# Multiplication by a Haar random unitary two times

Consider a Haar random unitary $$U$$.

I am trying to compute the value (or put a bound on)

$$$$\mathbb{E}\left[\left|\langle 0^{n} |U^{2} |0^{n}\rangle\right|^{2}\right].$$$$

The expectation is taken over the choice of the circuit.

We know that $$$$\mathbb{E}\left[\left|\langle 0^{n} |U |0^{n}\rangle \right|^{2}\right] = \frac{1}{2^{n}}.$$$$

Multiplication by another unitary $$U$$ should "scramble" the probability even more, but what might be a way to prove that?

• "The expectation is taken over the choice of the circuit." Do you mean that you integrate over all Haar-random $U$? If so, are you familiar with unitary designs?
– JSdJ
Commented Jun 10, 2022 at 9:38
• A wild guess- a Haar random unitary applied twice has the same distribution as another Haar random unitary. I would bet that there’s a one-one correspondence between the two, and applying a given unitary twice has the same expectation as applying it once. What would “more scrambled” even mean? Commented Jun 10, 2022 at 12:01
• I don’t think unitary designs talk of applying the same unitary twice. Commented Jun 10, 2022 at 15:07

There is an explicit formula for the integral with respect to the Haar measure of any polynomial in the entries of a unitary and its conjugate, due to Collins and Śniady:

Benoît Collins and Piotr Śniady. Integration with Respect to the Haar Measure on Unitary, Orthogonal and Symplectic Group. Communications in Mathematical Physics 264: 773-795, 2006. [arXiv:math-ph/0402073]

I won't actually write down the formula in this answer, it can be found in the paper. For high-degree polynomials you need to know some things about the representation theory of the symmetric group to evaluate it, but for low-degree polynomials it's easy enough to just look up the required values.

Let me rewrite the question using notation that matches with Collins and Sniady: we'll assume the rows and columns of the unitary $$U$$ we're integrating over are indexed by the integers $$1,\ldots,d$$, so $$d = 2^n$$, and we'll denote the $$(i,j)$$ entry of $$U$$ by $$U_{i,j}$$. The question asks for the value $$\int \bigl\vert \bigl(U^2\bigr)_{1,1} \bigr\vert^2 \mathrm{d}U$$ where the integral is with respect to Haar measure for $$d\times d$$ unitary matrices.

We need to rewrite the integrand. We have $$\bigl(U^2\bigr)_{1,1} = \sum_{i=1}^d U_{1,i} U_{i,1}$$ and therefore $$\bigl\vert \bigl(U^2\bigr)_{1,1} \bigr\vert^2 = \sum_{i=1}^d\sum_{j=1}^d U_{1,i} U_{i,1} \overline{U_{1,j}} \overline{U_{j,1}}.$$

From the formula of Collins and Sniady, we can conclude this: $$\int U_{1,i} U_{i,1} \overline{U_{1,j}} \overline{U_{j,1}} \, \mathrm{d}U = \begin{cases} \frac{2}{d(d+1)} & i = j = 1\\ \frac{1}{d^2-1} & i = j \not= 1\\ 0 & i\not=j. \end{cases}$$ Therefore, the value we're looking for is $$\int \bigl\vert \bigl(U^2\bigr)_{1,1} \bigr\vert^2 \mathrm{d}U = \frac{2}{d(d+1)} + (d-1) \frac{1}{d^2 - 1} = \frac{d+2}{d(d+1)}.$$

Switching back to the notation in the original question gives $$\mathbb{E}\Bigl[ \bigl\vert \langle 0^n \vert U^2 \vert 0^n\rangle \bigr\vert^2\Bigr] = \frac{2^n + 2}{2^n(2^n+1)} = \frac{2^{n-1} + 1}{2^{n-1}(2^n+1)},$$ which is ever-so-slightly larger than $$1/2^n$$.

So, unless I made a mistake in this calculation (which is a definite possibility — it should be checked carefully), the intuition that applying a unitary twice scrambles the probability more is wrong: it scrambles it slightly less. It's kind of like vitamins: taking twice as much as you need isn't better for you, it's actually a little bit worse.

• maybe an intuitive way to understand this is to observe that unitaries equal/close to the identity are preserved by the squaring operation, while others are not, thus resulting in a distribution more skewed towards matrices close to the identity? At the very least, some quick numerics points in this direction, see i.sstatic.net/KFGA8.png
– glS
Commented Jun 14, 2022 at 15:27
• Thanks, as always, for a great answer! :) @John Watrous Commented Jun 14, 2022 at 22:13