This repository contains the source of the O29 Cosmochrony paper
Spin-1/2 Sector Identification via the Symmetric Rank Formula:
Effective Dimension of the Admissible Covariance in End(Vρ).
This work extends the spectral admissibility sub-programme by resolving the representation-theoretic identification problem left open in O26–O28.
It addresses the next structural question after O28:
Why does the effective covariance rank equal 3 instead of 4, and what is the correct observable for representation identification?
The observed rank deficit is not a numerical artefact.
It is a structural constraint.
More precisely:
- conjugate-pair data are constrained by an anti-linear parity
- this forces outer products into a symmetric subspace
- the accessible rank is reduced from
$d_\rho^2$ to$d_\rho(d_\rho+1)/2$
Thus:
- the observable used in O26 must be reformulated
- the corrected observable uniquely identifies
$d_\rho = 2$
This confirms the spin-$\tfrac{1}{2}$ sector.
O26–O28 established that:
- σpair behaves as a quadratic observable (O26)
- a representation-theoretic sector is required (Level III)
- the effective covariance rank should test the sector dimension
- the proxy computation in End(
$H_{\mathrm{eff}}$ ) yields:$r_{\mathrm{eff}} = 3$ instead of the expected:$d_\rho^2 = 4$
However:
- the origin of this discrepancy was unclear
- it was attributed to a possible projection artefact
- the correct observable space was not identified
This defines the scope of O29.
The paper establishes that:
The covariance built from conjugate-pair data is intrinsically confined to the symmetric subspace
$\mathrm{Sym}(V_\rho, \mathbb{C})$ , due to the anti-linear Born–Infeld parity constraint.
As a consequence:
This replaces the O26 target:
Result. For all admissible trajectories:
Thus:
- the observable does not explore
$\mathrm{End}(V_\rho)$ - it is confined to the symmetric subspace
This constraint is:
- algebraic (pointwise)
- independent of averaging
- invariant under admissible transformations
Result. The restriction arises from:
- anti-linear Born–Infeld parity:
$\pi_{q-c}(v) = \pi_c(v)$ (up to a slowly varying phase)
Thus:
- conjugate blocks are not independent
- the observable is structurally constrained
Result.
Thus:
- rank is reduced relative to the full matrix space
- the reduction is intrinsic to the data
Result. Inverting the rank formula:
For:
Thus:
- the spin-$\tfrac{1}{2}$ sector is uniquely identified
- no ambiguity remains
Result. The correct falsifiability condition becomes:
- not
$r_{\mathrm{eff}} = d_\rho^2$ - but:
$r_{\mathrm{eff}} = \frac{d_\rho(d_\rho+1)}{2}$
Thus:
- O26 Level III is preserved
- the observable is correctly specified
The computation confirms:
-
$r_{\mathrm{eff}} = 3$ across all pairs - zero inter-pair variance at
$q = 61, 151$ - modal consistency at
$q = 101$ (multi-sample confirmed)
Additional observations:
- eigenvalue structure:
$[1 : \tfrac{1}{2} : \tfrac{1}{2}]$ - symmetry ratio small but non-zero:
$|M - M^\top| / |M| \sim 10^{-2}$
Thus:
- symmetry is structural but phase-modulated
- rank result is robust
The derivation is fully internal:
Born–Infeld admissibility
No external structure is imposed.
O29 provides the structural resolution of the representation problem:
- explains the rank discrepancy observed in O28
- identifies the correct observable space ($\mathrm{Sym}(V_\rho)$)
- derives the symmetric rank formula
- enables unique sector identification
- reformulates the O26 falsifiability criterion
More precisely, the paper:
- proves the symmetric constraint
- derives the rank formula
- validates the result numerically
- closes the representation identification loop
- quadratic observable (O26)
- admissible morphism structure (O27)
- numerical rank observation (O28)
- symmetric constraint (proved)
- symmetric rank formula (proved)
- inversion for
$d_\rho$ (analytic) - corrected falsifiability criterion
- numerical confirmation across primes
- analytical proof of
$\dim V_\rho = 2$ - extension to larger primes
- full
$d_\rho^2$ measurement via independent blocks - analytical derivation of eigenvalue ratios
The conceptual shift is:
- previous view: observable explores full matrix space
- O29: observable is structurally restricted
Thus:
- the rank deficit is not an error
- it is a signature of admissibility constraints
- representation identification requires the correct observable
O29 completes the representation identification stage:
- O26: quadratic structure
- O27: SU(2) rigidity
- O28: numerical rank observation
- O29: structural explanation + identification
Thus:
- the observable is corrected
- the sector is identified
- the chain is closed
- identification of the correct observable space
- symmetric constraint from parity
- symmetric rank formula
- unique determination of
$d_\rho$ - resolution of the O28 discrepancy
- completion of Level III identification
The spectral admissibility framework is now:
- structurally grounded (O24)
- numerically validated (O25)
- geometrically interpreted (O26)
- representation-theoretically constrained (O27)
- observationally resolved (O29)
The sector is:
- uniquely identified
- structurally justified
- numerically confirmed
Design a protocol probing
Derive
Confirm stability for larger primes.
Derive
Construct explicit embedding into
The programme is now:
- structurally closed (O24)
- numerically validated (O25)
- geometrically lifted (O26)
- representation-constrained (O27)
- observationally completed (O29)
paper/
├── out/ # Compiled O29 PDF
├── tex/ # LaTeX sources
└── README.md
If you reference this work, please cite:
J. Beau Spin-1/2 Sector Identification via the Symmetric Rank Formula: Effective Dimension of the Admissible Covariance in End(Vρ) Zenodo, 2026.
Portions of the derivations, conceptual synthesis, structural organisation, and editorial refinement benefited from iterative interactions with large language models used as analytical assistants.
All theoretical results, computations, and interpretations remain the sole responsibility of the author.
This repository is intended as a research reference.
Critical feedback, independent verification, and further analysis of:
- admissible covariance structures
- symmetric constraints
- representation identification
- sector selection
- measurement observables
are welcome.
Please open an issue to discuss conceptual points, technical details, or possible extensions.