Gutenberg–Richter law: Difference between revisions

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In mathematics, there are at least two results known as '''"Weyl's inequality"'''.
 
==Weyl's inequality in number theory==
In [[number theory]], '''Weyl's inequality''', named for [[Hermann Weyl]], states that if ''M'', ''N'', ''a'' and ''q'' are integers, with ''a'' and ''q'' [[coprime]], ''q''&nbsp;>&nbsp;0, and ''f'' is a [[real number|real]] [[polynomial]] of degree ''k'' whose leading coefficient ''c'' satisfies
 
:<math>|c-a/q|\le tq^{-2},\,</math>
 
for some ''t'' greater than or equal to 1, then for any positive real number <math>\scriptstyle\varepsilon</math> one has
 
:<math>\sum_{x=M}^{M+N}\exp(2\pi if(x))=O\left(N^{1+\varepsilon}\left({t\over q}+{1\over N}+{t\over N^{k-1}}+{q\over N^k}\right)^{2^{1-k}}\right)\text{ as }N\to\infty.</math>
 
This inequality will only be useful when
 
:<math>q < N^k,\,</math>
 
for otherwise estimating the modulus of the [[exponential sum]] by means of the [[triangle inequality]] as <math>\scriptstyle\le\, N</math> provides a better bound.
 
==Weyl's inequality in matrix theory==
In linear algebra, '''Weyl's inequality''' is a theorem about the changes to [[eigenvalues]] of a [[Hermitian matrix]] that is perturbedIt is useful if we wish to know the eigenvalues of the Hermitian matrix ''H'' but there is an uncertainty about the entries of ''H''.  We let ''H'' be the exact matrix and ''P'' be a perturbation matrix that represents the uncertainty. The matrix we 'measure' is <math>\scriptstyle M \,=\, H \,+\, P</math>.
 
The theorem says that if ''M'', ''H'' and ''P'' are all ''n'' by ''n'' Hermitian matrices, where ''M'' has eigenvalues
 
:<math>\mu_1 \ge \cdots \ge \mu_n\, </math>
 
and ''H'' has eigenvalues
 
:<math>\nu_1 \ge \cdots \ge \nu_n\, </math>
 
and ''P'' has eigenvalues
 
:<math>\rho_1 \ge \cdots \ge \rho_n\, </math>
 
then the following inequalties hold for <math>\scriptstyle i \,=\, 1,\dots ,n</math>:
 
:<math>\nu_i + \rho_n \le \mu_i \le \nu_i + \rho_1\, </math>
 
More generally, if  <math>\scriptstyle j+k-n \,\ge\, i \,\ge\, r+s-1,\dots ,n</math>, we have
 
:<math>\nu_j + \rho_k \le \mu_i \le \nu_r + \rho_s\, </math>
 
If ''P'' is positive definite (that is, <math>\scriptstyle\rho_n \,>\, 0</math>) then this implies
 
:<math>\mu_i > \nu_i \quad  \forall i = 1,\dots,n.\,</math>
 
Note that we can order the eigenvalues because the matrices are Hermitian and therefore the eigenvalues are real.
 
==References==
 
* ''Matrix Theory'', Joel N. Franklin, (Dover Publications, 1993) ISBN 0-486-41179-6
 
* "Das asymptotische Verteilungsgesetz der Eigenwerte linearer partieller Differentialgleichungen", H. Weyl, Math. Ann., 71 (1912), 441–479
 
{{DEFAULTSORT:Weyl's Inequality}}
[[Category:Diophantine approximation]]
[[Category:Inequalities]]
[[Category:Linear algebra]]

Revision as of 14:41, 20 June 2013

In mathematics, there are at least two results known as "Weyl's inequality".

Weyl's inequality in number theory

In number theory, Weyl's inequality, named for Hermann Weyl, states that if M, N, a and q are integers, with a and q coprime, q > 0, and f is a real polynomial of degree k whose leading coefficient c satisfies

|ca/q|tq2,

for some t greater than or equal to 1, then for any positive real number ε one has

x=MM+Nexp(2πif(x))=O(N1+ε(tq+1N+tNk1+qNk)21k) as N.

This inequality will only be useful when

q<Nk,

for otherwise estimating the modulus of the exponential sum by means of the triangle inequality as N provides a better bound.

Weyl's inequality in matrix theory

In linear algebra, Weyl's inequality is a theorem about the changes to eigenvalues of a Hermitian matrix that is perturbed. It is useful if we wish to know the eigenvalues of the Hermitian matrix H but there is an uncertainty about the entries of H. We let H be the exact matrix and P be a perturbation matrix that represents the uncertainty. The matrix we 'measure' is M=H+P.

The theorem says that if M, H and P are all n by n Hermitian matrices, where M has eigenvalues

μ1μn

and H has eigenvalues

ν1νn

and P has eigenvalues

ρ1ρn

then the following inequalties hold for i=1,,n:

νi+ρnμiνi+ρ1

More generally, if j+knir+s1,,n, we have

νj+ρkμiνr+ρs

If P is positive definite (that is, ρn>0) then this implies

μi>νii=1,,n.

Note that we can order the eigenvalues because the matrices are Hermitian and therefore the eigenvalues are real.

References

  • Matrix Theory, Joel N. Franklin, (Dover Publications, 1993) ISBN 0-486-41179-6
  • "Das asymptotische Verteilungsgesetz der Eigenwerte linearer partieller Differentialgleichungen", H. Weyl, Math. Ann., 71 (1912), 441–479