This is Clarabel, compiled to WebAssembly and running in your browser.
The theory is in the conic optimization post.
Stay inside the cone, like me inside my shell.
Interior-point methods stay strictly inside the cone. I stay strictly inside my shell.
Spatulas or forks? Clarabel will tell you. I’d make chanterelles.
Portfolio advice from a snail: diversify. Mine is all chanterelles.
Positive semidefinite: no negative eigenvalues, and no negative thoughts.
Box constraints keep the variables in their box. I keep to my shell.
Try a tighter tolerance in the solver settings. More iterations, more fun.
1 The code is running in the browser using WebAssembly.
Solving Conic Problems using Clarabel1
Clarabel can be used to solve conic problems on the form2 2 Linear, Quadratic, Semidefinite, Second-order cone, Power cone, and Exponential cone programs are all examples of conic programs. To read more about cones and the interior point method behind Clarabel look here.
$$\begin{array}{rl} \text{minimize} & \frac{1}{2}x^\top P x + q^\top x\\[2ex] \text{subject to} & Ax + s = b, \quad s \in \mathcal{K} \end{array}$$
where $\mathcal{K}$ is a composition of convex cones. Try the examples below.