feat: add CMA-ES sampler behind cma-es feature flag

Implement CMA-ES (Covariance Matrix Adaptation Evolution Strategy) as a
new sampler for continuous optimization. Uses nalgebra for matrix
operations and implements the full Hansen 2016 algorithm: mean update,
evolution paths, covariance matrix adaptation, and cumulative step-size
adaptation.

Key features:
- Builder API with configurable sigma0, population_size, and seed
- Three-phase state machine: discovery, active sampling, generation update
- Rejection sampling with bounds clipping fallback
- Log-scale and step parameter support via internal-space mapping
- Categorical parameters handled via random sampling fallback
- Numerical robustness: eigenvalue clamping, symmetry enforcement

Cargo.toml

@@ -25,6 +25,7 @@ serde = { version = "1", features = ["derive"], optional = true }
 serde_json = { version = "1", optional = true }
 tracing = { version = "0.1", optional = true }
 sobol_burley = { version = "0.5", optional = true }
+nalgebra = { version = "0.33", optional = true }
 
 [features]
 default = []
@@ -33,6 +34,7 @@ derive = ["dep:optimizer-derive"]
 serde = ["dep:serde", "dep:serde_json"]
 tracing = ["dep:tracing"]
 sobol = ["dep:sobol_burley"]
+cma-es = ["dep:nalgebra"]
 
 [dev-dependencies]
 tokio = { version = "1", features = ["rt-multi-thread", "macros", "time"] }