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PERCOLATION AND DISORDERED SYSTEMS Geoffrey GRIMMETT

PERCOLATION AND DISORDERED SYSTEMS Geoffrey GRIMMETT

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Percolation and Disordered Systems 265<br />

Henceforth we assume that q ≥ 1. Turning to the question of phase transition,<br />

and remembering percolation, we define the percolation probabilities<br />

(13.8) θ b (p, q) = φ b p,q(0 ↔ ∞), b = 0, 1,<br />

i.e., the probability that 0 belongs to an infinite open cluster. The corresponding<br />

critical probabilities are given by<br />

p b c (q) = sup{p : θb (p, q) = 0}, b = 0, 1.<br />

Faced possibly with two (or more) distinct critical probabilities, we present<br />

the following result, abstracted from [16, 158, 159, 162].<br />

Theorem 13.9. Assume that d ≥ 2 and q ≥ 1. There exists a countable<br />

subset P = Pq,d of [0, 1], possibly empty, such that φ 0 p,q = φ 1 p,q if either<br />

θ 1 (p, q) = 0 or p /∈ P.<br />

Consequently, θ0 (p, q) = θ1 (p, q) if p does not belong to the countable set<br />

Pq,d, whence p0 c (q) = p1c (q). Henceforth we refer to the critical value as pc(q).<br />

It is believed that Pq,d = ∅ for small q (depending on the value of d), and<br />

that Pq,d = {pc(q)} for large q; see the next section.<br />

Next we prove the non-triviality of pc(q) for q ≥ 1 (see [16]).<br />

Theorem 13.10. If d ≥ 2 and q ≥ 1 then 0 < pc(q) < 1.<br />

Proof. We compare the case of general q with the case q = 1 (percolation).<br />

Using the comparison inequalities (Theorem 13.2), we find that<br />

(13.11) pc(1) ≤ pc(q) ≤<br />

qpc(1)<br />

, q ≥ 1,<br />

1 + (q − 1)pc(1)<br />

where pc(1) is the critical probability of bond percolation on L d . Cf. Theorem<br />

3.2. �<br />

We note that pc(q) is monotone non-decreasing in q, by use of the comparison<br />

inequalities. Actually it is strictly monotone and Lipschitz continuous<br />

(see [161]).<br />

Finally we return to the Potts model, and we review the correspondence<br />

of phase transitions. The relevant ‘order parameter’ of the Potts model is<br />

given by<br />

M(βJ, q) = lim<br />

Λ→Zd �<br />

π 1 � � −1<br />

Λ,β,J σ(0) = 1 − q �<br />

,<br />

where π1 Λ,β,J is a Potts measure on Λ ‘with boundary condition 1’. We may<br />

think of M(βJ, q) as a measure of the degree to which the boundary condition<br />

‘1’ is noticed at the origin. By an application of Theorem 12.8 to a suitable<br />

graph obtained from Λ, we have that<br />

π 1 � � −1 −1 1<br />

Λ,β,J σ(0) = 1 − q = (1 − q )φΛ,p,q (0 ↔ ∂Λ)

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