What question did this study set out to answer?

This research aims to explain how physical data can be derived from a sequence of projections in a flavor framework.

February 6, 2026Open Access

Projection Principle for Flavor from Division-Algebra Towers (Corner Selection and Tilts)

Key Points

This research aims to explain how physical data can be derived from a sequence of projections in a flavor framework.
Introduces the Projection Principle for flavor extraction
Describes a series of projections from vacuum to corners
Analyzes tilts to reveal CKM/PMNS structure
Establishes the extraction of CKM/PMNS structures without continuous fit parameters
Demonstrates a systematic approach using projection chains
Provides theoretical insights into flavor dynamics through mathematical frameworks

Abstract

Companion synthesis note to the tower-based flavor framework. It states the Projection Principle: physical data are extracted from a chain of projections and stabilizers (vacuum P1P1 → corner P2P2 → infinitesimal tilts P3P3), yielding CKM/PMNS structure with no continuous fit parameters. Overview paper: 10.5281/zenodo.18434449 Construction artefact (CKM/PMNS): 10.5281/zenodo.18364899 Tower termination note: 10.5281/zenodo.18475872

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M. Bakhtaoui

Université des Sciences et de la Technologie d'Oran Mohamed Boudiaf

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Projection Principle for Flavor from Division-Algebra Towers (Corner Selection and Tilts)

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