I have some 2D distribution descretized to equal areas. I am trying to minimize the maximum eigenvalue of the second moment which I know will be positive definite. I have n variables d_i which represent the density at each point z_i (known) and t which represents the largest eigenvalue of the second moment. There are also some constraints on the density and mass

- m is the mass, a function of d_i
- \mu the first moment, a function of m, d_i, z_i

The second moment should be the PSD matrix defined by

\Sigma= \sum_{i = 1}^n d_i * (z_i - \mu)(z_i - \mu)^T

minimize t

subject

\Sigma <= tI

m == m_{total}

d_i <= d_{max}

However, I get the `Invalid quadratic form(s): not a square.`

error. I see why this is happening, but I am unsure to get around this.

```
function Sigma = second_moment(d, Z, mu)
Sigma = d(1) * (Z(:, 1) - mu) * (Z(:, 1) - mu)';
for i = 2:len(d)
Sigma = Sigma + d(i) * (Z(:, i) - mu) * (Z(:, i) - mu)';
end
end
```