Checkpoint
Eigenvectors and eigenvalues
Twelve questions across the module: finding eigenvectors, what repeated multiplication does, symmetric matrices and singular values. The numbers are new. Work on paper where it helps; the last item is a short piece of code. You pass at 80 percent.
- 1
Which of these are eigenvectors of ? Select every one.
- 2
The matrix has two real eigenvalues. Find the eigenvector for the smaller one, scaled so its first entry is 1.
v - 3
You learn that is an eigenvalue of a square matrix . What does that tell you?
- 4
A matrix has trace 4. Two of its eigenvalues are 2 and . What is its determinant?
det - 5
A matrix has eigenvector with eigenvalue 1 and eigenvector with eigenvalue . Compute .
A^3 x - 6
What is the spectral radius of ?
rho - 7
A matrix has eigenvalues and . You multiply a random vector by 60 times. What happens?
- 8
What is the largest singular value of ? Its eigenvalues are 3 and 0.
sigma 1 - 9
A symmetric matrix has eigenvalues and 2. What are its singular values?
- 10
Centered 2D data has covariance matrix . What is the first principal component, and what fraction of the variance does it capture?
- 11
You approximate a weight matrix by its rank-8 truncated SVD, stored as the 8 columns and the 8 rows . How many numbers do you store?
numbers - 12
Code it Write
gain(A): the largest factor by which the matrixA(any shape) can stretch a vector. Compute it as the square root of the largest eigenvalue of , usingnp.linalg.eigvalsh. Do not usenp.linalg.svdornp.linalg.norm(A, 2).