Diagonalizability of Linear Transformations, Multiplicity of Eigenvalues, and the Relationship with Eigenspaces
📂Linear AlgebraDiagonalizability of Linear Transformations, Multiplicity of Eigenvalues, and the Relationship with Eigenspaces
Theorem
Let T:V→V be a linear transformation on a finite-dimensional vector space V. Suppose the characteristic polynomial of T splits and λ1,λ2,…,λk are distinct eigenvalues of T. Then,
T is diagonalizable if and only if, for all i, the multiplicity of λi and the dimension dim(Eλi) of the eigenspace are the same.
T is diagobalizable. ⟺multiplicity of λi=dim(Eλi),∀i
If T is diagonalizable, and if βi is an ordered basis of Eλi, then β=β1∪⋯∪βk is an ordered basis of V containing the eigenvectors of T.
T is diagonalizable if and only if V is the direct sum of the eigenspaces of T.
T is diagobalizable. ⟺V=Eλ1⊕⋯⊕Eλk
Proof
1.
Let mi be the multiplicity of λi. Suppose di=dim(Eλi), n=dim(V).
(⟹)
Assume T is diagonalizable. This is equivalent to saying that there exists a basis of V consisting of the eigenvectors of T. Let β be such a basis of V, consisting of the eigenvectors of T. For each i, let βi=β∩Eλi. In other words, βi is a set of eigenvectors corresponding to the eigenvalue λi that belong to β. Also, suppose ni=∣βi∣. Then, since βi is a linearly independent subset of Eλi, ni≤di holds. Moreover, since the algebraic multiplicity of an eigenvalue is greater or equal to its geometric multiplicity, di≤mi holds. Therefore, n=∣β∣ implies, by adding ni for all i, we get n, and by definition of multiplicity, adding mi for all i also results in n. Therefore,
n=i=1∑kni≤i=1∑kdi≤i=1∑kmi=n
⟹i=1∑k(mi−di)=0
But since mi−di≥0, for all i, mi=di holds.
(⟸)
Suppose that for all i, mi=di holds. Let βi be an ordered basis of Eλi. And let β=β1∪⋯∪βk. Then, because the union of linearly independent sets from different eigenspaces is also linearly independent, β is linearly independent. Also, by assumption, i=1∑kdi=i=1∑kmi=n holds, so β contains n linearly independent eigenvectors. Therefore, β is an ordered basis of V, and T is diagonalizable.
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2.
The proof of (⟸) in 1. already covered this.
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3.
Let λ1,…,λk be distinct eigenvalues of T.
(⟹)
Assume T is diagonalizable. Let γi be an ordered basis of the eigenspace Eλi. Then, by 2., γ1∪⋯∪γk is an ordered basis of V.
Properties of direct sums
Let W1,W2,…,Wk be subspaces of a finite-dimensional vector space V. The following propositions are equivalent:
- V=W1⊕W2⊕⋯⊕Wk
- If γi is an ordered basis of Wi, then γ1∪⋯∪γk is an ordered basis of V.
- There exists an ordered basis γi of Wi such that γ1∪⋯∪γk is an ordered basis of V.
Thus, by the theorem above, V=Eλ1⊕⋯⊕Eλk holds.
(⟸)
Assume V=Eλ1⊕⋯⊕Eλk. Let γi be an ordered basis of Eλi. Then, by the properties of direct sums, γ1∪⋯∪γk is an ordered basis of V. Since this basis consists of eigenvectors, T is diagonalizable.
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