Lévy's constant

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In mathematics Lévy's constant (sometimes known as the Khinchin–Lévy constant) occurs in an expression for the asymptotic behaviour of the denominators of the convergents of simple continued fractions.[1] In 1935, the Soviet mathematician Aleksandr Khinchin showed[2] that the denominators qn of the convergents of the continued fraction expansions of almost all real numbers satisfy

limnqn1/n=eβ

Soon afterward, in 1936, the French mathematician Paul Lévy found[3] the explicit expression for the constant, namely

eβ=eπ2/(12ln2)=3.275822918721811159787681882 Template:OEIS

The term "Lévy's constant" is sometimes used to refer to π2/(12ln2) (the logarithm of the above expression), which is approximately equal to 1.1865691104… The value derives from the asymptotic expectation of the logarithm of the ratio of successive denominators, using the Gauss-Kuzmin distribution. In particular, the ratio has the asymptotic density functionTemplate:Citation needed

f(z)=1z(z+1)ln(2)

for z1 and zero otherwise. This gives Lévy's constant as

β=1lnzz(z+1)ln2dz=01lnz1(z+1)ln2dz=π212ln2.

The base-10 logarithm of Lévy's constant, which is approximately 0.51532041…, is half of the reciprocal of the limit in Lochs' theorem.

Proof

[4]

The proof assumes basic properties of continued fractions.

Let T:x1/xmod1 be the Gauss map.

Lemma

|lnxlnpn(x)/qn(x)|1/qn(x)1/Fnwhere Fn is the Fibonacci number.

Proof. Define the function f(t)=lnpn+pn1tqn+qn1t. The quantity to estimate is then |f(Tnx)f(0)|.

By the mean value theorem, for any t[0,1],|f(t)f(0)|maxt[0,1]|f(t)|=maxt[0,1]1(pn+tpn1)(qn+tqn1)=1pnqn1qnThe denominator sequence q0,q1,q2, satisfies a recurrence relation, and so it is at least as large as the Fibonacci sequence 1,1,2,.

Ergodic argument

Since pn(x)=qn1(Tx), and p1=1, we havelnqn=lnpn(x)qn(x)+lnpn1(Tx)qn1(Tx)++lnp1(Tn1x)q1(Tn1x)By the lemma, lnqn=lnx+lnTx++lnTn1x+δ

where |δ|k=11/Fn is finite, and is called the reciprocal Fibonacci constant.


By Birkhoff's ergodic theorem, the limit limnlnqnn converges to01(lnt)ρ(t)dt=π212ln2 almost surely, where ρ(t)=1(1+t)ln2 is the Gauss distribution.

See also

References

  1. Template:Citation
  2. [Reference given in Dover book] "Zur metrischen Kettenbruchtheorie," Compositio Matlzematica, 3, No.2, 275–285 (1936).
  3. [Reference given in Dover book] P. Levy, Théorie de l'addition des variables aléatoires, Paris, 1937, p. 320.
  4. Ergodic Theory with Applications to Continued Fractions, UNCG Summer School in Computational Number Theory University of North Carolina Greensboro May 18 - 22, 2020. Lesson 9: Applications of ergodic theory

Further reading


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