Alternative Deterministic Structural Inference: The DSFB Stack for Reconstruction, Causal Architecture, Trust Recursion, and Historical Replay

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Authors: Riaan De Beer
Cited by: 50
References: 10

Abstract

This paper develops a deterministic structural inference framework forreasoning about system state, causal structure, trust evolution,anomaly semantics, regime dynamics, and historical traces within asingle operator-theoretic architecture. The proposed stack---DSFB,DSCD, TMTR, ADD, SRD, and HRET---treats structural reconstruction,causal graphs, trust recursion, anomaly detection, regime detection,and historical replay as interacting deterministic operators acting onstructural state, observation, trust, regime, causal graph, and tracespaces. The paper contributes four layers of theory. First, it introduces aset of design principles for deterministic structural inference.Second, it develops a shared algebraic framework linking reconstruction,trust, causality, anomaly semantics, regime structure, and historicalreplay within a common operator language. Third, it establishescomponentwise theorem banks containing twenty structural theorems foreach of the six principal stack layers. Fourth, it presents a cross-layeranchor theorem program proving representation, factorization,compatibility, stability, convergence, and compositional closureproperties of the unified architecture. To illustrate the expressive scope of the framework, the paper alsoconstructs a structural realization space cataloging alternativemathematical realizations across the six stack components. Takentogether, these results define the first installment of a deterministicstructural inference program: they introduce a coherent operatorlanguage, identify the core invariants governing the stack, establishan initial theorem program, and delineate the scope, limitations, andfuture directions of the broader theory.

Fields of Study & Subjects

Logic Reasoning and Knowledge Formal Methods in Verification Quantum Mechanics and Applications

Publication details

Journal / source
Zenodo (CERN European Organization for Nuclear Research)
Publication date
15 March 2026
Language
EN
Document type
Preprint