Group Theory and Linear Algebra

Arun Ram
Department of Mathematics and Statistics
University of Melbourne
Parkville, VIC 3010 Australia
aram@unimelb.edu.au

Last updated: 21 September 2014

Lecture 16: Orthogonal complements and adjoints

Let V be a vector space over ℂ. Let ⟨,⟩:V×V→ℂ be a positive definite Hermitian form. Let W be a subspace of V. The orthogonal complement to W is W⊥= { v∈V | if w∈W  then ⟨v,w⟩ =0 } .

(a) W⊥ is a subspace of V.
(b) V=W⊕W⊥.

Proof.

(a)
To show:
(aa) If u1,u2∈W⊥ then u1+u2∈W⊥.
(ab) If u∈W⊥ and c∈ℂ then cu∈W⊥.
(aa) Assume u1,u2∈W⊥.
To show: u1+u2∈W⊥.
To show: If w∈W then ⟨u1+u2,w⟩=0.
Assume w∈W.
To show: ⟨u1+u2,w⟩=0. ⟨u1+u2,w⟩ = ⟨u1,w⟩+ ⟨u2,w⟩ = 0+0,since u1,u2 ∈W⊥ = 0.
(ab) Assume u∈W⊥ and c∈ℂ.
To show: cu∈W⊥.
To show: If w∈W then ⟨cu,w⟩=0.
Assume w∈W.
To show: ⟨cu,w⟩=0. ⟨cu,w⟩ = c⟨u,w⟩ = c·0,since u∈W⊥ = 0.
(b)
To show: V=W⊕W⊥.
To show:
(ba) W∩W⊥={0}.
(bb) W+W⊥=V.
Choose an orthonormal basis of W (by Gram-Schmidt).
Extend this to an orthonormal basis of all V (by more Gram-Schmidt). { b1,b2,…,bk ⏞basis of W , bk+1, bk+2,…, bk+ℓ ⏟basis of V } Then {bk+1,bk+2,…,bk+ℓ} is an orthonormal basis of W⊥: If w=c1b1+⋯+ckbk∈W then ⟨bk+i,w⟩ = ⟨ bk+i, c1b1+⋯+ckbk ⟩ = c1⟨bk+i,b1⟩+⋯+ ck⟨bk+i,bk⟩ = c1·0+⋯+ck·0 = 0, so that bk+i∈W⊥.

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Adjoints

Let V be a vector space over C and ⟨,⟩:V×V→ℂ a positive definite Hermitian form. Let f:V→V be a linear transformation. The adjoint of f is a linear transformation f*:V→V such that if u,w∈V then ⟨f(u),w⟩=⟨u,f*(w)⟩.

The linear transformation f:V→V is

• self adjoint, or Hermitian, if f satisfies f=f*,
• an isometry, or unitary, if f satisfies f*f=1,
• normal, if f satisfies f*f=ff*.

Let V be a finite dimensional vector space over ℂ and ⟨,⟩:V×V→ℂ a positive definite Hermitian form. Let f:V→V be a linear transformation and B={b1,…,βk} an orthonormal basis of V. Then Bf*=(Bf‾)t.

If A is a matrix with (i,j) entry Aij then At is a matrix with (i,j) entry Aji.

Let A be a matrix. The transpose of A is the matrix At given by (At)ij=Aji. The conjugate of A is the matrix A‾ given by (A‾)ij =Aij‾. The conjugate transpose of A is the matrix A‾t given by (A‾t)ij =Aji‾.

Proof of the theorem.

If f*(bj)= p1jb1+ p2jb2+⋯+ pkjbk then pij = ⟨f*(bj),bi⟩ = ⟨bi,f*(bj)⟩‾ = ⟨f(bi),bj⟩‾ = ⟨qi1+b1+q2ib2+⋯+qkibk,bj⟩‾ = qji‾. So Bf*=(pij) and Bf=(qij) and (Bf*)ij= pij=qji‾ =(Bf‾t)ij. So Bf*=Bf‾t.

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Let V be a vector space over ℂ which is finite dimensional and let ⟨,⟩:V×V→ℂ be a positive definite Hermitian form. Let f:V→V be a linear transformation. Let g:V→V be a linear transformation. Then

(a) f*V→V is a linear transformation and is unique,
(b) f*+g*=(f+g)*,
(c) (fg)*=g*f*,
(d) If c∈ℂ then (cf)*=c‾f*,
(e) (f*)*.

Idea of proof.

(a) f* has matrix Bf*=(Bf‾)t as given in the theorem.
Let B={b1,…,bk} be an orthonormal basis and let A=Bf*and C=Bg*. Then show that
(b') (A+C‾)t=A‾t+C‾t,
(c') (AC‾)t=C‾tA‾t,
(d') If c∈C then (cA‾)t=c‾A‾t,
(e') (A‾t)‾t=A.

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Notes and References

These are a typed copy of Lecture 16 from a series of handwritten lecture notes for the class Group Theory and Linear Algebra given on August 30, 2011.

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