ArticleScientific reports2026
Quantum informative analysis for weather of San Francisco.
Article in Scientific reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Authors and funding
4 authors.
Funding
Abstract
We present a novel weather analysis of San Francisco from 2009 to 2019 using concepts from quantum information theory. We describe how to transform a classical weather dataset into a quantum-inspired analytical framework by treating it as a quantum information system embedded in a quantum-like representation, with data encoded as density matrices in Hilbert space. Transforming classical weather data into quantum states is a mathematical abstraction, whereas a quantum-inspired system is not a quantum-physical system. We study a quantum-inspired analytical framework using quantum information-theoretic metrics, including fidelity, classical information, quantum information, decoherent information, Shannon and von Neumann entropies, and the quantum stability index, to represent and analyze the dataset. Furthermore, we give predictions for each quantum information metric for 2020 and 2021. We fit Fourier-series models to the metrics to explore temporal patterns and structural properties in the data.
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Registered trials
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