feat: scaffold FCES-native C++ project with libtorch integration

- CMakeLists.txt with libtorch, GoogleTest, GoogleBenchmark, OpenMP, pybind11
- Header files: config, controller, population, fitness, evolution, spectral, oscillation, telemetry, optimizer
- Source implementations: controller (full micro-MLP forward pass, mutation, crossover), fitness (Welford's algorithm), oscillation (DFT), spectral (SVD rank), optimizer (sign-SGD stub)
- Tests: controller, population, fitness, optimizer (Google Test)
- Benchmarks: evolve throughput, optimizer step (Google Benchmark)
- Examples: simple optimization, PyTorch/libtorch integration
- Python extension: pybind11 bindings with setup.py
- README with architecture diagram and build instructions

include/fces/optimizer.hpp

@@ -0,0 +1,87 @@
+#pragma once
+
+/**
+ * @file optimizer.hpp
+ * @brief FCESOptimizer — the main entry point. libtorch-compatible optimizer.
+ */
+
+#include <torch/torch.h>
+#include <memory>
+#include <vector>
+#include <string>
+
+#include "config.hpp"
+#include "population.hpp"
+#include "fitness.hpp"
+#include "evolution.hpp"
+#include "spectral.hpp"
+#include "oscillation.hpp"
+#include "telemetry.hpp"
+
+namespace fces {
+
+/**
+ * FCESOptimizer — Fuzzy Controlled Evolutionary Search V49.0 (C++ Port).
+ *
+ * Usage:
+ *   auto optimizer = FCESOptimizer(model->parameters(), FCESConfig{}.set_lr(1.6e-3));
+ *   // In training loop:
+ *   optimizer.zero_grad();
+ *   auto loss = model->forward(input);
+ *   loss.backward();
+ *   optimizer.step();
+ *   optimizer.update_fitness(loss.item<float>());
+ */
+class FCESOptimizer : public torch::optim::Optimizer {
+public:
+    explicit FCESOptimizer(
+        std::vector<torch::Tensor> params,
+        FCESConfig config = FCESConfig{}
+    );
+
+    /// Perform a single optimization step
+    torch::Tensor step(LossClosure closure = nullptr) override;
+
+    /// Update evolutionary fitness with current loss
+    void update_fitness(float loss);
+
+    /// Backup model weights to CPU RAM
+    void backup_to_ram();
+
+    /// Restore model weights from CPU RAM backup
+    void restore_from_ram();
+
+    /// Get current step count
+    int step_count() const { return step_counter_; }
+
+    /// Calculate model sparsity
+    float calculate_sparsity() const;
+
+private:
+    FCESConfig config_;
+    Population population_;
+    FitnessEngine fitness_engine_;
+    FuzzyFitnessEvaluator fitness_evaluator_;
+    std::unique_ptr<EvolutionManager> evolution_manager_;
+    OscillationDetector oscillation_detector_;
+    RunningStats grad_norm_tracker_;
+
+    // State
+    int step_counter_ = 0;
+    float ema_loss_ = 0.0f;
+    float last_step_loss_ = 0.0f;
+    float best_loss_window_ = std::numeric_limits<float>::infinity();
+    float rollback_ema_ = 0.0f;
+    int stagnation_counter_ = 0;
+    float last_loss_velocity_ = 0.0f;
+
+    // RAM backup
+    std::vector<torch::Tensor> ram_backup_;
+
+    // Internal methods
+    void gather_stats();
+    void apply_parameter_updates(const torch::Tensor& actions);
+    void handle_rollback();
+};
+
+}  // namespace fces