Experiments / V2.525
V2.525
Dynamical Selection COMPLETE

V2.525 - Bayesian Model Showdown — Framework vs ΛCDM vs w₀wₐCDM

V2.525: Bayesian Model Showdown — Framework vs ΛCDM vs w₀wₐCDM

Status: NUANCED — Bayes factor favors framework over ΛCDM (+1.32); AIC/BIC favor ΛCDM; CMB is the discriminator

The Question

The framework predicts Ω_Λ = 149√π/384 = 0.6877 with zero free parameters. ΛCDM fits Ω_Λ ≈ 0.685 with one parameter. w₀wₐCDM uses 3 parameters. Which model does the combined data prefer when the Occam razor is properly applied?

Data

41 measurements from 5 datasets spanning z = 0 to z = 1090:

DatasetNSource
BAO12DESI Y1 (7 redshifts, DM/DH correlations)
CMB3Planck 2018 compressed (R, l_a, Ω_b h²)
Cosmic chronometers24Moresco+2022 compilation
SNe Ia1Pantheon+ compressed (Ω_m = 0.334 ± 0.018)
BBN1Primordial D/H (Cooke+2018)

Key Results

Chi-squared breakdown

DatasetFramework (0p)Planck ΛCDM (1p)Δχ²
BAO20.3523.88-3.54 (framework wins)
CMB12.050.04+12.01 (ΛCDM wins)
CC13.5013.70-0.20
SNe1.461.08+0.38
BBN0.260.26+0.00
Total47.6238.96+8.65

The framework’s total chi² is higher, driven almost entirely by the CMB compressed likelihood. The framework’s 0.44% higher Ω_Λ shifts the CMB shift parameter and acoustic scale enough to produce a 12-point chi² penalty.

Bayesian Evidence (Laplace approximation)

Modelkχ²_minln(Z)
Framework047.62-23.81
ΛCDM138.73-25.13
w₀wₐCDM325.72-23.56

Bayes Factors

Comparisonln(B)Interpretation
Framework vs ΛCDM+1.32Substantial evidence for framework
Framework vs w₀wₐCDM-0.25Inconclusive
ΛCDM vs w₀wₐCDM-1.57Substantial evidence for w₀wₐCDM

Information Criteria

Modelkχ²AICBIC
Framework047.6247.6247.62
Best ΛCDM138.7340.7342.44
Best w₀wₐ325.7231.7236.86

AIC and BIC both favor ΛCDM over the framework by ΔAIC = +6.9, ΔBIC = +5.2.

Interpretation

Why the Bayes factor and AIC/BIC disagree

The Bayes factor penalizes ΛCDM for its wasted prior volume: with a prior Ω_Λ ∈ [0.4, 0.9] but the data constraining Ω_Λ to ±0.001, ΛCDM “wastes” 99.8% of its prior. The framework pays no such penalty.

AIC/BIC penalize parameters at a fixed rate (2 per param for AIC, 3.7 per param for BIC), which is much less than the actual Bayesian Occam factor (~6 in log-evidence). This is because AIC/BIC are asymptotic approximations that assume the prior is uninformative relative to the likelihood — not true here.

The honest answer: both perspectives are legitimate.

  • The Bayesian analysis says: “A theory that predicts Ω_Λ = 0.6877 with 0 parameters is more impressive than a theory that fits Ω_Λ = 0.685 with 1 parameter.”
  • The frequentist analysis says: “The data prefer Ω_Λ = 0.685, and the framework’s value doesn’t fit as well.”

Where the tension lives

The entire Δχ² = 8.65 is dominated by the CMB compressed likelihood (Δχ² = +12.0). Specifically:

  • The framework’s Ω_Λ = 0.6877 shifts the CMB acoustic scale l_a by 0.9 (vs Planck’s σ = 0.09)
  • This 10σ pull in l_a drives the CMB chi²

The BAO data actually prefer the framework (Δχ² = -3.5), confirming V2.519.

The w₀wₐCDM question

The combined data show substantial evidence for w₀wₐCDM over ΛCDM (ln B = -1.57). The best-fit w₀ = -0.50, wₐ = -1.65 — both far from the cosmological constant (w₀ = -1, wₐ = 0). However, the framework and w₀wₐCDM are essentially tied (ln B = -0.25).

This confirms the DESI finding: there IS some pull toward w ≠ -1 in the combined data, driven by BAO. But the framework’s zero-parameter prediction is competitive with the 3-parameter w₀wₐCDM fit.

Critical Assessment

Strengths

  1. Bayes factor favors framework over ΛCDM: the Occam razor rewards zero parameters
  2. BAO data prefer the framework: Δχ² = -3.5 across 12 DESI measurements
  3. Framework vs w₀wₐCDM is a tie: 0 parameters matches 3-parameter fit

Weaknesses

  1. CMB compressed likelihood is the Achilles heel: 12-point chi² penalty from l_a mismatch
  2. Profile likelihood shows 5.6σ tension between framework’s Ω_Λ and the combined best-fit — this is serious
  3. Bayes factor is prior-dependent: a tighter ΛCDM prior (e.g., [0.6, 0.8]) would reduce the Occam penalty
  4. Pantheon+ constraint is compressed: full distance modulus analysis could shift results
  5. Cosmic chronometers have large uncertainties: contribute little constraining power

The fundamental tension

The framework predicts Ω_Λ = 0.6877. The CMB data (Planck) prefer 0.6847. The difference is only 0.44%, but the CMB constrains Ω_Λ so precisely that this generates significant tension in the combined fit.

This tension could be resolved by:

  • Euclid/DESI Y5: if Ω_Λ moves from 0.6847 toward 0.688, the framework wins
  • Systematic re-analysis: the CMB compressed likelihood may not capture the full Planck posterior
  • The framework is wrong: if the trace anomaly prediction is off by 0.4%

Connection to Other Experiments

  • V2.519: DESI BAO alone favors the framework (Δχ² = -3.2), confirmed here
  • V2.520: Multi-probe stress test showed χ²/dof = 1.07, but used approximate methods
  • V2.521: Forecasts 2.9σ combined discrimination by 2035 — this is driven by the CMB tension we quantify here
  • V2.524: Euclid will distinguish n_grav = 10 vs 9 at 2.7σ, which would shift Ω_Λ enough to affect this comparison

Files

  • src/bayesian_showdown.py: Full cosmology engine, 5 datasets, evidence computation
  • tests/test_bayesian_showdown.py: 32 tests (all passing)
  • run_experiment.py: Complete 7-section analysis
  • results.json: Machine-readable results