Complex Vector Space
A $\mathbf z$ is a complex vector (denoted by $\mathbf z \in \mathbb C^n$)
- when it’s components $z_i$ are Complex Numbers
- complex vectors also form a Vector Space
Norm
How do we define the length of a complex vector?
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$| \mathbf z |^2 = \langle \mathbf z, \mathbf z \rangle = \mathbf z^T \mathbf z$ is no good: - length should be positive - consider, for example, vector $(1, i)$
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$| (1, i) |^2$ would be $1^2 + i^2 = 0$ - what we really want is $\langle \mathbf z, \mathbf z \rangle = \overline {\mathbf z}^T \mathbf z$ - where $\overline {\mathbf z}$ is a Complex Conjugate, i.e. $\overline {\mathbf z} = (\overline z_1, \ … \ , \overline z_n)$
- this way each component of $\langle \mathbf z, \mathbf z \rangle$ contributes a strictly positive number to the overall dot product
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so $| (1, i) |^2$ is $1 - i^2 = 2$ - thus, $| (1, i) | = \sqrt{2}$
Hermitian
The way to transpose and take the conjugate at the same time
- $\mathbf z^H$ is $\overline {\mathbf z}^T$
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so we say $| \mathbf z |^2 = \mathbf z^H \mathbf z = \sum z_i ^2$ - hermitian operator also applies to matrices - $A^H$ is $\overline A^T$
Inner Product
The same for the dot product
- $\langle x, y \rangle$ is not $\mathbf x^T \mathbf y$
- it’s $\langle x, y \rangle = \mathbf x^H \mathbf y$
Symmetric Matrices
What about symmetric matrices in $\mathbb C^{n \times n}$?
- The definition that $A$ is symmetric if $A^T = A$ is for $\mathbb R$, not $\mathbb C$
- the complex version of symmetry is $\overline {A}^T = A$, or $A^H = A$ 0 using the Hermitian operator
- note that diagonal of a symmetric matrix must be real, because otherwise real values are complex conjugates of each others
Unitary Matrices
Can a complex matrix be orthogonal?
- $Q^T Q = I$ is orthogonal matrix for $\mathbb R$
- what about $\mathbb C$?
- yes, it’s possible: $Q^H Q = I$ and all it’s columns $\mathbf q_1, \ … \ , \mathbf q_n$ are orthonormal
- vectors $\mathbf q_1, \ … \ , \mathbf q_n$ are orthonormal when $\mathbf q_i^H \mathbf q_j = \begin{cases} 1 & \text{ if } i = j \ 0 & \text{ if } i \ne j \end{cases}$
- but here instead of “orthogonal” they are usually called “unitary” matrices