Source scope: §3.6. Worked numerical examples, experiments, and practice are teaching supplements unless identified as source results.
Direction can survive a transformation
For , the horizontal vector becomes ; the vertical vector becomes . Both remain on their original lines. A negative scale reverses direction.
For a square real matrix , a nonzero vector is an eigenvector with eigenvalue if . Zero is excluded because for every . A zero eigenvalue is allowed: a nonzero direction can collapse to zero.
Not every vector is an eigenvector. Here is not a scalar multiple of . A real matrix need not have real eigenvectors: a quarter-turn rotation has no nonzero real vector on an unchanged line.
Proposition 3: shift, invert, repeat
Source statement and proof. Suppose with .
- For any real , . The same eigenvector has shifted eigenvalue .
- If is invertible, . Invertibility forces , so division gives .
- For every nonnegative integer , . The case uses ; multiplying the th relation by proves the next. If is invertible, applying the same argument to proves the relation for negative integers too.
Source clarification: Proposition 3(iii) prints without repeating the invertibility condition. Negative powers require it. For , the scalar factor is one even when , by the identity-power convention.
Turn a unit vector
Predict the quadratic value before aligning x with an eigenvector.
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Transfer
If , what is ? What is ?
Keep the same vector
They are and . Squaring removes the reversal because two negative scalings produce a positive scaling. The inverse conclusion additionally requires the whole matrix to be invertible.