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The Spectral Theorem in Complex and Real Inner Product Space |
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| Jan6-13, 03:24 AM | #1 |
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The Spectral Theorem in Complex and Real Inner Product Space
Hi
I am going through Sheldon Axler - Linear Algebra Done right. The book States the Complex Spectral Theorem as : Suppose that V is a complex inner product space and T is in L(V,V). Then V has an orthonormal basis consisting of eigen vectors of T if and only if T is normal. The proof of this theorem seems fine. It uses the property that ||Tv|| = ||T*v|| for a normal operator T, where T* is the adjoint of T. However, the Real Spectral Theorem States that V has an orthonormal basis consisting of eigen vectors of T if and if only if T is self adjoint. My Doubt : Why does Real Spectral Theorem take into account only self adjoint operators as a necessary condition despite the fact that an operator can be normal and still not self adjoint. When it's normal, the property ||Tv|| = ||T*v|| should be still valid for real inner product space which leads to the desired result. Would be great if somebody could give me an insight. Thanks. |
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| Jan6-13, 04:04 AM | #2 |
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The complex spectral theorem states that exactly the normal operators are the operators which are orthogonally diagonalizable.
The real spectral theorem states that it are the self-adjoint operators. Why the difference? The real spectral theorem asks for which matrices [itex]A\in M_n(\mathbb{R})[/itex], there exists an orthogonal basis [itex]\{v_1,...,v_n\}[/itex] and real numbers [itex]\lambda_i[/itex] such that [itex]Av_i=\lambda v_i[/itex]. Of course, if A satisfies the real spectral theorem, then it satisfies the complex spectral theorem. But vice versa is not the case. Let A be a normal operator, then it satisfies the complex spectral theorem. This means that there exists an orthogonal basis [itex]\{v_1,...,v_n\}[/itex] and complex numbers [itex]\lambda_i[/itex] such that [itex]Av_i=\lambda v_i[/itex]. But in order to satisfy the real spectral theorem, we demand the [itex]\lambda_i[/itex] to be real (and we demand that entries of A to be real). So the matrices satisfying the real spectral theorem are exactly the (real) normal matrices with real eigenvalues. Now, it turns out that if a normal matrix has only real eigenvalues, then it is self-adjoint. This is why only self-adjoint matrices satisfy the real spectral theorem. |
| Jan6-13, 05:50 AM | #3 |
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So, if i prove that if the eigen values of a normal operator T's matrix are all real, then T is self adjoint , this should prove the real spectral theorem from the complex spectral theorem. Attempt: Given that : T T* = T* T and T is real . To prove that : T is self adjoint. Proof : T is normal => ||Tv||=||T*v|| . Now, this means from the complex spectral theorem that T has a diagonal matrix with complex entries. But, T is real => while calculating the modulus of the column vectors, we can deduce that the entries on the diagonal are actually real with 0 imaginary components. => T is self adjoint since a self adjoint operator has all real eigen values. Thanks Micromass :) |
| Jan6-13, 11:21 AM | #4 |
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Recognitions:
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The Spectral Theorem in Complex and Real Inner Product Space
Here is an excerpt from the math 4050 notes on my web page:
Cor: Structure of normal operators. Assume T:V-->V is a normal operator on a finite dimensional inner product space. 1) If V is a complex space, with minimal polynomial m(T) = ∏(t-cj)^dj, all cj distinct, then V decomposes into an orthogonal direct sum of eigenspaces Vj = ker(T-cj). I.e., all dj = 1, and there is an orthonormal basis of V in which the matrix of T is diagonal. 2) If V is a real space, with minimal polynomial m = ∏(t-ci)^di∏qj^ej, all ci distinct real scalars, and all qj distinct irreducible real monic quadratic polynomials, then i) V is an orthogonal direct sum of the invariant subspaces ker∏(T-ci) and ker∏qj(T). ii) The eigenspaces ker∏(T-ci) decompose into one dimensional invariant subspaces, and the invariant subspaces ker∏qj(T) decompose into indecomposable invariant two dimensional subspaces, on each of which qj is the minimal polynomial. iii) In particular all di =1, and all ej =1. The matrix of T on the eigenspace ker∏(T-ci) is diagonal with ci along the diagonal, and the matrix of T on ker∏qj(T) is a block matrix with 2 by 2 matrices of form |aj -bj | |bj aj |, along the diagonal, where the roots of qj are aj ± i bj. We get all the theorems from steps 1) and 2) by induction. |
| Jan7-13, 11:38 AM | #5 |
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My another query was this lemma : Suppose T in L(V,V) is self adjoint. Then T has real eigen values.V is a real inner product space Proof : Let n = dim V and choose v in V with v ≠ 0. Then (v, Tv , ......... , T^n v ) cannot be linearly independent because V has dimension n and we have n+1 vectors. Thus, there exist real numbers ao , ......, an, not all 0 such that 0 = aov + a1Tv+.........+anT^n v = c (T^2 +mT + nI ) ( T^2 + rT+sI)(T - k1I) ......... ( T - k2I) the above factorisation is such that m^2<4n and r^2<4s Now, we also know that since T is self adjoint each of the quadratic expressions above is invertible . Hence, the roots lie amongst the linear expressions. However, How can the linear expressions guarantee a real root ( Although i can give an another proof to validate that a self adjoint does have real eigen values but does this expression solely substantiate the cause of T having real eigen values ? ) . Only when the degree of the above equation n is odd , can we be sure that it would by force, have a real eigen value else, we can't be sure. I would love to hear your views about this. Thanks. |
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