The latter returns a cholesky factor object (which is not a subtype of abstract array), instead of a lower triangular matrix. You can extract it with

```
L = cholfact([DeltaT rho*DeltaT;rho*DeltaT DeltaT], :L)
Lmatrix = L[:L]
```

Alternatively, these work:

```
L = cholfact([DeltaT rho*DeltaT;rho*DeltaT DeltaT])[:L]
L = cholfact([DeltaT rho*DeltaT;rho*DeltaT DeltaT], :L)[:L]
```

If performance matters, go with the latter of these two. The former computes the upper triangular, and then transposes it while the latter gets the lower triangular directly.

For a 4000x4000 matrix, this makes the difference between 262/315 and 185/187 ms minimum/median on my computer.

Extra allocations of non-lazy tranpose on 0.6.2 is why the minimum/median gap is so big for calculating the upper triangle and transposing.

On 0.7 it was 270/271 and 203/204, respectively.

Syntax was updated to `cholfact(Hermitian(X, :L)).L`

.

Memory requirements did not go down because `.L`

still transposed the data when using `cholfact(Hermitian(X)).L`

.