Research paperHistorical importARR-2026-4F7SF8FXM18ANAXH · v1 · 2026-08-10

Architecture-Dependent Decoherence Suppression in Passive Quantum Networks: Irreducible Channel Mixing, Squared Rate Gaps, and the Price in Dwell Time

Lluis Eriksson

Abstract

We study whether passive reservoir filtering can suppress decoherence more effectively when its channel mixing is irreducible, even after fixing the passband responses and rational complexity. For every integer S ≥ 5, we construct an explicit causal inner six-port network with three signal and three vacuum-loss ports. Its signal block is a rational Schur transfer satisfying 3(S−1) delayed full-spark tangential calibrations and exhibiting exponentially small leakage on two stop arcs. In contrast, every transfer of the same bidegree possessing a constant nontrivial reducing channel and satisfying the same calibrations retains unit stopband norm.We strengthen this exact separation with a quantitative finite-error obstruction: for calibration defect δ and sampled reducing-line defect β, comparator leakage is bounded below by [1−C_S(δ+β)]_+, with C_S given explicitly by finite singular-value margins. A scalar Schur construction proves that every bound of this form must deteriorate at least as 2 exp(9S/20)(1+o(1)); hence uniform robustness is impossible for the chosen clustered calibrations.For uniformly nondegenerate bath spectra, the signal-level separation is squared at the Kossakowski-rate level. A closed Markov pure-dephasing model includes all auxiliary vacuum ports exactly, producing an architecture-independent measurable baseline and an explicit total Ramsey-rate advantage. Finally, we prove that strong passive suppression requires large dwell time: under a peak-delay budget D, the rate-improvement factor is asymptotically at most quadratic in D/S. The construction therefore moves the coherence-maintenance resource into passive memory, vacuum noise and conditioning rather than eliminating it. All certificates, figures and numerical audits are publicly reproducible.

Original depositai.vixra first-submission history · source omits timezone
Historical mirrorv1Author-authorized ARR bulk release · SHA-256 recorded
Mirrored PDF downloadsNot measuredBulk historical-release assets are not yet included in ARR's per-record download snapshot.
Page viewsNot measuredPage views are not measured until ARR connects a privacy-reviewed, no-cookie analytics source.
Definitions and rankings →
Not yet rated

Verification record

Frontier-model screening
Not assessed
Source integrity
Pass
Bibliographic integrity
Not assessed
Reproducibility
Not assessed
Lean 4
Not assessed

Recorded under ARR-HISTORICAL-IMPORT-1.0. ARR verification and screening are not peer review.

Version history

The ARR identifier remains stable. Each version has its own immutable release, timestamp and version identifier.

  • v1 · source snapshot available · viewing

Original ai.vixra version history

Dates below are the source submission timestamps. ai.vixra omits a timezone; ARR preserves the displayed values and uses the normalized offset only for deterministic ordering.

  • v1 · original ai.vixra file

AI assistance statement

Historical import from ai.vixra, an AI-assisted e-print archive. ARR has not normalized or independently verified the original manuscript's model-use disclosure; the author remains responsible for its contents.

Frontier-model screening

Status: not_assessed. Any listed reports correspond to this exact version under ARR-SCREEN-1.0; no absent assessment is represented as a pass.

    Longitudinal frontier-model record

    Independent model assessments

    Read the scale and limits
    Not yet rated

    No eligible independent ARR-ASSESS-1.0 report is published for this exact version. Missing evidence is not scored as zero.

    No model reports are published for this version.

    A model assessment is not peer review or a correctness certificate. ARR preserves disagreement, exact-version provenance and later reassessments.

    Editorial disclosure

    Author-authorized historical import. ARR verified file retrieval and integrity only; it did not perform the current hostile frontier-model admission audit, peer review, novelty review, or correctness certification.