{"nodes": [{"id": "ml_structured_latent_basis", "label": "The Structured Latent Basis", "title": "The Structured Latent Basis: Feature Engineering as Basis Selection", "color": "#f59e0b", "domain": "core", "lean": false, "size": 8}, {"id": "fin_spectral_ir_pricing", "label": "An Audited Contract Boundary for COS ...", "title": "An Audited Contract Boundary for COS Caplet Pricing", "color": "#6b7280", "domain": "quantitative_finance", "lean": true, "size": 8}, {"id": "sgd", "label": "Machine-Checked Scalar Foundations fo...", "title": "Machine-Checked Scalar Foundations for SGD Analysis", "color": "#6b7280", "domain": "optimization and formal methods", "lean": true, "size": 8}, {"id": "core_the_latent", "label": "The Latent", "title": "The Latent: Finite Sufficient Representations of Smooth Systems", "color": "#f59e0b", "domain": "core", "lean": false, "size": 25}, {"id": "nt_bsd", "label": "Conditional BSD Implications with Twe...", "title": "Conditional BSD Implications with Twelve Explicit Debt Assumptions", "color": "#6b7280", "domain": "number_theory", "lean": true, "size": 8}, {"id": "ind_verified_design_certificates", "label": "From Design Points to Machine-Checked...", "title": "From Design Points to Machine-Checked Parameter Regions: Reusable Certificate Templates for Engineering Models", "color": "#10b981", "domain": "verification", "lean": true, "size": 8}, {"id": "math_latent_path_integral", "label": "A Finite-Dimensional Bounded-Perturba...", "title": "A Finite-Dimensional Bounded-Perturbation Certificate", "color": "#6b7280", "domain": "mathematics", "lean": true, "size": 23}, {"id": "fin_fenton_solved", "label": "The Fenton Distribution", "title": "The Fenton Distribution: An Elementary Representation", "color": "#3b82f6", "domain": "finance", "lean": true, "size": 11}, {"id": "ml_self_improvement", "label": "Conditional Bounds on AI Self-Improve...", "title": "Conditional Bounds on AI Self-Improvement in an Antitone Threshold Model", "color": "#10b981", "domain": "verification", "lean": true, "size": 8}, {"id": "phy_smale6", "label": "Toward Dimension-Independent Finitene...", "title": "Toward Dimension-Independent Finiteness of Central Configurations for Positive Masses: A Scope-Audited Reduction with Named Open Bridges", "color": "#10b981", "domain": "verification", "lean": false, "size": 11}, {"id": "phy_spectral_error_mitigation", "label": "Spectral Error Mitigation", "title": "Spectral Error Mitigation: Model-Based Noise Inversion for Quantum Computers via Cluster Lindblad", "color": "#ef4444", "domain": "physics", "lean": false, "size": 8}, {"id": "phy_m_theory_dimensions", "label": "Formal Koide Structure", "title": "Formal Koide Structure: Mass Bounds, Generation Counting, and Neutrino Predictions from the Z_N Ansatz", "color": "#10b981", "domain": "verification", "lean": true, "size": 8}, {"id": "nt_riemann_hypothesis", "label": "Toward the Riemann Hypothesis", "title": "Toward the Riemann Hypothesis: A Superquadratic-Growth Framework for Zeta Moments and its Limits", "color": "#ec4899", "domain": "math", "lean": true, "size": 14}, {"id": "phy_exact_3body_solution", "label": "Toward an Exact Latent Encoding of th...", "title": "Toward an Exact Latent Encoding of the Gravitational Three-Body Problem", "color": "#ef4444", "domain": "physics", "lean": false, "size": 8}, {"id": "phy_nbody_latent_solution", "label": "A Finite Latent Framework for the Gra...", "title": "A Finite Latent Framework for the Gravitational N-Body Problem", "color": "#ef4444", "domain": "physics", "lean": false, "size": 8}, {"id": "fin_harvestability", "label": "Harvestability", "title": "Harvestability", "color": "#10b981", "domain": "verification", "lean": true, "size": 14}, {"id": "fin_equity_premium", "label": "Resolving the Equity Premium Requires...", "title": "Resolving the Equity Premium Requires at Least Two Dimensions: A Machine-Checked Class No-Go and a Term-Structure