Schilling, Andreas (2025) Randomness, Quantum Uncertainty, and Emergence: A Suggestion for Testing the Seemingly Untestable. [Preprint]

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Abstract

The functioning of complex natural structures, such as living systems, has eluded a generally accepted theoretical basis and empirical verification for decades, partly because of a lack of meaningful experiments. We therefore propose a class of experiments designed to test whether hitherto unknown principles of order are at work in sufficiently complex natural dynamical systems that cannot be captured by known physical laws. The underlying working hypothesis, which has already been formulated in various forms by several authors, is that the quantum mechanical uncertainty principle leaves room for ordering phenomena in the sense of a strong emergence principle in chaotic or nearly chaotic physical systems, which would not be expected if they were treated according to conventional modelling approaches. The key idea behind testing this undoubtedly bold hypothesis is to compare two sufficiently complex, virtually identical setups, one of which is operating with deterministic pseudo-random number generators placed at certain key points that are sensitive to small changes, while the other is equipped with quantum-based physical random-number generators, the two setups being otherwise identical. Existing neural networks are proposed as suitable test objects for this purpose, and the overall performance under identical training conditions could be used as a quantitative benchmark. As the working hypothesis used goes far beyond artificial networks, a successful outcome of such an experiment could have strong implications in many other branches of science.

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Item Type:	Preprint
Creators:	Creators Email ORCID Schilling, Andreas andreas.schilling@physik.uzh.ch 0000-0002-3898-2498
Keywords:	Complex systems, neural networks, emergence, uncertainty principle, randomness
Subjects:	Specific Sciences > Artificial Intelligence General Issues > Computer Simulation General Issues > Determinism/Indeterminism Specific Sciences > Artificial Intelligence > Machine Learning General Issues > Theory/Observation
Depositing User:	Prof. Andreas Schilling
Date Deposited:	15 May 2025 12:18
Last Modified:	15 May 2025 12:18
Item ID:	25313
Subjects:	Specific Sciences > Artificial Intelligence General Issues > Computer Simulation General Issues > Determinism/Indeterminism Specific Sciences > Artificial Intelligence > Machine Learning General Issues > Theory/Observation
Date:	13 May 2025
URI:	https://philsci-archive.pitt.edu/id/eprint/25313

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• Randomness, Quantum Uncertainty, and Emergence: A Suggestion for Testing the Seemingly Untestable. (deposited 15 May 2025 12:18) [Currently Displayed]
  • Randomness, Quantum Uncertainty, and Emergence: A Suggestion for Testing the Seemingly Untestable. (deposited 19 May 2025 13:04)

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