Title: Algorithmic Complexity of Quantum Gravity

Jincheng Zhang

Published Sep 5, 2026• 0 citations

Abstract

Quantum gravity, a theoretical framework attempting to reconcile general relativity and quantum mechanics, presents a profound challenge to our understanding of spacetime. Accurately simulating quantum gravity calculations, particularly those involving complex spacetime geometries and quantum entanglement, demands significant computational resources. Traditional approaches often rely on approximations and heuristics, failing to fully capture the inherent complexity. This paper investigates a novel algorithmic complexity framework for quantum gravity, leveraging information theory and graph theory to quantify the computational challenges. We introduce a 'Quantum Information Landscape' – a layered representation of potential quantum states and their interactions – to provide a more precise assessment of these challenges. The proposed algorithm focuses on identifying and characterizing regions of high computational cost, ultimately informing the design of more efficient simulation techniques. This research seeks to move beyond simple complexity measures and provide a quantifiable metric, informing both theoretical advancements and practical algorithm design within the field of quantum gravity.

DOI: 10.5281/zenodo.22331925

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