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Zero Worlds · source record · paper

Law without law: from observer states to physics via algorithmic information theory

Müller, M. P. · 2020

AI-verified citationSRC-MULLER-2020
identifier / locator
Quantum 4: 301. DOI: 10.22331/q-2020-07-20-301
url
https://quantum-journal.org/papers/q-2020-07-20-301/
verification note
Journal page retrieved and read during the 2026-08-22 batch; title, author, volume, and DOI confirmed. The abstract quote in ZW-C004 is verbatim from that page. Preprint: arXiv:1712.01826.
reliability notes
  • The foundational technical paper of algorithmic idealism, in a reputable open peer-reviewed quantum-science journal; contains the emergence theorems and the preliminary Bell result.
  • Single-author theory paper; the framework's distinctive claims have not been independently rederived.

Evidence drawn from this source

Supports· strongZW-E001

Müller 2020: the emergence theorems and the preliminary Bell result

what the source states
The paper postulates that "universal induction determines the chances of what any observer sees next," and proves within an algorithmic- information-theoretic model that observers should expect to find themselves in a stable, apparently objective external world governed by simple computable probabilistic laws — with the Boltzmann-brain problem dissolved (the transition out of a lawful history is algorithmically disfavored) and a preliminary theorem that Bell-inequality violation with preservation of no-signalling can sometimes be expected.
what we infer
The load-bearing formal result of the whole case: it demonstrates the observer-first reversal can output a lawful world rather than assume one. Note what it does not contain — any derivation that the emergent laws are specifically quantum; the Bell result is the seed of that project, not its completion.
limitations
  • Results hold in an idealized bit-string model with monotone information accumulation (the 'erasure problem', ZW-C504).
  • Universal induction is uncomputable in exact form; invariance-theorem constants are machine-dependent and matter for finite predictions.
  • Full text not re-derived for this import; characterization follows the journal abstract and the author's own exposition.