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In mathematics, the '''Jacobi method for complex [[Hermitian matrices]]''' is a generalization of the [[Jacobi eigenvalue algorithm|Jacobi iteration method]]The [[Jacobi eigenvalue algorithm|Jacobi iteration method]] is also explained in "Introduction to Linear Algebra" by {{harvtxt|Strang|1993}}.
 
== Derivation ==
The complex [[unitary matrices|unitary]] [[Rotation matrix|rotation]] matrices ''R''<sub>''pq''</sub> can be used for [[Jacobi eigenvalue algorithm|Jacobi iteration]] of complex [[Hermitian matrices]] in order to find a numerical estimation of their eigenvectors and eigenvalues simultaneously.  
 
Similar to the [[Givens rotation|Givens rotation matrices]], ''R''<sub>''pq''</sub> are defined as:
:<math> 
\begin{align}
(R_{pq})_{m,n} & = \delta_{m,n}  & \qquad m,n \ne p,q, \\[10pt]
(R_{pq})_{p,p} & = \frac{+1}{\sqrt{2}} e^{-i\theta},  \\[10pt]
(R_{pq})_{q,p} & = \frac{+1}{\sqrt{2}} e^{-i\theta}, \\[10pt]
(R_{pq})_{p,q} & = \frac{-1}{\sqrt{2}} e^{+i\theta}, \\[10pt]
(R_{pq})_{q,q} & = \frac{+1}{\sqrt{2}} e^{+i\theta}
\end{align}
</math>
 
Each rotation matrix, ''R''<sub>''pq''</sub>, will modify only the ''p''th and ''q''th rows or columns of a matrix ''M'' if it is applied from left or right, respectively:
 
:<math>
\begin{align}
(R_{pq} M)_{m,n} & =
\begin{cases}
M_{m,n} & m \ne p,q \\[8pt]
\frac{1}{\sqrt{2}} (M_{p,n} e^{-i\theta} - M_{q,n} e^{+i\theta}) & m = p \\[8pt]
\frac{1}{\sqrt{2}} (M_{p,n} e^{-i\theta} + M_{q,n} e^{+i\theta}) & m = q
\end{cases} \\[8pt]
(MR_{pq}^\dagger)_{m,n} & =
\begin{cases}
M_{m,n} & n \ne p,q \\
\frac{1}{\sqrt{2}} (M_{m,p} e^{+i\theta} - M_{m,q} e^{-i\theta}) & n = p \\[8pt]
\frac{1}{\sqrt{2}} (M_{m,p} e^{+i\theta} + M_{m,q} e^{+i\theta}) & n = q
\end{cases}
\end{align}
</math>
 
A [[Hermitian matrix]], ''H'' is defined by the conjugate transpose symmetry property:
 
:<math>  H^\dagger = H \ \Leftrightarrow\ H_{i,j} = H^{*}_{j,i} </math>
 
By definition, the complex conjugate of a complex [[unitary matrices|unitary]] [[Rotation matrix|rotation]] matrix, ''R'' is its inverse and also a complex  [[unitary matrices|unitary]] [[Rotation matrix|rotation]] matrix:
 
:<math>
\begin{align}
R^\dagger_{pq} & = R^{-1}_{pq} \\[6pt]
\Rightarrow\ R^{\dagger^\dagger}_{pq} & = R^{-1^\dagger}_{pq} = R^{-1^{-1}}_{pq} = R_{pq}.
\end{align}
</math>
 
Hence, the complex equivalent [[Givens rotation|Givens transformation]] <math>T</math> of a [[Hermitian matrices|Hermitian matrix]] ''H'' is also a [[Hermitian matrices|Hermitian matrix]] similar to ''H'':
 
:<math>
\begin{align}
T & \equiv R_{pq} H R^\dagger_{pq}, & & \\[6pt]
T^\dagger & = (R_{pq} H R^\dagger_{pq})^\dagger = R^{\dagger^\dagger}_{pq} H^\dagger R^\dagger_{pq} = R_{pq} H R^\dagger_{pq} = T
\end{align}
</math>
 
The elements of ''T'' can be calculated by the relations above. The important elements for the [[Jacobi eigenvalue algorithm|Jacobi iteration]] are the following four:
 
:<math> 
\begin{array}{clrcl}
T_{p,p} & = & &      H_{p,q}              & - \ \ \ \mathrm{Re}\{H_{p,q} e^{-2i\theta}\}, \\[8pt]
T_{p,q} & = & & \frac{H_{p,p} - H_{q,q}}{2} & + \ i \ \mathrm{Im}\{H_{p,q} e^{-2i\theta}\}, \\[8pt]
T_{q,p} & = & & \frac{H_{p,p} + H_{q,q}}{2} & - \ i \ \mathrm{Im}\{H_{p,q} e^{-2i\theta}\}, \\[8pt]
T_{q,q} & = & &      H_{p,q}              & + \ \ \ \mathrm{Re}\{H_{p,q} e^{-2i\theta}\}.  
\end{array}
</math>
 
Each [[Jacobi eigenvalue algorithm|Jacobi iteration]] with ''R''<sup>''J''</sup><sub>''pq''</sub> generates a transformed matrix, ''T''<sup>''J''</sup>, with ''T''<sup>''J''</sup><sub>''p'',''q''</sub>&nbsp;=&nbsp;0. The rotation matrix ''R''<sup>''J''</sup><sub>''p'',''q''</sub> is defined as a product of two complex [[unitary matrices|unitary]] [[Givens rotation|rotation]] matrices.
 
