What question did this study set out to answer?

The framework aims to implement a finite-capacity latency–erasure theory in cosmological inference practices using real data.

March 17, 2026Open Access

Global Cosmological Inference of the Finite-Capacity Latency–Erasure Theory Real-Data MCMC Constraints from CMB, BAO, Pantheon+, Growth, and Lensing

Puntos clave

The framework aims to implement a finite-capacity latency–erasure theory in cosmological inference practices using real data.
Developed an inference-ready formulation of the finite-capacity latency–erasure theory.
Defined key equations and minimal sampling bases for analysis.
Outlined implementation paths using CLASS software for different data types.
Constructed a likelihood stack incorporating various cosmological data such as CMB and BAO.
Established clear criteria for evaluating cosmological success versus trivial models.
Highlighted potential for maintaining perturbative stability under real data conditions.
Differentiated between trivial and nontrivial branches of the latency–erasure theory.

Resumen

We present a technical cosmological-inference framework for the finite-capacity latency–erasure theory (FCLET) designed for implementation in a Boltzmann plus MCMC pipeline. Earlier works in the FCLET program established moderated erasure cosmology, matter-coupling closure, perturbation consistency, parameter hierarchy, mathematical admissibility, and benchmark-oriented numerical architecture. The present manuscript converts that architecture into an inference-ready formulation. We specify a canonical cosmological realization, define a minimal yet nontrivial sampling basis, derive explicit background and linear-perturbation equations, formulate hard theoretical viability cuts, and describe a concrete CLASS-to-Cobaya or CLASS-to-MontePython implementation path. We also define the real-data likelihood stack, including CMB, BAO, type-Ia supernovae, growth, and lensing-sensitive information, and state the statistical outputs required for referee-level assessment: posterior distributions, contour plots, breakdowns, information criteria, posterior-predictive curves, and tension metrics. The purpose of this work is not to claim an empirical victory before the chains are run, but to remove all ambiguity about what would count as cosmological success, triviality, or exclusion. We distinguish a trivial near-CDM survival branch from a genuinely nontrivial latency–erasure branch and define explicit criteria for each. Particular emphasis is placed on the question of whether FCLET can maintain perturbative stability, preserve the matter era, remain compatible with precision background observables, and still produce a statistically meaningful posterior island once confronted with real data. The paper is intentionally written to answer the strongest foreseeable referee objections: that the model simply re-labels dark energy, that its parameters are underconstrained, that it improves the background only by damaging perturbations, or that it collapses to CDM under full likelihood pressure.

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