Large gaps in sets of primes and other sequences I. Heuristics and basic constructions
Kevin Ford
University of Illinois at Urbana-Champaign
May, 2018 Large gaps between primes
th Def: G(x) = max(pn − pn−1), pn is the n prime. pn6x 2, 3, 5, 7,..., 109, 113, 127, 131,..., 9547, 9551, 9587, 9601,...
Upper bound: G(x) x0.525 (Baker-Harman-Pintz, 2001). Improve to O(x1/2+ε) on RH.
log2 x log4 x Lower bound: G(x) (log x) (F,Green,Konyagin,Maynard,Tao,2018) log3 x Conjectures
G(x) Cramér (1936): lim sup 2 = 1. x→∞ log x Shanks (1964): G(x) ∼ log2 x.
G(x) −γ Granville (1995): lim sup 2 > 2e = 1.1229 ... x→∞ log x Computational evidence, up to 1018 Cramér’s model of large prime gaps
Let X3,X4,X5,... be indep. random vars. s.t. 1 1 (X = 1) = , (X = 0) = 1 − . P n log n P n log n Let P = {n : Xn = 1} = {P1,P2,...}, the set of “probabilistic primes”.
Theorem (Cramér, 1936) With probability 1,
PN+1 − PN lim sup 2 = 1. N→∞ log N
Cramér: “for the ordinary sequence of prime numbers pn, some similar relation may hold”. Sketch of the proof of Cramér’s theorem
1 1 (X = 1) = , (X = 0) = 1 − . P n log n P n log n 1−o(1) Suppose that N 6 k 6 N. Then 1 g (X = ··· = X = 0) ≈ 1 − ≈ e−g/ log N . P k+1 k+g log k
Hence (summing on k)
−g/ log N E#{gaps of length > g below N} ≈ Ne .
If g > (1 + ε) log2 N, this is o(1). If g < (1 − ε) log2 N, then this is very large. More predictions of Cramér’s model: distribtion of gaps
−λ (1/N)E#{gaps of length > λ log N} ≈ e .
18 Actual prime gap statistics, pn < 4 · 10
Gallagher, 1976. Prime k−tuples conjecture ⇒ exponential prime gap distribution General Cramér’s-type model: random darts
Choose N random points in [0, 1] (random darts)
Theorem (classical?) log N W.h.p., the max. gap is ∼ N . Proof idea (Rényi). The N + 1 gaps have distribution
E E =d 1 ,..., N+1 ,S = E + ··· + E , S S 1 N+1
−x where each Ei has exponential distribution, P(Ei 6 x) = 1 − e . W.h.p., S ∼ N. Also,
e−u N+1 (max E log N + u) = 1 − ∼ exp{−e−u}, P i 6 N the Gumbel extreme value distribution. Random darts and Cramér’s model
Choose N random points in [0, x] (random darts) x(log N + u) max gap ≈ exp{−e−u}. P 6 N
Probabilistic primes; N = li(x) + O(x1/2+ε) x(log li(x) + u) −u P max Pn+1 − Pn 6 ≈ exp{−e }. Pn6x li(x)
Theorem For Cramér’s probabilistic primes,
x log li(x) max Pn − Pn−1 . Cr1(x) := ≈ (log x)(log x − log2 x). Pn6x li(x)
Q1: Does this explain the data for actual primes? Data vs. refined Cramér conjecture General Cramér’s-type model: random darts
Choose N random points in [0, x] (random darts) x log N Expected maximal gap is of size ≈ N Prime k-tuples. Let f1, . . . , fk be distinct, irreducible polynomials fi : Z → Z with pos. leading coeff., degrees di, and f1 ··· fk has no fixed prime factor. Conjecture (Bateman-Horn)
#{n 6 x : f1(n), . . . , fk(n) all prime} ∼ C lik(x), R x dt where C = C(f1, . . . , fk) > 0 is constant and lik(x) = 2 (log t)k Refined Cramér conjecture
The largest gap in {n 6 x : f1(n), . . . , fk(n) all prime} is
k x log(C lik(x)) (log x) . Crk(x) := ≈ (log x − k log2 x) C lik(x) C Twin prime gaps
(f1, f2) = (n, n + 2), C ≈ 1.32032 Prime triplet gaps
(f1, f2, f3) = (n, n + 2, n + 6) C ≈ 2.85825 Prime quadruplet gaps
(f1, . . . , f4) = (n, n + 2, n + 6, n + 8) C ≈ 4.15118 Cramér’s model defect: global distribution of primes
Theorem (Cramér, 1936 (“Probabilistic RH”)) 1/2+ε With probability 1, Π(x) := #{Pn 6 x} = li(x) + O(x ). J. Pintz observed the following: Theorem
x (Π(x) − li(x))2 ∼ , E log x contrast with Theorem (Cramér,1920) On R.H., Z 2x 1 2 x |π(t) − li(t)| dt 2 x x log x Cramér’s model defect: small gaps
Theorem. With probability 1,
#{n : n, n + 1 ∈ P} = ∞
This does not hold for real primes!
Theorem. With probability 1, x #{n 6 x : n, n + 2 ∈ P} ∼ . log2 x
Conjecture (Hardy-Littlewood, 1923). x #{n 6 x : n, n + 2 prime} ∼ C , log2 x
Q 2 where C = 2 p>2(1 − 1/(p − 1) ) ≈ 1.3203 Granville’s refinement of Cramér’s model
Cramér’s model major defect: Cramér primes are equidistributed modulo small primes like 2,3,..., whereas real primes are not.
This shows up in asymptotics for prime k-tuples, and for counts of primes in very short intervals: w.h.p., y Π(x + y) − Π(x) ∼ (y/ log2 x → ∞) log x By contrast, Theorem (H. Maier, 1985) ∀M > 1, π(x + logM x) − π(x) lim sup M−1 > 1. x→∞ log x Granville’s refinement of Cramér’s model, II
Y o(1) Let T = ε log x, QT = p = x . p6T Real primes live in
ST := {n ∈ Z :(n, QT ) = 1}
For n ∈ ST ∩ (x, 2x], define the random variables
Zn : P(Zn = 1) = θ/ log n, P(Zn = 0) = 1 − θ/ log n,
−γ where 1/θ = φ(QT )/QT ∼ e / log T is the density of ST . That is, θ = conditional prob. that n is prime given that n ∈ S . log n T Granville’s refinement of Cramér’s model, III
ST := {n ∈ Z :(n, QT ) = 1}
Let y = c log2 x, take special values of m ∈ (x, 2x], namely those 2+o(1) with with QT |m. Since y = T , y # ([m, m + y] ∩ S ) = # ([0, y] ∩ S ) ∼ . (sp) T T log y
By contrast, for a typical m ∈ Z, y # ([m, m + y] ∩ S ) ∼ θ−1y ∼ 2e−γ . (ty) T log y
Note 2e−γ = 1.1229 . . . > 1, so the intervals in (sp) are deficient in sifted numbers. Granville’s refinement of Cramér’s model, IV
T = ε log x, y = c log2 x, y # ([m, m + y] ∩ S ) = # ([0, y] ∩ S ) ∼ . (sp) T T log y Get