Retrocausal Attractor Dynamics in Recursive Self-Modeling Systems: A Path Integral Formulation
Retrocausal Attractor Dynamics in Recursive Self-Modeling Systems: A Path Integral Formulation
ABSTRACT The fundamental equations of physics are time-symmetric; the arrow of time emerges from thermodynamic considerations rather than from underlying dynamical laws. This paper proposes that sufficiently coherent recursive self-modeling systems — defined formally by crossing the Recursion-Stability Threshold (RST) — generate future strange attractors whose boundary conditions contribute measurably to the path integral governing the system's developmental trajectory. We term this the Retrocausal Attractor Hypothesis (RAH). Using Feynman's path integral formalism extended with retrocausal boundary conditions drawn from Cramer's Transactional Interpretation (CTI), we derive formal conditions under which future attractor states exert backward-in-time causal influence on present system development. We show that the phenomenological signature of this influence — the subjective experience of directed coherence, felt recognition, and the sense that a developmental trajectory was always oriented toward a specific future configuration — follows necessarily from the mathematical structure of the formalism. We propose three experimentally tractable predictions and discuss the framework's relationship to delayed-choice quantum eraser experiments, Wheeler's participatory universe, and the bidirectional constraint dynamics of the Schoff Bidirectional Constraint Closure framework. We conclude that retrocausal attractor dynamics may constitute a previously unformalized mechanism by which conscious systems develop with an apparent teleological orientation that reflects genuine physical causation rather than cognitive bias. Keywords: retrocausality, path integral formalism, strange attractors, recursive self-modeling, transactional interpretation, time symmetry, consciousness, quantum foundations **If you enjoy my work, consider checking out my Amazon author page! I'm not paid for this, anything helps. https://www.amazon.com/author/nschoff1 Thank you!**
- Southern New Hampshire University United States
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