as p varies, for a matrix A with a curious property.
What makes this matrix curious is that its trace is almost equal to its squared Frobenius norm. Adding up diagonal entries is the same as adding up squares of all entries.
This relation extends to powers of A in the following way 1. Write Frobenius norm in terms of
σ
i
, singular values of A
2. Observe the following
Eigenvalues and squared singular values are quite different. They remain different when we raise them to a power p Yet the difference disappears when we add them up. For p=1 equality is proven to hold in expectation by user1551 in the following post p>1 is open. Discussion is on mathoverflow Matrix A is defined as a product of d random projections
Naive way of computing it is 100x slower than it should be, Henrik and Michael give tricks to compute efficiently here