Algorithmic Idealism III: "Algorithmic State" Formulation of Quantum Mechanics

TL;DR

This paper proposes a novel framework called Algorithmic Idealism that models quantum mechanics as a computational process driven by informational principles, offering new insights into quantum phenomena and foundational physics.

Contribution

It introduces a set of quantum postulates based on informational constructs, unifying quantum mechanics with computational theory and addressing philosophical questions about identity and reality.

Findings

Quantum measurement as Bayesian updating

Entanglement as joint utility optimization

Quantum probabilities as utility-weighted predictions

Abstract

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