:<math> 
\begin{align}
R^J_{pq} & \equiv R_{pq}(\theta_2)\, R_{pq}(\theta_1),\text{ with} \\[8pt]
\theta_1 & \equiv \frac{\pi - 2\phi_1}{4} \text{ and } \theta_2 \equiv \frac{\phi_2}{2},
\end{align}
</math>
 
where the phase terms, <math>\phi_1</math> and <math>\phi_2</math> are given by:
 
:<math>
\begin{align}
\tan \phi_1 & = \frac{\mathrm{Im}\{H_{p,q}\}}{\mathrm{Re}\{H_{p,q}\}}, \\[8pt]
\tan \phi_2 & = \frac{2 H_{p,q}}{H_{p,p} - H_{q,q}}.
\end{align}
</math>
 
Finally, it is important to note that the product of two complex rotation matrices for given angles ''&theta;''<sub>1</sub> and ''&theta;''<sub>2</sub> cannot be transformed into a single complex unitary rotation matrix ''R''<sub>''pq''</sub>(''&theta;''). The product of two complex rotation matrices are given by:
 
:<math>
\begin{align}
\left[ R_{pq}(\theta_2)\, R_{pq}(\theta_1) \right]_{m,n} =
\begin{cases}
\ \ \ \ \delta_{m,n}                        &  m,n \ne p,q, \\[8pt]
-i e^{-i\theta_1}\, \sin{\theta_2}          & m = p \text{ and } n = p, \\[8pt]
-i e^{+i\theta_1}\, \cos{\theta_2}          & m = p \text{ and } n = q, \\[8pt]
\ \ \ \ e^{-i\theta_1}\, \cos{\theta_2}    & m = q \text{ and } n = p, \\[8pt]
+i e^{+i\theta_1}\, \sin{\theta_2}          & m = q \text{ and } n = q.
\end{cases}
\end{align}
</math>
 
== References ==
 
* {{Citation | last=Strang | first=G. | authorlink=Gilbert Strang | title=Introduction to Linear Algebra | publisher=Wellesley Cambridge Press | location = MA | year=1993}}.
 
{{Numerical linear algebra}}
 
[[Category:Numerical linear algebra]]

Latest revision as of 02:20, 9 January 2013

In mathematics, the Jacobi method for complex Hermitian matrices is a generalization of the Jacobi iteration method. The Jacobi iteration method is also explained in "Introduction to Linear Algebra" by Template:Harvtxt.

Derivation

The complex unitary rotation matrices Rpq can be used for Jacobi iteration of complex Hermitian matrices in order to find a numerical estimation of their eigenvectors and eigenvalues simultaneously.

Similar to the Givens rotation matrices, Rpq are defined as:

(Rpq)m,n=δm,nm,np,q,(Rpq)p,p=+12eiθ,(Rpq)q,p=+12eiθ,(Rpq)p,q=12e+iθ,(Rpq)q,q=+12e+iθ

Each rotation matrix, Rpq, will modify only the pth and qth rows or columns of a matrix M if it is applied from left or right, respectively:

(RpqM)m,n={Mm,nmp,q12(Mp,neiθMq,ne+iθ)m=p12(Mp,neiθ+Mq,ne+iθ)m=q(MRpq)m,n={Mm,nnp,q12(Mm,pe+iθMm,qeiθ)n=p12(Mm,pe+iθ+Mm,qe+iθ)n=q

A Hermitian matrix, H is defined by the conjugate transpose symmetry property:

H=HHi,j=Hj,i*

By definition, the complex conjugate of a complex unitary rotation matrix, R is its inverse and also a complex unitary rotation matrix:

Rpq=Rpq1Rpq=Rpq1=Rpq11=Rpq.

Hence, the complex equivalent Givens transformation T of a Hermitian matrix H is also a Hermitian matrix similar to H:

TRpqHRpq,T=(RpqHRpq)=RpqHRpq=RpqHRpq=T

The elements of T can be calculated by the relations above. The important elements for the Jacobi iteration are the following four:

Tp,p=Hp,qRe{Hp,qe2iθ},Tp,q=Hp,pHq,q2+iIm{Hp,qe2iθ},Tq,p=Hp,p+Hq,q2iIm{Hp,qe2iθ},Tq,q=Hp,q+Re{Hp,qe2iθ}.

Each Jacobi iteration with RJpq generates a transformed matrix, TJ, with TJp,q = 0. The rotation matrix RJp,q is defined as a product of two complex unitary rotation matrices.

RpqJRpq(θ2)Rpq(θ1), withθ1π2ϕ14 and θ2ϕ22,

where the phase terms, ϕ1 and ϕ2 are given by:

tanϕ1=Im{Hp,q}Re{Hp,q},tanϕ2=2Hp,qHp,pHq,q.

Finally, it is important to note that the product of two complex rotation matrices for given angles θ1 and θ2 cannot be transformed into a single complex unitary rotation matrix Rpq(θ). The product of two complex rotation matrices are given by:

[Rpq(θ2)Rpq(θ1)]m,n={δm,nm,np,q,ieiθ1sinθ2m=p and n=p,ie+iθ1cosθ2m=p and n=q,eiθ1cosθ2m=q and n=p,+ie+iθ1sinθ2m=q and n=q.

References

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Template:Numerical linear algebra