hey,

I was trying to reconstruct the Hamiltonian from a covariance matrix but I always get nan values. this function implements the conversion. I checked and I realized that it’s the “atanh” that causes the problem. is there a way to overcome this issue??

I’m using the latest version of strawberryfields from the master

here is a simple script to produce the same error:

```
prog = sf.Program(1)
amp = .7
np.random.seed(5)
x = np.random.rand(1)
with prog.context as q:
sf.ops.DisplacedSqueezed(r=amp,p=x) | q[0]
eng = sf.Engine('gaussian')
result = eng.run(prog)
cov = result.state.cov()
print(sf.decompositions.covmat_to_hamil(cov))
```