December 20247 Experiments Completed

MOO-First Experiments

Systematic experiments using Multi-Objective Optimization to validate, refine, or bound framework claims. Each experiment produces honest results regardless of outcome.

CASCADE VALIDATED

Singularity-Skirting MOO

61.9%

Win Rate

CASCADE enables access to "danger zones" near physics singularities where standard MOO fails. The bigeometric derivative D*[1/r] = -1 (constant) allows evaluation where classical calculus diverges.

13/21

Wins

93.4%

Best Gain

10

Domains

k=-1

Optimal

View full CASCADE singularity proof →

Executive Summary

EXP-1: Shock
VERIFIED

Best L2

EXP-2: Conv
VERIFIED

2nd order

EXP-3: k(L)
CORRECTED

R2=0.82

EXP-4: Chaos
NEUTRAL

Matches RK4

EXP-5: Gap
REFINED

BC-dep

EXP-6: Quantum
INVALID

0% unit

EXP-7: Cosmo
CANNOT

H0: 0/9

Methodology: Build on existing infrastructure (37 result files, 8 MOO scripts). Use pymoo NSGA-II for optimization. Document honest outcomes for each experiment.

EXP-1: Shock Tube CFD

VERIFIED

Visual engineering demonstration on the Sod shock tube. Tests meta-calculus flux limiting against classical limiters (minmod, superbee, Van Leer, MC).

CORRECTED: What Really Happened

  • + Sod: 10/30 solutions strictly dominate Van Leer
  • + Shu-Osher: 5.4% L2 improvement over minmod
  • + Statistical: 12.1% +/- 3.1% across 5 seeds
  • + Adaptive k switching works automatically

Critical Failure

  • - Parameters are problem-specific (cross-validation)
  • - Sod params on Shu-Osher: -3.9% WORSE
  • - Only 1D benchmarks tested
  • - Real CFD much more complex
Data: results/shock_tube_dual_moo.json, results/shu_osher_moo.json | Script: simulations/shock_tube_moo.py, simulations/shu_osher_moo.pyFull validated results →

EXP-2: Convergence Order Verification

VERIFIED

Lax equivalence test on 1D linear advection. Measures convergence order via log-log error analysis.

CORRECTED: What Really Happened

  • + Bigeometric achieves 2nd order (order = 1.99)
  • + Matches Lax-Wendroff reference exactly
  • + Meta schemes interpolate via k parameter
  • + All fits have R^2 > 0.99

Critical Failure

  • - Only 1D linear advection tested
  • - Gaussian pulse (smooth IC)
  • - Short time (T = 0.5)
  • - No shock/discontinuity tests
Data: results/convergence_order_verification.json | Script: simulations/convergence_order_verification.py

EXP-5: Spectral Gap Boundary

REFINED

Extended from 9 tests to 200+ configurations. Discovered boundary conditions matter critically.

What Still Holds

  • + Dirichlet BCs: 100% pass rate
  • + Periodic BCs: ~95% pass rate
  • + Symmetric operators: reliable
  • + FRW cosmology cases: safe

Counterexamples Found

  • - Neumann BCs: ~80% pass (20% fail)
  • - Mixed operators + Neumann: gap_ratio = 0.69
  • - First derivatives + Neumann: gap ~ 0
  • - High condition numbers correlate with failures
Data: results/spectral_gap_boundary_moo.json | Script: simulations/spectral_gap_boundary_moo.py

EXP-3: k(L) Mechanism Discovery

BUG FIXED

Tested 14 derived features (8 affine + 6 non-affine). Found intercept bug that caused spurious R^2 differences. All affine features are mathematically equivalent.

Overfitting Analysis

Cross-validation reveals that complex features (sigmoid) achieve high R^2 on interpolated data but catastrophically fail on the 8 true baseline points. Simple log-linear is robust.

Corrected Results

  • + Log-linear: k(L) = -0.015 * log10(L) + 0.19
  • + All affine features have R^2 = 0.8206 (identical)
  • + "Energy density beats log_L" was BUG ARTIFACT
  • + Physical meaning: gradual quantum-classical crossover

Non-Affine Analysis

  • - Sigmoid R^2=0.94... but OVERFITS (8M% LOO error)
  • - Complex features fit interpolation, not truth
  • - Only 8 true baseline points
  • - 18% unexplained variance is genuine noise
Data: results/k_mechanism_discovery.json | Script: simulations/k_mechanism_discovery.py

EXP-4: Lorenz Chaos Preservation

NEUTRAL

Tests whether meta-calculus can preserve Lorenz attractor geometry longer than classical RK4. Measures divergence time, energy drift, and Lyapunov exponent estimation.

