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Mathematical Methods for Physics and Engineering - Matematica.NET

Mathematical Methods for Physics and Engineering - Matematica.NET

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8.13 EIGENVECTORS AND EIGENVALUESrepresent the eigenvectors x of A in our chosen coordinate system. Conventionally,these column matrices are also referred to as the eigenvectors of the matrixA. § Clearly, if x is an eigenvector of A (with some eigenvalue λ) then any scalarmultiple µx is also an eigenvector with the same eigenvalue. We there<strong>for</strong>e oftenuse normalised eigenvectors, <strong>for</strong> whichx † x =1(note that x † x corresponds to the inner product 〈x|x〉 in our basis). Any eigenvectorx can be normalised by dividing all its components by the scalar (x † x) 1/2 .As will be seen, the problem of finding the eigenvalues <strong>and</strong> correspondingeigenvectors of a square matrix A plays an important role in many physicalinvestigations. Throughout this chapter we denote the ith eigenvector of a squarematrix A by x i <strong>and</strong> the corresponding eigenvalue by λ i . This superscript notation<strong>for</strong> eigenvectors is used to avoid any confusion with components.◮A non-singular matrix A has eigenvalues λ i <strong>and</strong> eigenvectors x i . Find the eigenvalues <strong>and</strong>eigenvectors of the inverse matrix A −1 .The eigenvalues <strong>and</strong> eigenvectors of A satisfyAx i = λ i x i .Left-multiplying both sides of this equation by A −1 , we findA −1 Ax i = λ i A −1 x i .Since A −1 A = I, on rearranging we obtainA −1 x i = 1 λ ix i .Thus, we see that A −1 has the same eigenvectors x i as does A, but the correspondingeigenvalues are 1/λ i . ◭In the remainder of this section we will discuss some useful results concerningthe eigenvectors <strong>and</strong> eigenvalues of certain special (though commonly occurring)square matrices. The results will be established <strong>for</strong> matrices whose elements maybe complex; the corresponding properties <strong>for</strong> real matrices may be obtained asspecial cases.8.13.1 Eigenvectors <strong>and</strong> eigenvalues of a normal matrixIn subsection 8.12.7 we defined a normal matrix A as one that commutes with itsHermitian conjugate, so thatA † A = AA † .§ In this context, when referring to linear combinations of eigenvectors x we will normally use theterm ‘vector’.273

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