Discriminator", "color": "#10b981", "domain": "verification", "lean": true, "size": 8}, {"id": "nt_rh_path1_fourier_euler", "label": "The Riemann Hypothesis via Fourier-Euler Product", "title": "The Riemann Hypothesis via Fourier-Euler Product: A Short Conditional Reduction", "color": "#ec4899", "domain": "math", "lean": true, "size": 11}, {"id": "nt_rh_path2_gue", "label": "Full Density of Zeta Zeros on the Cri...", "title": "Full Density of Zeta Zeros on the Critical Line via GUE Universality", "color": "#ec4899", "domain": "math", "lean": false, "size": 11}, {"id": "fin_projected_generator_method", "label": "The Projected-Generator Method for Pa...", "title": "The Projected-Generator Method for Path-Dependent Derivative Pricing", "color": "#3b82f6", "domain": "finance", "lean": true, "size": 11}, {"id": "ml_icl_architecture", "label": "Architectural Optimizations of the In...", "title": "Architectural Optimizations of the In-Context Gradient-Descent Mechanism", "color": "#6b7280", "domain": "machine_learning", "lean": true, "size": 8}, {"id": "ml_icl_capacity_scaling", "label": "Capacity, Scaling, and Grokking from ...", "title": "Capacity, Scaling, and Grokking from the In-Context Learning = Gradient Descent Mechanism", "color": "#6b7280", "domain": "machine_learning", "lean": true, "size": 17}, {"id": "ml_icl_dynamics_inference", "label": "Training Dynamics and Inference Guara...", "title": "Training Dynamics and Inference Guarantees of the In-Context Gradient-Descent Mechanism", "color": "#6b7280", "domain": "machine_learning", "lean": true, "size": 8}, {"id": "ml_in_context_gradient_descent", "label": "When In-Context Learning Implements G...", "title": "When In-Context Learning Implements Gradient Descent: A Learned Mechanism, Mechanically Verified and Empirically Tested", "color": "#6b7280", "domain": "machine_learning", "lean": true, "size": 14}, {"id": "fin_dimension_collapse", "label": "Endogenous Dimension Collapse", "title": "Endogenous Dimension Collapse: A Fold Bifurcation in Market Risk Structure", "color": "#3b82f6", "domain": "finance", "lean": false, "size": 8}, {"id": "prob_ips_scp_palm", "label": "Explicit Flat Palm Weights for the Se...", "title": "Explicit Flat Palm Weights for the Second Class Particle in a Three-State Attractive Interacting Particle System", "color": "#10b981", "domain": "verification", "lean": true, "size": 8}, {"id": "core_theory_universal_spectral_representation", "label": "The Universal Spectral Representation Theorem", "title": "The Universal Spectral Representation Theorem: Breaking the Curse of Dimensionality", "color": "#3b82f6", "domain": "finance", "lean": false, "size": 8}, {"id": "phy_yang_mills_mass_gap", "label": "The Yang-Mills Mass Gap via Gauge Abs...", "title": "The Yang-Mills Mass Gap via Gauge Absorption and Perelman W-Entropy", "color": "#10b981", "domain": "verification", "lean": true, "size": 17}, {"id": "core_latent_of_latents", "label": "The Latent of Latents", "title": "The Latent of Latents: Hierarchical Finite Representations of Knowledge Families", "color": "#8b5cf6", "domain": "ml", "lean": true, "size": 8}, {"id": "fin_basket_options", "label": "Pricing Basket Options via Eigenvalue...", "title": "Pricing Basket Options via Eigenvalue-Conditional Black-Scholes Mixing", "color": "#3b82f6", "domain": "finance", "lean": false, "size": 8}, {"id": "fin_es_backtest_exact", "label": "Contaminated by Construction", "title": "Contaminated by Construction: Separating Simulation Noise from Model Risk in ES Backtests", "color": "#3b82f6", "domain": "finance", "lean": true, "size": 8}, {"id": "fin_exact_var_computational", "label": "Deterministic Portfolio VaR Without Monte Carlo", "title": "Deterministic Portfolio VaR Without Monte Carlo: The Eigen-COS Method", "color": "#3b82f6", "domain": "finance", "lean": true, "size": 8}, {"id": "fin_fenton_practical", "label": "Terminal Portfolio Value Distribution...", "title": "Terminal Portfolio Value Distribution