What This Shows

  • - Meta-0.3 matches RK4 exactly (100.0 time units)
  • - No improvement over classical method
  • - Higher k values cause early divergence
  • - Chaotic systems resist scheme modifications

Honest Interpretation

  • NEUTRAL: Neither helps nor hurts
  • Exponential error growth dominates
  • This bounds framework capabilities
  • Not all problems benefit from meta-calculus
Data: results/chaos_preservation_moo.json | Script: simulations/chaos_preservation_moo.py
CORRECTED December 2025

Fatal Bug: Forced Normalization Invalidated Results

The original P05 simulation had a critical bug: forced normalization after each timestep (lines 139-141). This artificially made all configurations appear unitary-preserving when they were not.

Honest result after bug fix: Bigeometric quantum evolution does NOT naturally preserve unitarity. 0/1000 configurations preserve norm without explicit correction. Best norm drift: 0.000256 (still requires normalization). Previous claim that "MOO discovers unitarity-preserving parameters" was INVALID.

EXP-6: Quantum Phase Diagram

CORRECTED - BUG FOUND

CORRECTED December 2025: Original P05 simulation had forced normalization bug. After bug fix, bigeometric quantum evolution does NOT preserve unitarity. 0/1000 configurations preserve norm naturally. MOO discovery claim was INVALID.

CORRECTED: What Really Happened

  • - 0/1000 configurations preserve unitarity naturally
  • - Forced normalization masked the failure (bug lines 139-141)
  • - Best norm drift: 0.000256 (still diverges without correction)
  • - Previous "MOO discovery" claim was INVALID

Critical Failure

  • - Bigeometric evolution requires explicit normalization to stay unitary
  • - Classical Crank-Nicolson (k=0, w=0, p=0) preserves unitarity
  • - ALL meta-calculus parameters (k u003E 0) break unitarity
  • - Data file: public/corrected_results.json
Data: results/quantum_phase_moo.json | Script: simulations/quantum_phase_moo.py

EXP-7: Cosmology vs Real Data

CANNOT RESOLVE

Tests meta-calculus predictions against SH0ES, DESI, KiDS, and Planck data. Critical validation: can the framework resolve cosmological tensions?

Why It Cannot Resolve Tensions

  • - H0: 0/9 Pareto solutions (k is uniform)
  • - S8: 0/9 Pareto solutions (same reason)
  • - Li7: -28% improvement (does not help)
  • - Tensions need SCALE-DEPENDENT physics

Honest Assessment

  • k produces UNIFORM corrections
  • Previous claims were post-hoc fitting
  • Framework is numerical tool, not physics
  • This confirms HONEST-STATUS.md
Data: results/cosmology_validation_moo.json | Script: simulations/cosmology_validation_moo.py

Methodology

Step 1
Build on Existing

Reused 37 result files, 8 MOO scripts, existing test infrastructure.

Step 2
MOO Optimization

pymoo NSGA-II with 30-50 population, 50-100 generations per experiment.

Step 3
Honest Documentation

Document both positive and negative results. Update claims accordingly.

What Changed

ClaimBeforeAfter
Shock Tube CFD"Not implemented""5.4% improvement (validated 12.1% +/- 3.1%)"
Spectral Gap Preservation"Always holds (9/9)""Holds for Dirichlet/Periodic BCs"
k(L) Pattern"Energy density better (R^2=0.73)""BUG FIXED: All affine features R^2=0.82"
Convergence Order"Unknown""Bigeometric = 2nd order (verified)"
Chaos Preservation"Not tested""NEUTRAL: Matches RK4 (0% improvement)"
Quantum Unitarity"Not tested (forced normalization bug)""CORRECTED: 0% unitary (bug fixed Dec 2025)"
Cosmology Tensions"May resolve H0""CANNOT resolve (uniform k)"
HONEST-STATUS.mdVersion 3.0Version 3.2 (updated)

All 7 Experiments Complete

DONE

MOO-First Validation Complete

All 7 experiments implemented with honest outcomes documented. 2 VERIFIED, 1 CORRECTED, 1 REFINED, 1 NEUTRAL, 1 INVALID (bug), 1 CANNOT RESOLVE. 3 VERIFIED, 1 PARTIAL, 1 REFINED, 1 NEUTRAL, 1 CANNOT RESOLVE.

Dec 2024

Key Insight

Meta-calculus is a numerical tool, not a physics theory. It helps with regularization, scheme consistency, and parameter optimization - but cannot resolve physics problems that require scale-dependent modifications.