Admissibility-Time Bounds from Fixed-Point Damping Exact Exit Times, Certified Proper-Time Filters, and the MTT Source Boundary

This paper separates the exact admissibility exit time of a damped incoherent sector from the earliest time certified by an exponential semigroup bound. It proves the certified threshold formula and obtains the exact formula when a nonnegative self-adjoint generator is reduced by the incoherent projector. Declared operator, projector, spectral-window, tolerance, and time data then determine a unique functional-calculus filter with a controlled error decomposition and an explicit circle benchmark. The result is conditional rather than a first-principles scale prediction: MTT geometry must still select those source data and their physical intertwiner before the filter can replace a regulator or modify a propagator.

Authors

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-07-30
DOI
https://doi.org/10.5281/zenodo.21704669
Primary Topic
Model Reduction and Neural Networks
Type
preprint
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preprint

Admissibility-Time Bounds from Fixed-Point Damping Exact Exit Times, Certified Proper-Time Filters, and the MTT Source Boundary

Peter Nero
Zenodo (CERN European Organization for Nuclear Research)
Model Reduction and Neural Networks
preprint

Admissibility-Time Bounds from Fixed-Point Damping Exact Exit Times, Certified Proper-Time Filters, and the MTT Source Boundary

Peter Nero
preprint en

Abstract

This paper separates the exact admissibility exit time of a damped incoherent sector from the earliest time certified by an exponential semigroup bound. It proves the certified threshold formula and obtains the exact formula when a nonnegative self-adjoint generator is reduced by the incoherent projector. Declared operator, projector, spectral-window, tolerance, and time data then determine a unique functional-calculus filter with a controlled error decomposition and an explicit circle benchmark. The result is conditional rather than a first-principles scale prediction: MTT geometry must still select those source data and their physical intertwiner before the filter can replace a regulator or modify a propagator.

Zenodo (CERN European Organization for Nuclear Research)
Model Reduction and Neural Networks
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