Function minimize_by_settling 

pub fn minimize_by_settling(
    q: &[Vec<f64>],
    b: &[f64],
    target: &AnalogTarget,
    opts: &SettleOpts,
) -> Result<MinimizeOutcome, AnaLowerError>

minimize ½xᵀQx + bᵀx by settling ẋ = −(Q·x + b) — the SAME force network with the signs flipped (the tiles generate the negative gradient). The admission gate is R1’s; the CERTIFICATE is R2’s theorem: for spectrum ≥ μ > 0 (exact Gershgorin row bound over ℚ), f(x̂) − f* ≤ ‖∇f(x̂)‖²/(2μ) — a gradient residual becomes a distance-to-optimum bound. Candidate semantics: the bound is the claim; no optimality field exists to lie with.