Riemann–Siegel formula

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In mathematics, the Riemann–Siegel formula is an asymptotic formula for the error of the approximate functional equation of the Riemann zeta function, an approximation of the zeta function by a sum of two finite Dirichlet series. It was found by Template:Harvtxt in unpublished manuscripts of Bernhard Riemann dating from the 1850s. Siegel derived it from the Riemann–Siegel integral formula, an expression for the zeta function involving contour integrals. It is often used to compute values of the Riemann–Siegel formula, sometimes in combination with the Odlyzko–Schönhage algorithm which speeds it up considerably. When used along the critical line, it is often useful to use it in a form where it becomes a formula for the Z function.

If M and N are non-negative integers, then the zeta function is equal to

ζ(s)=n=1Nns+γ(1s)n=1Mns1+R(s)

where

γ(s)=π12sΓ(s2)Γ(1s2)

is the factor appearing in the functional equation Template:Math, and

R(s)=Γ(1s)2πi(x)s1eNxex1dx

is a contour integral whose contour starts and ends at +∞ and circles the singularities of absolute value at most Template:Math. The approximate functional equation gives an estimate for the size of the error term. Template:Harvtxt[1] and Template:Harvtxt derive the Riemann–Siegel formula from this by applying the method of steepest descent to this integral to give an asymptotic expansion for the error term R(s) as a series of negative powers of Im(s). In applications s is usually on the critical line, and the positive integers M and N are chosen to be about Template:Math. Template:Harvtxt found good bounds for the error of the Riemann–Siegel formula.

Riemann's integral formula

Riemann showed that

01eiπu2+2πipueπiueπiudu=eiπp2eiπpeiπpeiπp

where the contour of integration is a line of slope −1 passing between 0 and 1 Template:Harv.

He used this to give the following integral formula for the zeta function:

πs2Γ(s2)ζ(s)=πs2Γ(s2)01xseπix2eπixeπixdx+π1s2Γ(1s2)01xs1eπix2eπixeπixdx

References

Template:Reflist

Template:Bernhard Riemann