feat(ode): automatic differentiation for Jacobians

[Ryan-D-Gast]

🎯 What
Adds optional automatic differentiation (AD) support for Jacobians in the ODE trait using num-dual.
This implementation provides a jacobian_ad method that can be implemented to return exact Jacobians without finite differences.

📊 Coverage
Added a unit test test_jacobian_ad_exact validating that dual-number-based Jacobians produce exact answers compared to the default finite-difference implementation.

✨ Result
Resolves #72. Integrates num-dual to compute Jacobians optimally, benefiting stiff solvers that compute Jacobians iteratively.

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PR created automatically by Jules for task 10718081313258689296 started by @Ryan-D-Gast

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