Hi!

I am having trouble with the section * a)* of the exercise. I believe I understood correctly how to build the

*matrix. First we should substract the alpha coefficients from the zero vector and divide it by its norm. This will result in the state that will be given to the householder function to get the*

**PREPARE***matrix.*

**PREPARE**```
zero_vec = np.array([1] + [0]*(2**k_bits - 1))
state = (zero_vec - alpha_list) / np.linalg.norm(zero_vec - alpha_list)
return householder(state)
```

This is the code I use to perform this operation.

I did by hand some calculations and ran the code locally, the results were as follows:

If I did the calculations correctly, these should be the expected * PREPARE* matrices for the corresponding alphas. Nevertheless, I could have made a mistake either on the calculations or on the code, so any help is appreciated .

Cheers,

Erick