot for D(x), which connects j(x) and V/(x) as j(x) = D(x) V/(x) (d) Plot for 2j (thick orange line arrows are not attached but directions are the same as those of the black arrows) and 2Z)(x) V/(x) (black arrows)...

In Chapter 2, we saw that the configuration integral is the key quantity to be calculated if one seeks to compute thermal properties of classical (confined) fluids. However, it is immediately apparent that this is a formidable task because it reejuires a calculation of Z, which turns out to involve a 3N-dimensional integration of a horrendously complex integrand, namely the Boltzmann factor exp [-C7 (r ) /k T] [ see Eq. (2.112)]. To evaluate Z we either need additional simplifjfing assumptions (such as, for example, mean-field approximations to be introduced in Chapter 4) or numerical approaches [such as, for instance, Monte Carlo computer simulations (see Chapters 5 and 6), or integral-equation techniques (see Chapter 7)]. 

To focus on the mean field approach (see Sect. 2), the statistical weight of any configuration of the network may be expressed as a product of the contributions of the (restricted) network chains. Starting with (in our opinion) more natural models for restricted chains, a model with restricted junction fluctuations can be derived by integrating over the configuration space of the network chains. The constraints acting on the network chains are transformed in this way into a mean force potential acting on the junctions. This mean force potential is approximated within the model of restricted junction fluctuation by the domain accessible to each junction. 

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