Inner product is anti-linear in second argument
Dependencies:
- Inner product space
- /complex-numbers/conjugation-is-homomorphic
Let $V$ be an inner-product space. The inner product is anti-linear in the second argument. This means that:
- $\langle \mathbf{u}, a \mathbf{v} \rangle = \overline{a}\langle \mathbf{u}, \mathbf{v} \rangle$.
- $\langle \mathbf{u}, \mathbf{v_1} + \mathbf{v} _2 \rangle = \langle \mathbf{u}, \mathbf{v_1} \rangle + \langle \mathbf{u}, \mathbf{v} _2 \rangle$.
Proof
\begin{align} & \langle \mathbf{u}, a \mathbf{v} \rangle \\ &= \overline{\langle a \mathbf{v}, \mathbf{u} \rangle} \tag{by conjugate symmetry} \\ &= \overline{a\langle \mathbf{v}, \mathbf{u} \rangle} \tag{by linearity in first argument} \\ &= \overline{a}\overline{\langle \mathbf{v}, \mathbf{u} \rangle} \tag{conjugation is homomorphic} \\ &= \overline{a} \langle \mathbf{u}, \mathbf{v} \rangle \tag{by conjugate symmetry} \end{align}
\begin{align} & \langle \mathbf{u}, \mathbf{v_1} + \mathbf{v_2} \rangle \\ &= \overline{\langle \mathbf{v_1} + \mathbf{v_2}, \mathbf{u} \rangle} \tag{by conjugate symmetry} \\ &= \overline{\langle \mathbf{v_1}, \mathbf{u} \rangle + \langle \mathbf{v_2}, \mathbf{u} \rangle} \tag{by linearity in first argument} \\ &= \overline{\langle \mathbf{v_1}, \mathbf{u} \rangle} + \overline{\langle \mathbf{v_2}, \mathbf{u} \rangle} \tag{conjugation is homomorphic} \\ &= \langle \mathbf{u}, \mathbf{v_1} \rangle + \langle \mathbf{u}, \mathbf{v_2} \rangle \tag{by conjugate symmetry} \end{align}
Dependency for:
- Extreme direction of convex cone as extreme point of intersection with hyperplane
- Symmetric operator iff hermitian
- Symmetric operator on V has a basis of orthonormal eigenvectors
- All eigenvalues of a symmetric operator are real
- x and y are parallel iff ∥x∥²∥y∥² = |< x, y >|².
- Pythagorean theorem
- Cauchy-Schwarz Inequality
- Joining orthogonal linindep sets
Info:
- Depth: 5
- Number of transitive dependencies: 6
Transitive dependencies:
- /complex-numbers/conjugation-is-homomorphic
- Group
- Ring
- Field
- Vector Space
- Inner product space