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The Generative Reality Hypothesis: A Computational Framework for Quantum Mechanics

Parth Shukla

Published Aug 11, 2025• 0 citations
Publisher

Abstract

We propose the Generative Reality Hypothesis (GRH), a novel interpretation of quantum mechanics that reconceptualizes physical reality as an information-processing system analogous to generative artificial intelligence models. Under this framework, quantum superposition represents the latent space of possible states, wave function collapse corresponds to sampling from probability distributions during information queries (measurements), and the Born rule emerges as the fundamental sampling algorithm of reality. We present rigorous mathematical foundations establishing formal equivalences between quantum dynamics and specific generative models. Our framework recasts the measurement problem as a question of computational process, explains non-local correlations as the enforcement of consistency within a shared generative model, and provides a mechanistic explanation for wave-particle duality as a transition between two computational modes: continuous latent evolution (wave) and discrete sampling (particle). We propose five specific, falsifiable experimental tests using current quantum technologies that can distinguish GRH from standard quantum mechanics through quantitative predictions about complexity-dependent decoherence, measurement dynamics, and information flow. Statistical criteria for falsification are established with required experimental precision specified. The framework connects quantum mechanics to information theory and computational complexity, offering a computationally grounded foundation for quantum phenomena while making testable predictions that differ measurably from existing interpretations.

DOI
10.20944/preprints202508.0772.v1

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We propose the Generative Reality Hypothesis (GRH), a novel interpretation of quantum mechanics that reconceptualizes physical reality as an information-processing system analogous to generative artificial intelligence models. Under this framework, quantum superposition represents the latent space of possible states, wave function collapse corresponds to sampling from probability distributions during information queries (measurements), and the Born rule emerges as the fundamental sampling algorithm of reality. We present rigorous mathematical foundations establishing formal equivalences between quantum dynamics and specific generative models. Our framework recasts the measurement problem as a question of computational process, explains non-local correlations as the enforcement of consistency within a shared generative model, and provides a mechanistic explanation for wave-particle duality as a transition between two computational modes: continuous latent evolution (wave) and discrete sampling (particle). We propose five specific, falsifiable experimental tests using current quantum technologies that can distinguish GRH from standard quantum mechanics through quantitative predictions about complexity-dependent decoherence, measurement dynamics, and information flow. Statistical criteria for falsification are established with required experimental precision specified. The framework connects quantum mechanics to information theory and computational complexity, offering a computationally grounded foundation for quantum phenomena while making testable predictions that differ measurably from existing interpretations.
This preprint presents a foundational theory that reinterprets quantum mechanics not as a description of fundamental physical reality, but as the emergent statistical signature of a universal information-processing architecture. We introduce and formally define the Ze (Zero-point entropy) system—an active predictive engine that operates through a mandatory cycle of forward prediction and retrograde inference. The system's core axiom is that the retrograde encoding process, essential for reconciling past models with present evidence, necessitates a complete cessation of the forward information flow. From this single architectural constraint, we mathematically derive phenomena isomorphic to quantum superposition, interference, and wavefunction collapse. Superposition corresponds to a dynamical equilibrium of multiple predictive hypotheses; collapse is a structured, non-fundamental process triggered when hypothesis divergence exceeds a system-specific stability threshold; and interference arises from the coherent blending of compatible hypotheses. The framework positions quantum behavior as an epistemic property of any system performing active inference under this architectural constraint, bridging domains from particle physics to cognitive neuroscience. We present novel, falsifiable predictions and propose that quantum theory describes the dynamics of a universal class of predictive engines, not a microscopic realm of reality.
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This work introduces Algorithmic Idealism a framework that reinterprets quantum mechanics as a computational process governed by algorithmic probability informational simplicity and utility optimization Reality is modeled as an agentenvironment feedback loop where agents maximize utility by predicting selfstate transitions Core quantum phenomena such as measurement entanglement and probabilities are explained through informational constructs The paper presents a set of quantum mechanics postulates inspired by this framework and explains their mathematical meaning in detail These postulates include measurement as Bayesian updating entanglement as joint utility optimization and quantum probabilities as utilityweighted predictions Physical laws are shown to emerge as informational regularities from algorithmic constraints By defining identity through decisionmaking consistency and treating simulated and base realities as indistinguishable the framework also resolves philosophical questions about identity and reality This approach unifies quantum mechanics with computational theory offering a novel perspective on foundational physics and its connection to information and computation
We propose the Computational Holography Hypothesis (CHH), a frameworkunifying deterministic computation, holographic information encoding, and observerinducedepistemic constraints to explain the emergence of quantum mechanics (QM).Through 1D, 2D, and 3D cellular automata (CA) simulations, we demonstrate howobserver-limited access to a deterministic substrate generates quantum-like phenomena—including entanglement analogs (via correlated initial seeds) and decoherence (viamutual information decay). CHH posits that QM’s probabilistic nature arises fromgeometric information bottlenecks at causal boundaries, offering a pathway to reconcilelocality with apparent nonlocality. Our simulations show that local entropyfluctuations mirror Born rule probabilities, while observer-window dynamics reproducemeasurement collapse. This work suggests QM is an effective theory of a deeper,computationally irreducible reality.
The standard Copenhagen interpretation of quantum mechanics relies on a set of historically established, ad hoc postulates to describe particle-wave duality, measurement, and non-locality. In this paper, we propose a single foundational axiom that fully reproduces the standard mathematical formalism of quantum mechanics while eliminating the need for supplementary assumptions. From this singular postulate, we rigorously derive the fundamental origin of the wave function and the mathematical generator of the Schrödinger equation. Furthermore, we demonstrate via isomorfism that all seemingly inexplicable quantum phenomena—including wave-function collapse and quantum entanglement—are mathematically and conceptually reducible to the underlying dynamics of the double-slit experiment. By establishing a direct fundamental correlation between the double-slit interference mechanism and the Monty Hall phenomenon, we prove that these effects are distinct manifestations of the exact same principle. We framed the double-slit experiment as an interference of the space of possibilities affected by information and simetrys. Ultimately, by anchoring the existing quantum mathematical framework to this unique axiom, this work provides a coherent, paradox-free ontological foundation that resolves the interpretational crisis of quantum mechanics without altering its empirical predictive power.
We propose the Computational Holography Hypothesis (CHH), a frameworkunifying deterministic computation, holographic information encoding, and observerinducedepistemic constraints to explain the emergence of quantum mechanics (QM).Through 1D, 2D, and 3D cellular automata (CA) simulations, we demonstrate howobserver-limited access to a deterministic substrate generates quantum-like phenomena—including entanglement analogs (via correlated initial seeds) and decoherence (viamutual information decay). CHH posits that QM’s probabilistic nature arises fromgeometric information bottlenecks at causal boundaries, offering a pathway to reconcilelocality with apparent nonlocality. Our simulations show that local entropyfluctuations mirror Born rule probabilities, while observer-window dynamics reproducemeasurement collapse. This work suggests QM is an effective theory of a deeper,computationally irreducible reality.