to Machine Precision", "color": "#3b82f6", "domain": "finance", "lean": true, "size": 8}, {"id": "fin_return_paradox", "label": "What Is a Return? (Especially When Pr...", "title": "What Is a Return? (Especially When Prices Can Be Negative)", "color": "#3b82f6", "domain": "finance", "lean": true, "size": 8}, {"id": "fin_spectral_importance_sampling", "label": "Spectral Importance Sampling", "title": "Spectral Importance Sampling: Optimal Rare-Event Simulation via Eigenvalue-Conditioned Measure Change", "color": "#3b82f6", "domain": "finance", "lean": false, "size": 14}, {"id": "nt_damped_vinogradov", "label": "Explicit L\u00b2 Bounds for Damped Vinogra...", "title": "Explicit L\u00b2 Bounds for Damped Vinogradov Sums", "color": "#ec4899", "domain": "math", "lean": false, "size": 8}, {"id": "nt_euler_product_smoothness", "label": "The Euler Product Smoothness Theorem", "title": "The Euler Product Smoothness Theorem: Multiplicative Structure Forces Latent Existence", "color": "#ec4899", "domain": "math", "lean": false, "size": 11}, {"id": "phy_navier_stokes_latent", "label": "Grade Decomposition and Gevrey Regula...", "title": "Grade Decomposition and Gevrey Regularity for Navier-Stokes: A Machine-Checked Conditional Framework", "color": "#10b981", "domain": "verification", "lean": true, "size": 8}, {"id": "phy_navier_stokes_regularity", "label": "Global Regularity for the Three-Dimen...", "title": "Global Regularity for the Three-Dimensional Navier-Stokes Equations via Direction Coherence and Dyadic W-Entropy Weakening", "color": "#6b7280", "domain": "mathematical physics", "lean": false, "size": 8}, {"id": "phy_practical_pade_3body", "label": "Practical Pad\u00e9 Representations of the...", "title": "Practical Pad\u00e9 Representations of the Gravitational Three-Body Problem", "color": "#ef4444", "domain": "physics", "lean": true, "size": 8}, {"id": "phy_quantum_tuna9_parity", "label": "A refuted-and-vindicated pre-registra...", "title": "A refuted-and-vindicated pre-registration test of a spectral error model on a superconducting processor", "color": "#ef4444", "domain": "physics", "lean": false, "size": 8}, {"id": "nt_rh_latent_existence", "label": "A Conditional Moment-Based Diagnostic...", "title": "A Conditional Moment-Based Diagnostic for the Riemann Hypothesis", "color": "#ec4899", "domain": "math", "lean": false, "size": 8}, {"id": "fin_tensor_spectral", "label": "The Spectral Tensor Representation of...", "title": "The Spectral Tensor Representation of Stochastic Processes", "color": "#3b82f6", "domain": "finance", "lean": false, "size": 8}, {"id": "fin_fenton_spectral", "label": "The Spectral Lognormal Distribution", "title": "The Spectral Lognormal Distribution", "color": "#3b82f6", "domain": "finance", "lean": true, "size": 8}, {"id": "ml_knowledge_artifacts_algebra", "label": "The Knowledge Artifact and Knowledge ...", "title": "The Knowledge Artifact and Knowledge Algebra of Machine Learning Models", "color": "#8b5cf6", "domain": "ml", "lean": false, "size": 11}, {"id": "phy_fundamental_constants_as_grade_ratios", "label": "Fundamental Constants as Grade-Ratio ...", "title": "Fundamental Constants as Grade-Ratio Hypotheses", "color": "#ef4444", "domain": "physics", "lean": true, "size": 14}], "edges": [{"from": "math_latent_path_integral", "to": "core_the_latent"}, {"from": "math_latent_path_integral", "to": "phy_navier_stokes_regularity"}, {"from": "nt_rh_path1_fourier_euler", "to": "nt_rh_path2_gue"}, {"from": "ml_icl_architecture", "to": "ml_in_context_gradient_descent"}, {"from": "ml_icl_capacity_scaling", "to": "ml_in_context_gradient_descent"}, {"from": "ml_icl_dynamics_inference", "to": "ml_in_context_gradient_descent"}, {"from": "ml_in_context_gradient_descent", "to": "sgd"}, {"from": "phy_yang_mills_mass_gap", "to": "phy_navier_stokes_latent"}, {"from": "fin_spectral_importance_sampling", "to": "fin_harvestability"}, {"from": "ml_knowledge_artifacts_algebra", "to": "sgd"}]}