A Framework for Non-Paradoxical Backwards Information Flow in Entangled Quantum Systems

This paper introduces the Theory of Retrodirected Informational Return (TIRR), a novel quantum framework enabling limited, non-paradoxical information feedback from future measurements within entangled systems.By defining a retrofilter operator and an informational curvature metric, TIRR translates time-symmetric quantum interpretations into testable, operational protocols.We propose a concrete experimental setup using post-selection in entangled photon pairs to empirically verify retroinformational influence under coherence-preserving conditions.

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-05-04
DOI
https://doi.org/10.5281/zenodo.15336957
Primary Topic
Quantum Mechanics and Applications
Type
article
Field-Weighted Citation Impact
0.00
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article

A Framework for Non-Paradoxical Backwards Information Flow in Entangled Quantum Systems

Zenodo (CERN European Organization for Nuclear Research)
Quantum Mechanics and Applications
article

A Framework for Non-Paradoxical Backwards Information Flow in Entangled Quantum Systems

article en

Abstract

This paper introduces the Theory of Retrodirected Informational Return (TIRR), a novel quantum framework enabling limited, non-paradoxical information feedback from future measurements within entangled systems.By defining a retrofilter operator and an informational curvature metric, TIRR translates time-symmetric quantum interpretations into testable, operational protocols.We propose a concrete experimental setup using post-selection in entangled photon pairs to empirically verify retroinformational influence under coherence-preserving conditions.

Zenodo (CERN European Organization for Nuclear Research)
Reduced inequalities
Openalex Percentile: Top 59%
Quantum Mechanics and Applications
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A Framework for Non-Paradoxical Backwards Information Flow in Entangled Quantum Systems · Zenodo (CERN European Organization for Nuclear Research) (2025) | TGRS Research Map | TGRS