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PropositionStatement: AI-generatedProof: AI-generated
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Extremal degrees at a fixed logarithmic mean

Statement

Fix γ>1 and let p=γlog⁡n/n. For all sufficiently large integers n, let G(n,p) be the random simple graph on [n]={1,…,n} whose distinct possible edges occur independently with probability p. Write d(v) for the number of edges incident to v, and let dmin⁡=min⁡vd(v) and dmax⁡=max⁡vd(v). Let I(a)=alog⁡a−a+1 for a>0, and let a−∈(0,1) and a+>1 be the unique solutions of γI(a)=1. Then dmin⁡/(pn)→a− and dmax⁡/(pn)→a+ in probability as n→∞: for each ε>0, the probability that either normalized degree differs from its stated limit by more than ε tends to zero.

Facts & Assumptions

[F1]

In G(n,p) the edge indicators are independent Bernoulli variables. Each degree has law Bin⁡(n−1,p); for distinct u,v, d(u)=Auv+Ru and d(v)=Auv+Rv, where Auv,Ru,Rv are independent, Auv is Bernoulli(p) and each residual degree is Bin⁡(n−2,p) (The Erdős-Rényi finite random graph G(n,p), Single-vertex degree laws and the shared-edge dependence).

[F2]

For X∼Bin⁡(N,p), P(X=k)=(Nk)pk(1−p)N−k for 0≤k≤N. In particular the probability envelope in Elementary binomial probability envelopes applies; the exact mass formula also permits adjacent masses to be compared (The Binomial count has its usual probability mass function).

[F3]

Stirling's formula is k!∼2πk(k/e)k as k→∞ (Stirling's formula for factorials).

[F4]

I is strictly decreasing on (0,1) and strictly increasing on (1,∞), with the two stated roots for γ>1 (Entropy rates, inverse branches and shifted root contracts).

[F5]

For a finite real random variable Y and t>0, P(∣Y−EY∣≥t)≤Var⁡(Y)/t2; variance expands as the sum of pairwise covariances (Chebyshev's inequality on a finite probability space, Variance and covariance identities for random variables).

[F6]

The logarithm has derivative 1/x on (0,∞) (The natural logarithm has derivative 1/x and equals the integral from 1 to x of 1/t). For positive x,y, log⁡(xy)=log⁡x+log⁡y and log⁡(x/y)=log⁡x−log⁡y (Order, continuity, range, and the product, quotient, and reciprocal laws for the natural logarithm).

[F7]

For any finite family of events E1,…,Em in one probability space, P(⋃i=1mEi)≤∑i=1mP(Ei) (The finite union bound).

Proof

Given: The graph sequence and fixed γ>1 in the Statement. Put μ=np=γlog⁡n.

Goal: Prove convergence in probability of both extreme degrees to the stated roots.

1.1F2F3F6algebra

Fix a>0, let k=⌊aμ⌋, and let N=n−1 or n−2. For sufficiently large n, 1≤k<N. By [F2] and the logarithm laws in [F6], the logarithm of the mass at k is ∑j=0k−1log⁡(N−j)+klog⁡p−log⁡(k!)+(N−k)log⁡(1−p). Since k=O(log⁡n), [F6] gives ∑j=0k−1log⁡(N−j)=klog⁡N+O(k2/N) and (N−k)log⁡(1−p)=−Np+O(kp+Np2). By [F3], log⁡(k!)=klog⁡k−k+O(log⁡k). Thus the log mass is −μI(a)+o(log⁡n), because Np=μ+o(1) and k/μ→a. Consequently this mass is n−γI(a)+o(1). The same conclusion holds if k is changed by a bounded integer amount.

2.1F1F2F4F7step 1.1algebra

For X∼Bin⁡(n−1,p), [F2] gives P(X=j−1)/P(X=j)=j(1−p)/((n−j)p) for 1≤j≤n−1. If 0<a<1, this ratio is at most a fixed ρ<1 for all j≤⌊aμ⌋ and all sufficiently large n. If a>1, the reciprocal ratio P(X=j+1)/P(X=j) is at most a fixed ρ<1 for all j≥⌊aμ⌋ with j<n−1. Summing the corresponding finite geometric bounds and using step 1.1 shows that each respective lower or upper tail is at most n−γI(a)+o(1). If a<a− or a>a+, [F4] makes γI(a)>1; the union bound [F7] over the n vertices then makes the probability of a degree in that respective tail tend to zero.

2.2F1F2F5step 1.1algebra

Fix a>0 with γI(a)<1, and set k=⌊aμ⌋. Let Z count vertices of degree exactly k, and write q=P(d(v)=k). By step 1.1, EZ=nq=n1−γI(a)+o(1)→∞. For distinct u,v, let bj=P(Ru=j) and put r=bk−1/bk. The mass formula gives r=k(1−p)/((n−1−k)p)→a. By the independent shared-edge decomposition in [F1], q=bk((1−p)+pr) and P(d(u)=k,d(v)=k)=bk2((1−p)+pr2). Hence the ratio of this joint probability to q2 is 1+p(1−p)(r−1)2/((1−p)+pr)2=1+O(p)=1+o(1). Expanding the variance using [F5] yields Var⁡(Z)/(EZ)2≤1/(nq)+o(1)→0. Chebyshev's inequality therefore gives P(Z=0)→0.

3.1F4F7step 2.1step 2.2algebra∎

Given ε>0, choose b−,c−,b+,c+ with 0<b−<a−<c−<1<c+<a+<b+, all within ε of their respective roots. By [F4], the outer choices have γI>1 and the inner choices have γI<1. Step 2.1 excludes degrees at or below ⌊b−μ⌋ and at or above ⌊b+μ⌋ with probability tending to one. Step 2.2 supplies vertices of degrees ⌊c−μ⌋ and ⌊c+μ⌋ with probability tending to one. Since μ→∞, the floor errors divided by μ vanish. By [F7], these four bounds hold simultaneously with probability tending to one and bracket dmin⁡/μ and dmax⁡/μ within ε of their respective roots with probability tending to one, proving both asserted convergences.

Depends on

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