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December 20, 20250 citationsOpen Access

A Minimal Boundary Interpretation of Large-Scale Cosmological Anomalies

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SAStephen Atalebe

Key Points

  • The research aims to explain large-scale cosmological anomalies using a minimal modification to primordial boundary conditions.
  • Adopted conservative data-first analysis to identify anomalies across multiple datasets.
  • Analyzed correlations and coherence of anomalies like CMB polarization and galaxy spin.
  • Identified that no known internal LambdaCDM mechanism explains the anomalies.
  • Proposed a minimal anisotropic boundary condition to account for anomalies in various data sets.

Abstract

Large-scale cosmological anomalies persist across independent datasets and physical domains, including CMB temperature and polarization, low-ℓ alignments, hemispherical asymmetry, radio number-count dipoles, galaxy spin chirality, bulk flows, void thermodynamics, and directional variation in the Hubble parameter. Although often treated as unrelated statistical outliers, these anomalies exhibit directional convergence, cross-domain coherence, and scale consistency that are highly unlikely under isotropic LambdaCDM initial conditions. This paper adopts a conservative, data-first analysis and shows that no known internal LambdaCDM mechanism can simultaneously account for these correlated features. The anomalies are instead explained by a single minimal modification to the primordial boundary conditions: an anisotropic boundary condition or primordial modulation field. The most general linear boundary tensor consistent with symmetry is written as P⏛⏜ = α n⏛ n⏜ + β ε⏛⏜⏚ n^λ + γ (t) S⏛⏜, with α introducing directionality, β producing parity-odd signatures, and γ (t) generating dynamic anisotropic stress. This minimal boundary influence preserves General Relativity, maintains the success of LambdaCDM across small- and intermediate-scale observations, and modifies only the earliest definable hypersurface. Each boundary parameter is mapped to the anomalies it explains, and a suite of falsifiable predictions is derived for CMB-S4, LiteBIRD, SKA, LSST, Euclid, and DESI. The analysis isolates the empirical structure motivating an anisotropic boundary condition; a companion work will address the physical microstructure capable of generating such a boundary.

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Cite This Study

Stephen Atalebe (2025) studied this question.

synapsesocial.com/papers/6945e9325151ab1219e4d64dhttps://doi.org/10.20944/preprints202512.1676.v1
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