historical background - H.
Cramér's contribution to the field
Although Erdös, Kac, Wintner
and Kubilius are generally credited with
the founding of probabilistic number theory, the following (earlier) work
of Harald
Cramér should not be overlooked:
H.
Cramér, "Prime numbers and probability", Skand. Mat.-Kongr.
8 (1935) 107-115.
A. Granville,
"Harald Cramér and the distribution of prime
numbers", Scandanavian Actuarial Journal 1 (1995),
12-28. [an excellent survey of Cramér's work in this area]
The following is an excerpt from the chapter "Stochastic
Distribution of Prime Numbers" of G. Tenenbaum and M. Mendès France's
wonderful little book
The Prime
Numbers and Their Distribution (AMS, 2000):
"The most natural questions about prime numbers are often quite
hard to answer. Furthermore, it is even rather difficult, in certain
cases, to make a reasonable guess for what the exact answer might be.
Having studied the distribution of prime numbers since the twenties,
Cramér
proposed at the end of the thirties a simple and fascinating
method for producing conjectures concerning primes: the sequence
of prime numbers behaves like a random sequence with the same growth
constraint.
Let us formalize a little. The prime number
theorem suggests that the probability that an integer of size
n be a prime is close to 1/log n. Denote by
{Xn} (where n = 2,3,4,...) a sequence of
independent random variables taking values 0 and 1 with the
probability(Xn = 1) = 1/log n
(n > 2)
Then the random sequence
S := {n > 1: Xn = 1}
constitutes, according to Cramér, a stochastic model of the sequence
of primes.
In more intuitive terms, we may consider the following mechanism.
Arrange, in an infinite (or very long) sequence, urns U3,
U4, etc., with the property that the urn
Un contains one white ball and about log n
black balls. Now choose a ball at random from each urn and assign the
integer n to the sequence S if the ball taken from
Un is white. The sequence S models the
sequence of primes. Of course, for each particular drawing the sequence
S will possess specific properties which will distinguish it
significantly from the sequence P of all prime numbers. However,
if a property turns up sufficiently frequently to occur almost
surely when the drawings are repeated, we conjecture with Cramér
that it is also shared by P."
A clearly-written elementary introduction to Cramér's
ideas is contained in the following article:
D.L. Snell, "Chance in the Primes, Part II",
Chance
News 11.02
C. Bonanno and M.S. Mega, "Toward a dynamical model for prime numbers"
Chaos, Solitons and Fractals 20 (2004) 107-118
[abstract:] "We show one possible dynamical approach to the study of the distribution of prime numbers. Our
approach is based on two complexity methods, the Computable Information Content and the Entropy Information
Gain, looking for analogies between the prime numbers and intermittency."
The main idea here is that the Manneville map Tz exhibits a phase
transition at z = 2, at which point the mean Algorithmic Information Content
of the associated symbolic dynamics is n/log n. n is a kind of iteration number.
For this to work, the domain of Tz [0,1] must be partitioned as
[0,0.618...] U [0.618...,1] where 1.618... is the golden mean.
The authors attempt to exploit the resemblance to the approximating function in the Prime
Number Theorem, and in some sense model the distribution of primes in dynamical terms,
i.e. relate the prime number series (as a binary string) to the orbits of the Manneville
map T2. Certain refinements of this are then explored.
"We remark that this approach to study prime numbers is similar to the probabilistic
approach introduced by Cramér...that is we assume that the [binary] string [generated
by the sequence of primes]...is one of a family of strings on which there is a probability measure..."
(approximately) chronological bibliography
P. Doyle's English
translation of von Sternach's 1896 treatise on number theoretical random walks, associated with this
introductory article on the subject (scroll down to the section "Probability and the Riemann Hypothesis").
P. Erdös and A. Wintner, "Additive arithmetic functions and
statistical independence", American Journal of Mathematics
61 (1939) 713-722.
