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May 25, 20260 citationsOpen Access

A Mathematical Proof of the Yang-Mills Mass Gap in the Constraint Network Framework

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MYMenggang Yu

Key Points

  • The aim is to provide a mathematical proof that establishes the existence of a mass gap in Yang-Mills theory.
  • Utilized the axiom-theorem framework of Constraint Network Dynamics.
  • Demonstrated the origin of the strong interaction through a bi-directional flow channel.
  • Established stability and positivity of the mass gap using prior theorems.
  • Confirmed a positive mass gap from the stability of the chain network, supported by Theorem 8.
  • Identified the mass gap's threshold as dictated by energy requirements from system parameters.
  • Established that the existence of the mass gap does not rely on external assumptions or simulations.

Abstract

The Yang-Mills existence and mass gap problem is one of the Millennium PrizeProblems of the Clay Mathematics Institute. The problem requires provingthat for any compact gauge group, quantum Yang-Mills theory exists and itsexcited states have a positive mass gap. This paper presents a mathematicalproof of this problem within the axiom-theorem system of Constraint NetworkDynamics. The Constraint Network Model is a deterministic discrete dynamicalsystem defined by three axioms, fully formalizable in ZF set theory, whoseeight theorems have been rigorously proved in prior work. We prove thatwithin this framework, the chain—a bi-directional flow channel of N = 1units between sealed nodes—is the origin of the strong interaction. Theformation and maintenance of a chain requires a specific energy thresholdthat is strictly positive and uniquely determined by the system parameters.This threshold is precisely the Yang-Mills mass gap. The existence of themass gap is guaranteed by the chain network stability established in Theorem8, and its positivity is jointly derived from the geometric constraint ofTheorem 4 and the irreversibility of accretion of Theorem 2. This proofintroduces no assumptions beyond the axiom system of the Constraint NetworkModel, and relies on neither numerical simulation nor perturbative expansion.

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Cite This Study

Menggang Yu (2026) studied this question.

synapsesocial.com/papers/6a13e8680e02ee3982d33332https://doi.org/10.5281/zenodo.20349988
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