Upload run.py

run.py

@@ -26,6 +26,10 @@ from riemann_vmix.problem_solvers.chebyshev_bias import ChebyshevBiasAnalyzer
 from riemann_vmix.problem_solvers.lehmer_phenomena import LehmerPhenomenaAnalyzer
 from riemann_vmix.problem_solvers.mertens_extremal import MertensExtremalAnalyzer
 from riemann_vmix.problem_solvers.cross_module_analysis import CrossModuleAnalyzer
+from riemann_vmix.problem_solvers.ramanujan_machine import RamanujanMachineSearcher
+from riemann_vmix.problem_solvers.alphafold_math import AlphaFoldMathEvolver
+from riemann_vmix.problem_solvers.cross_entropy_rh import CrossEntropyRHSampler
+from riemann_vmix.problem_solvers.self_play_conjectures import SelfPlayConjectureEngine
 from riemann_vmix.problem_solvers.new_strategies import (
     TransformerPrimeGapPredictor,
     TDAZeroAnalyzer,
@@ -146,6 +150,41 @@ def main():
         all_results['explicit_formula_minimum_zeros'] = min_zeros_results
         print(f"  Results: {json.dumps(min_zeros_results, indent=2, default=str)[:500]}")
 
+    # ─── ADVANCED STRATEGIES (Quantum + Game Theory inspired) ───
+    print("\n[ADVANCED STRATEGIES] Running quantum-inspired and game-theoretic analyses...")
+
+    # Ramanujan Machine: continued fraction search with factorial-reduction heuristic
+    print("\n[ADVANCED 1] Ramanujan Machine — Continued Fraction Discovery")
+    rm = RamanujanMachineSearcher(max_degree=2, max_coeff=5, max_depth=20)
+    rm_results = rm.search(n_candidates=2000)
+    all_results['ramanujan_machine'] = rm_results
+    summaries.append(rm.summary())
+    print(rm.summary())
+
+    # AlphaFold-Math: evolutionary formula discovery for zero spacings
+    print("\n[ADVANCED 2] AlphaFold-Math — Evolutionary Formula Discovery")
+    afm = AlphaFoldMathEvolver(all_zeros_imag)
+    afm_results = afm.evolve(population_size=30, generations=20, sample_size=500)
+    all_results['alphafold_math'] = afm_results
+    summaries.append(afm.summary())
+    print(afm.summary())
+
+    # Cross-entropy rare event simulation for RH consistency
+    print("\n[ADVANCED 3] Cross-Entropy Rare Event Simulation for RH")
+    ce = CrossEntropyRHSampler(all_zeros_imag)
+    ce_results = ce.run_simulation(n_iterations=10, n_samples=500, window_size=500)
+    all_results['cross_entropy_rh'] = ce_results
+    summaries.append(ce.summary())
+    print(ce.summary())
+
+    # Self-play conjecture engine
+    print("\n[ADVANCED 4] Self-Play Conjecture Generator")
+    sp = SelfPlayConjectureEngine(all_zeros_imag)
+    sp_results = sp.run_self_play(n_rounds=3)
+    all_results['self_play_conjectures'] = sp_results
+    summaries.append(sp.summary())
+    print(sp.summary())
+
     # ─── NEW STRATEGIES ───
     new_strategy_results = []
     if cfg['new_strategies']['transformer_prime_gaps']:
@@ -203,6 +242,10 @@ def main():
             "TDA persistent homology applied to zeta zero spacings.",
             "Information-theoretic entropy of zero spacings computed at multiple scales.",
             "Lightweight attention mechanism trained on prime gap sequences.",
+            "Ramanujan Machine continued fraction search with factorial-reduction heuristic.",
+            "AlphaEvolve-style evolutionary formula discovery for zero statistics.",
+            "Cross-entropy rare event simulation estimates RH stability probability.",
+            "Self-play conjecture engine verifies/falsifies 10 zero hypotheses automatically.",
         ],
     }