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Extremal degrees at a fixed logarithmic mean
Statement
Fix and let . For all sufficiently large integers , let be the random simple graph on whose distinct possible edges occur independently with probability . Write for the number of edges incident to , and let and . Let for , and let and be the unique solutions of . Then and in probability as : for each , the probability that either normalized degree differs from its stated limit by more than tends to zero.
Facts & Assumptions
In the edge indicators are independent Bernoulli variables. Each degree has law ; for distinct , and , where are independent, is Bernoulli and each residual degree is (The Erdős-Rényi finite random graph G(n,p), Single-vertex degree laws and the shared-edge dependence).
For , for . 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).
Stirling's formula is as (Stirling's formula for factorials).
is strictly decreasing on and strictly increasing on , with the two stated roots for (Entropy rates, inverse branches and shifted root contracts).
For a finite real random variable and , ; variance expands as the sum of pairwise covariances (Chebyshev's inequality on a finite probability space, Variance and covariance identities for random variables).
The logarithm has derivative on (The natural logarithm has derivative 1/x and equals the integral from 1 to x of 1/t). For positive , and (Order, continuity, range, and the product, quotient, and reciprocal laws for the natural logarithm).
For any finite family of events in one probability space, (The finite union bound).
Proof
Given: The graph sequence and fixed in the Statement. Put .
Goal: Prove convergence in probability of both extreme degrees to the stated roots.
Fix , let , and let or . For sufficiently large , . By [F2] and the logarithm laws in [F6], the logarithm of the mass at is . Since , [F6] gives and . By [F3], . Thus the log mass is , because and . Consequently this mass is . The same conclusion holds if is changed by a bounded integer amount.
For , [F2] gives for . If , this ratio is at most a fixed for all and all sufficiently large . If , the reciprocal ratio is at most a fixed for all with . Summing the corresponding finite geometric bounds and using step 1.1 shows that each respective lower or upper tail is at most . If or , [F4] makes ; the union bound [F7] over the vertices then makes the probability of a degree in that respective tail tend to zero.
Fix with , and set . Let count vertices of degree exactly , and write . By step 1.1, . For distinct , let and put . The mass formula gives . By the independent shared-edge decomposition in [F1], and . Hence the ratio of this joint probability to is . Expanding the variance using [F5] yields . Chebyshev's inequality therefore gives .
Given , choose with , all within of their respective roots. By [F4], the outer choices have and the inner choices have . Step 2.1 excludes degrees at or below and at or above with probability tending to one. Step 2.2 supplies vertices of degrees and with probability tending to one. Since , the floor errors divided by vanish. By [F7], these four bounds hold simultaneously with probability tending to one and bracket and within of their respective roots with probability tending to one, proving both asserted convergences.
Depends on
- Single-vertex degree laws and the shared-edge dependence
- Entropy rates, inverse branches and shifted root contracts
- Elementary binomial probability envelopes
- The Erdős-Rényi finite random graph G(n,p)
- The Binomial count has its usual probability mass function
- Stirling's formula for factorials
- Chebyshev's inequality on a finite probability space
- Variance and covariance identities for random variables
- The natural logarithm has derivative 1/x and equals the integral from 1 to x of 1/t
- Order, continuity, range, and the product, quotient, and reciprocal laws for the natural logarithm
- The finite union bound
Dependency tree · 2 levels
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