Solving the sparse system is returning a Matrix while converting to dense and then solving returns a Vector as expected. Is this the expected behavior? Or am I doing something incorrectly?

```
using SparseArrays
# Constructing sparse array
function hess_sparse(x)
return [-sin(x[1] + x[2]) + 1, -sin(x[1] + x[2]), -sin(x[1] + x[2]), -sin(x[1] + x[2]) + 1, 1.0, 1.0, 12*x[5]^2 + 1.0, 1.0]
end
rowval = [1, 1, 2, 2, 3, 4, 5, 6]
colval = [1, 2, 1, 2, 3, 4, 5, 6]
# Constructing sparse vec
function grad_sparse(x::Vector{T}) where T<: Number
return [cos(x[1] + x[2]), cos(x[1] + x[2]), 2*x[3], 1/2, 4*x[5]^3, 1/2]
end
gradinds = [1, 2, 3, 4, 5, 6]
x0 = [1.0, 1.0, 1.0, 1.0, 1.0, 1.0]
n = length(x0)
hess_mat = sparse(rowval, colval, hess_sparse(x0), n, n)
grad_vec = sparsevec(gradinds, grad_sparse(x0), n)
# Dense linear solve returns vector
@show x = Array(hess_mat) \ Array(grad_vec)
# Sparse linear solve returns matrix
@show x = hess_mat \ grad_vec
```