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A Basis for 3 by 3 Symmetric Matrices

Subspaces and dimensions — MIT 18.06 · Ch.1 / 1

A Basis for 3x3 Symmetric and Antisymmetric Matrices

The Vector Space of 3x3 Matrices (M)

The set of all real 3x3 matrices forms a vector space M of dimension 9.


Subspace: Symmetric Matrices (S)

A matrix S is symmetric if S^T = S.

Basis for S (6 matrices):

S1=(100000000)S2=(010100000)S3=(001000100)S_1 = \begin{pmatrix} 1 & 0 & 0 \\ 0 & 0 & 0 \\ 0 & 0 & 0 \end{pmatrix} \quad S_2 = \begin{pmatrix} 0 & 1 & 0 \\ 1 & 0 & 0 \\ 0 & 0 & 0 \end{pmatrix} \quad S_3 = \begin{pmatrix} 0 & 0 & 1 \\ 0 & 0 & 0 \\ 1 & 0 & 0 \end{pmatrix} S4=(000010000)S5=(000001010)S6=(000000001)S_4 = \begin{pmatrix} 0 & 0 & 0 \\ 0 & 1 & 0 \\ 0 & 0 & 0 \end{pmatrix} \quad S_5 = \begin{pmatrix} 0 & 0 & 0 \\ 0 & 0 & 1 \\ 0 & 1 & 0 \end{pmatrix} \quad S_6 = \begin{pmatrix} 0 & 0 & 0 \\ 0 & 0 & 0 \\ 0 & 0 & 1 \end{pmatrix}
  • Three diagonal matrices: diag(1,0,0), diag(0,1,0), diag(0,0,1)
  • Three off-diagonal matrices: 1 at (i,j) and (j,i) for i < j
  • Dimension of S = 6
  • Linearly independent, and their combinations span every symmetric 3x3 matrix

Subspace: Antisymmetric (Skew-Symmetric) Matrices (AS)

A matrix A is antisymmetric (or skew-symmetric) if A^T = -A.

Properties

  • Diagonal entries must be zero: a_{ii} = -a_{ii} implies a_{ii} = 0
  • Off-diagonal entries satisfy a_{ij} = -a_{ji} for i ≠ j

General form of a 3x3 antisymmetric matrix:

A=(0aba0cbc0)A = \begin{pmatrix} 0 & a & b \\ -a & 0 & c \\ -b & -c & 0 \end{pmatrix}

Three free parameters (a, b, c) give dimension 3.

Basis for AS (3 matrices):

A1=(010100000)A2=(001000100)A3=(000001010)A_1 = \begin{pmatrix} 0 & 1 & 0 \\ -1 & 0 & 0 \\ 0 & 0 & 0 \end{pmatrix} \quad A_2 = \begin{pmatrix} 0 & 0 & 1 \\ 0 & 0 & 0 \\ -1 & 0 & 0 \end{pmatrix} \quad A_3 = \begin{pmatrix} 0 & 0 & 0 \\ 0 & 0 & 1 \\ 0 & -1 & 0 \end{pmatrix}
  • Dimension of AS = 3

S and AS Together Give a Basis for All 3x3 Matrices

Every 3x3 matrix M can be uniquely decomposed into a symmetric part and an antisymmetric part:

S=M+MT2,A=MMT2S = \frac{M + M^T}{2}, \qquad A = \frac{M - M^T}{2}
  • S is symmetric (S = S^T)
  • A is antisymmetric (A = -A^T)
  • M = S + A

The combined basis S1,,S6,A1,A2,A3{S_1, \ldots, S_6, A_1, A_2, A_3} has 6 + 3 = 9 elements, matching the dimension of the full space of 3x3 matrices.


Example: Upper-Triangular All-Ones Matrix

Let U be the 3x3 upper-triangular matrix with all ones on and above the diagonal:

U=(111011001)U = \begin{pmatrix} 1 & 1 & 1 \\ 0 & 1 & 1 \\ 0 & 0 & 1 \end{pmatrix}

Decomposition into S + AS

Symmetric part (S = (U + U^T)/2):

UT=(100110111),U+UT=(211121112)U^T = \begin{pmatrix} 1 & 0 & 0 \\ 1 & 1 & 0 \\ 1 & 1 & 1 \end{pmatrix}, \qquad U + U^T = \begin{pmatrix} 2 & 1 & 1 \\ 1 & 2 & 1 \\ 1 & 1 & 2 \end{pmatrix} S=U+UT2=(112121211212121)S = \frac{U + U^T}{2} = \begin{pmatrix} 1 & \frac12 & \frac12 \\[4pt] \frac12 & 1 & \frac12 \\[4pt] \frac12 & \frac12 & 1 \end{pmatrix}

Antisymmetric part (A = (U - U^T)/2):

UUT=(011101110)U - U^T = \begin{pmatrix} 0 & 1 & 1 \\ -1 & 0 & 1 \\ -1 & -1 & 0 \end{pmatrix} A=UUT2=(012121201212120)A = \frac{U - U^T}{2} = \begin{pmatrix} 0 & \frac12 & \frac12 \\[4pt] -\frac12 & 0 & \frac12 \\[4pt] -\frac12 & -\frac12 & 0 \end{pmatrix}

Check: U = S + A

(112121211212121)+(012121201212120)=(111011001)=U\begin{pmatrix} 1 & \frac12 & \frac12 \\ \frac12 & 1 & \frac12 \\ \frac12 & \frac12 & 1 \end{pmatrix} + \begin{pmatrix} 0 & \frac12 & \frac12 \\ -\frac12 & 0 & \frac12 \\ -\frac12 & -\frac12 & 0 \end{pmatrix} = \begin{pmatrix} 1 & 1 & 1 \\ 0 & 1 & 1 \\ 0 & 0 & 1 \end{pmatrix} = U

Summary

Subspace Dimension Basis Elements
Symmetric (S) 6 diag(1,0,0)diag(1,0,0), E12+E21E_{12}+E_{21}, E13+E31E_{13}+E_{31}, diag(0,1,0)diag(0,1,0), E23+E32E_{23}+E_{32}, diag(0,0,1)diag(0,0,1)
Antisymmetric (AS) 3 E12E21E_{12}-E_{21}, E13E31E_{13}-E_{31}, E23E32E_{23}-E_{32}
All 3x3 matrices (M) 9 Union of S and AS bases
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© MIT OpenCourseWare  |  18.06 Linear Algebra  |  Gilbert Strang  |  Spring 2010
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