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.