fix: recognize projected-gradient convergence in diffusion MLE - #35
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Upgrade `basin` to 1.11 and replace `levenberg-marquardt` across calibration, volatility surfaces, and AI surrogates. Preserve evaluation budgets and report the best accepted fit on failures. Add convergence fixtures and Criterion comparisons. Use bounded CGMYSV coordinates to retain convergence, preserve negative-sigma SVI fits, and remove unused BSM history allocations. The measured fits retain their accuracy. Six benchmark cases improve, Heston stays within noise, and variance gamma remains about 3% slower. Closes rust-dd#33
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dancixx
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Treat Basin's ProjectedGradientTolerance as successful MLE convergence. A fit that starts at the Brownian drift optimum previously returned converged=false despite terminating successfully without an iteration; it now reports converged=true and keeps the optimum parameters.
The regression checks the convergence flag, zero iterations and both returned and model parameters. All 278 stats unit tests pass. The branch is reconciled with the ndarray/faer calibrators and their layout/SVD fixes.