P. Erdös and M. Kac, "The Gaussian law of errors in the theory of additive number
theoretic functions"
, American Journal of Mathematics 62 (1940) 738-742.
notes on the Erdös-Kac theorem
H. Riesel, "The Erdös-Kac Theorem", in
Prime Numbers and Computer Methods for Factorization, 2nd
ed. (Birkhäuser, 1994) pp. 158-159
"The Prime Number Theorem obtained by
statistical methods" - a heuristic argument from What is
Mathematics? by R. Courant and H. Robbins (1941)
M. Kac, "Probability methods in some problems of analysis and number
theory", Bulletin of the AMS (1949) 641-665.
A. Rényi, "On the density of certain sequences of integers", Publ.
Inst. Math. Belgrade 8 (1955) 157-162.
I.P. Kubilius, "Probability methods in number theory" (in Russian),
Usp. Mat. Nauk 68 (1956) 31-66.
A. Rényi and P. Turán, "On a theorem of Erdös-Kac", Acta. Arith.
4 (1958) 71-84.
D. Hawkins, "The random sieve",
Mathematics Magazine 31(1958) 1-3.
D. Hawkins, "Random sieves, II", Journal of Number Theory 6
(1974) 192-200.
A. Denjoy, "Probabilites confirmant l'hypothese de Riemann sur les zeros
de zeta(s), C.R. Acad. Sci. Paris 259 (1964)
3143-3145.
Notes on Denjoy's probabilistic interpretation
of the Riemann Hypothesis from H. Edwards book
Riemann's Zeta Function
I.J. Good and R.F. Churchhouse, "The Riemann hypothesis and pseudorandom features of the Möbius
sequence", Mathematics of Computation 22 (1968) 857-864
[abstract:] "A study of the cumulative sums of the Möbius function on the
Atlas Computer of the Science Research Council has revealed certain statistical properties which lead the authors to make a
number of conjectures. One of these is that any conjecture of the Mertens type, viz.
$|M(N)| = |\sum_{n=1}^{N}\mu(n)| \lt k(\sqrt(N))$
where $k$ is a positive constant, is false, and indeed, the authors conjecture that
$\Lim \sup {M(x)(x \log \log x)^{-1/2}} = \sqrt{(12)/\pi}$"
S. Golomb, "A class of probability distributions on the integers", Journal
of Number Theory 2 (1970) 189-192.
P. Billingsley, "Prime numbers and Brownian motion", American Mathematical
Monthly 80 (1973) 1099.
W. Neudecker and D. Williams, "The 'Riemann Hypothesis' for the Hawkins random
sieve" Compositio Mathematica 29 (1974) 197-200.
P. Nanopoulos, "Loi de Dirichlet sur N* et pseudo-probabilites",
C.R. Acad. Sci. Paris Ser. A-B 280 (22) (1975) A1543-A1546.
C.C. Heyde, "On asymptotic behavior
for the Hawkins random sieve", Proc. AMS 56 (1976) 277-280
[abstract:] "This paper is concerned with the Hawkins random sieve which is a probabilistic analogue of the sieve
of Eratosthenes. Analogues of the prime number theorem and Mertens' theorem have previously been obtained for this
sieve by classical probabilistic methods. In the present paper, sharper results akin to the Riemann hypothesis are
obtained by a more elegant martingale approach."
P. Diaconis, F. Mosteller and H. Onishi, "Second order terms for
the variances and covariances of the number of prime factors -
including the square free case", Journal of Number Theory
9 (1977) 187-202.
C.C. Heyde, "A log log improvement to the
Riemann Hypothesis for the Hawkins random sieve" Ann. Prob. 6 no.5 (1978) 870-875
[abstract:] "This paper is concerned with the Hawkins random sieve which is a probabilistic analouge of the sieve of
Eratosthenes. Analogues of the prime number theorem, Mertens' theorem and the Riemann hypothesis have previously been
established for the Hawkins sieve. In the present paper we give a more delicate analysis using iterated logarithm results
for both mantingales and tail sums of martingale differences to deduce a considerably improved log log replacement for the
Riemann hypothesis result."
