release(v2.0.0-alpha.1): top-level reorg + bsde/pde/stochastic_control + mean_field/agent_based/inference/optimization

Phase 1 (top-level reorg):
  - matrix_riccati promoted to crate root via re-export
  - new top-level groups: bsde, pde, stochastic_control,
    agent_based, inference, optimization

Phase 2 (bsde):
  - theta_scheme: linear-BSDE theta-scheme
  - deep_bsde_bridge: ConditionalExpectation trait + driver

Phase 3 (pde):
  - fokker_planck: 1D forward FP with conservative central FD
  - hjb_multid: explicit n-D HJB on Cartesian grid (d <= 3)
  - elliptic_fd: 2D Poisson SOR solver

Phase 4 (stochastic_control):
  - optimal_switching: Snell envelope backward induction
  - pontryagin: 1D LQR Riccati shooting
  - two_sided_intensity_control: bilateral intensity control

Phase 5/6 (controls):
  - optimal_control::quadratic_impact_control (closed-form Riccati)
  - stochastic_control::two_sided_intensity_control

Phase 7 (mean_field + agent_based):
  - mean_field::mckean_vlasov: interacting-particle Euler scheme
  - agent_based::mod: generic interacting-agent simulator

Phase 8 (inference + optimization):
  - inference::robust_drift: Huber IRLS drift estimator
  - optimization::generative_calibration_hooks: GenerativeSampler trait
    + Gaussian MMD + finite-diff calibration step

Tests: 38 NEW tests, all passing (165/170 lib total; the 5 pre-existing
failures predate v1.1 and are tracked separately).

Versions bumped: Cargo 2.0.0-alpha.1, pyproject 2.0.0a1.

Deferred to subsequent v2.0.x bumps (parallelisable follow-ups):
PyO3 bindings, executed companion notebooks, Sphinx RST pages,
hfthot-lab-instance propagation.

pyproject.toml

@@ -4,7 +4,7 @@ build-backend = "maturin"
 
 [project]
 name = "optimiz-rs"
-version = "1.1.0"
+version = "2.0.0a1"
 description = "High-performance optimization algorithms in Rust with Python bindings"
 authors = [
     {name = "HFThot Research Lab", email = "contact@hfthot-lab.eu"}