paper

Temporal Matrix Scale Invariance and the Classification of Tipping Points

arXiv:2606.02649

Abstract

We introduce temporal matrix scale invariance (tMSI), a mathematical structure for the two-time correlation kernel of a multivariate observable. A kernel satisfies tMSI of order if for all ; this condition holds near a tipping point, where the divergence of the coherence time produces temporal scale freedom. By a kernel factorization theorem, every tMSI kernel separates into a power-law envelope and a shape function diagonalized by the Mellin transform. This reveals a decoupling of two independent exponents: the dynamical exponent , carried by the envelope, and the spectral relaxation exponent , determined by the eigenvalue decay of the finite-dimensional truncation. Their equality characterizes a simple critical point; their inequality is the signature of temporal multicriticality. We provide a classification of tipping points. The Landau quartic coefficient is given exactly by , where , is the three-point structure constant, and is in explicit closed form. The transition is continuous for , tricritical for , and discontinuous for . The simple critical point is maximally fragile: any nonzero operator mixing drives , placing the synchronized state generically at the edge of catastrophe. The framework yields a matrix-valued early warning diagnostic, computable from a multivariate time series without knowledge of the underlying equations, that classifies an approaching tipping point as recoverable or catastrophic. Applications to epilepsy and acute myocardial infarction are discussed.

Temporal Matrix Scale Invariance and the Classification of Tipping Points · wovepaper