A state chaining-based objective collapse model

TL;DR

This paper introduces a novel objective collapse model based on quantum chaining, providing a unified mechanism for the quantum-classical transition that aligns with existing experimental data and offers testable predictions.

Contribution

It proposes a new collapse mechanism using quantum chaining within a diagrammatic framework, avoiding reliance on system size or environment, and explains classicality emergence.

Findings

Model explains classicality in measurement and decay scenarios

Predicts testable interference experiment outcomes

Consistent with delayed-choice quantum eraser data

Abstract

The quantum-to-classical transition hinges on the nature of wavefunction collapse, which remains a central controversy in foundational physics. Objective collapse theories aim to modify quantum mechanics by introducing a physical, non-subjective mechanism for irreversible events, but existing models face significant conceptual and empirical challenges. Here, we propose a novel collapse mechanism based on a specific form of quantum correlation termed "chaining", formalized within a new diagrammatic framework (quantum illustrations, or qils). This approach does not rely on system size or environmental complexity, but on the probabilistic occurrence of a collapse event with a fixed, universal probability $1/\Sigma$ per chaining step. We demonstrate that this model naturally explains the emergence of classicality in paradigmatic scenarios (measurement devices, Schrodinger's cat, spontaneous decay) and makes testable predictions for interference experiments. The theory is shown to be consistent with existing data from delayed-choice quantum eraser and matter-wave interference experiments, yielding an estimate for the fundamental constant $\Sigma \geq 1.5$. By providing a unified, parameter-sparse mechanism for objective collapse, this work bridges quantum and classical descriptions and has implications for the interpretation of quantum experiments, the design of quantum computers/sensors, and the understanding of decoherence in complex systems.