J. Kubilius,
Probabilistic Methods in the Theory of Numbers (AMS, 1978)
P.D.T.A. Elliot,
Probabilistic Number Theory I: Mean-value Theorems, Grundlehren der
Mathematischen Wissenschaften 239 (Springer, 1979)
P.D.T.A. Elliot, Probabilistic Number Theory II: Central Limit
Theorems, Grundlehren der Mathematischen Wissenschaften 240
(Springer, 1980)
R.O. Rabin, "Probabilistic algorithm for testing primality", Journal of Number Theory
12 (1980) 128-138.
M. Shlesinger, "On the Riemann hypothesis: a fractal random walk approach", Physica A
138 (1986) 310-319
[abstract:] "In his investigation of the distribution of prime numbers Riemann,
in 1859, introduced the zeta function with a complex argument. His
analysis led him to hypothesize that all the complex zeros of the
zeta function lie on a vertical line in the complex plane. The proof
or disproof of this hypothesis has been a famous outstanding problem
in mathematics. We are able to recast Riemann's Hypothesis into a
probabilistic framework connected to the fractal behavior of a lattice
random walk. Fractal random walks were introduced by P. Levy, and in
the continuum are called Levy flights. For one particular lattice
version of a Levy flight we show the connection to Weierstrass'
continuous but nowhere differentiable function. For a different
lattice version, using a Mellin transform analysis, we show how the
zeroes of the zeta function become the singularities of a complex
integrand which governs the behavior of a fractal random walk. The
laws of probability place restrictions on the locations of the zeroes
of the zeta function. No inconsistencies with probability theory are found if the Riemann Hypothesis is false."
V.K. Murty and M.R. Murty,
"An analog of the Erdös-Kac theorem for Fourier coefficients of modular
forms", Indian Journal of Pure and Applied Mathematics 15
(10) (1984) 1090-1101.
L. Smith and P. Diaconis, "Honest Bernoulli excursions", Journal of
Applied Probability 25 (1988) 464-477
J.V. Armitage, "The Riemann
Hypothesis and the Hamiltonian of a quantum mechanical system" (section
5: "A random walk approximation to the Riemann Hypothesis"), from Number
Theory and Dynamical Systems, eds. M.M. Dodson and J.A.G. Vickers (LMS
Lecture Notes, series 134, Cambridge University Press), 153-172.
"The connection between random walks and Brownian motion is well-known
and so also the connection with the Schrödinger equation, on replacing
'time' with 'imaginary time'. In this section we use a random walk approach
to the Ornstein-Uhlenbeck process (or the Fokker-Planck equation) to exhibit
a polynomial whose zeros, under a suitable limiting process, ought to be
the zeros of the Riemann zeta-function."
D. Williams, "Brownian motion and the Riemann zeta-function", from Disorder in Physical Systems (Clarendon Press, 1990) 361-372.
J.L. Lucio and Y. Meurice, "Asymptotic properties of random walks
on p-adic spaces", University of Iowa Preprint 90-33, 1-5 (1990)
S.W. Golomb, "Probability,
information theory, and prime number theory", Discrete
Mathematics 106-107 (1992) 219-229
[abstract:] "For any probability distribution D =
{\alpha(n)} on Z+, we define. . . the
probability in D that a 'random' integer is a multiple of
m; and . . . the probability in D that a 'random'
integer is relatively prime to k. We specialize this general
situation to three important families of distributions . . . Several
basic results and concepts from analytic prime number theory are
revisited from the perspective of these families of probability
distributions, and the Shannon entropy for each of these families is
determined."
K.S. Alexander, K. Baclawski and G.-C. Rota, "A stochastic
interpretation of the Riemann zeta function", Proceedings of the National Academy of Sciences USA
90 (1993) 697-699
[abstract:] "We give a stochastic process for which the terms of the Riemann zeta function occur as the probability distributions of
the elementary random variables of the process."
S. Albeverio and W. Karwowski,
"A Random Walk on p-Adics - the Generator and Its Spectrum",
Stochastic Processes and their Applications 53 (1994) 1-22.
G. Tenenbaum, Introduction to Analytic and Probabilistic Number
Theory, Cambridge Studies in Advanced Mathematics 46
(C.U.P., 1995)
N. Boston,
"A probabilistic generalization of the Riemann zeta function"
,