The Residual after Elimination: From Orthogonal Innovation to Effective Response

We investigate the information retained after eliminating hidden degrees of freedom from a finite-dimensional positive-definite Hermitian operator. A single energy-dependent elimination signature connects orthogonal residual geometry, linear innovation, Feshbach–Schur reduction, resolvent response, and dynamical memory. Its value at zero determines the minimum energy after elimination, while its negative first derivative is the Gram matrix of the full-state reconstruction. The main result solves an extremal problem over all positive realizations sharing the same signature value, first derivative, and known lower spectral threshold of the hidden block. We construct a minimal canonical realization that saturates a matrix-valued lower bound throughout the subthreshold energy interval. We determine the exact minima and suprema of the first indexed eigenvalues, allowing arbitrary finite hidden dimensions. All lower minima are attained simultaneously by one realization, while a single family approaches all upper suprema. Operator equality with the extremal bound at one energy enforces the entire extremal signature. The deviation from this bound controls the high-energy component of the static reconstruction and satisfies optimal comparisons across energies. The full signature identifies the active hidden realization up to unitary equivalence, whereas first-order data determine only its minimum required dimension. Noncommuting and three-mode examples demonstrate the benefit of retaining complete matrix information and distinguish reduced visible-state weight from destructive interference in a fixed spectral readout.

Authors

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-10-15
DOI
https://doi.org/10.5281/zenodo.23395765
Primary Topic
Spectral Theory in Mathematical Physics
Type
preprint
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
preprint

The Residual after Elimination: From Orthogonal Innovation to Effective Response

Maciej Stachowiak, Paweł Nowak
Zenodo (CERN European Organization for Nuclear Research)
Spectral Theory in Mathematical Physics
preprint

The Residual after Elimination: From Orthogonal Innovation to Effective Response

Maciej Stachowiak, Paweł Nowak
preprint en

Abstract

We investigate the information retained after eliminating hidden degrees of freedom from a finite-dimensional positive-definite Hermitian operator. A single energy-dependent elimination signature connects orthogonal residual geometry, linear innovation, Feshbach–Schur reduction, resolvent response, and dynamical memory. Its value at zero determines the minimum energy after elimination, while its negative first derivative is the Gram matrix of the full-state reconstruction. The main result solves an extremal problem over all positive realizations sharing the same signature value, first derivative, and known lower spectral threshold of the hidden block. We construct a minimal canonical realization that saturates a matrix-valued lower bound throughout the subthreshold energy interval. We determine the exact minima and suprema of the first indexed eigenvalues, allowing arbitrary finite hidden dimensions. All lower minima are attained simultaneously by one realization, while a single family approaches all upper suprema. Operator equality with the extremal bound at one energy enforces the entire extremal signature. The deviation from this bound controls the high-energy component of the static reconstruction and satisfies optimal comparisons across energies. The full signature identifies the active hidden realization up to unitary equivalence, whereas first-order data determine only its minimum required dimension. Noncommuting and three-mode examples demonstrate the benefit of retaining complete matrix information and distinguish reduced visible-state weight from destructive interference in a fixed spectral readout.

Zenodo (CERN European Organization for Nuclear Research)
Spectral Theory in Mathematical Physics
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.