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Bold Philosophical Positioning:
The manuscript takes a clear stance supporting Einstein’s local-realist worldview, providing a systematic critique of the assumptions behind Bell’s theorem and standard quantum theory.
Logical and Mathematical Clarity in Presentation:
The author rigorously defines the topological limitations of measurement using concepts from metric topology.
The so-called General Principle of Measurements is coherently argued and formally stated.
Internal Consistency:
The proposed reinterpretation—shifting from “superposition as conjunction” to “superposition as disjunction”—is logically self-consistent within the author’s framework.
Misinterpretation of Bell’s Theorem:
The paper repeatedly claims that Bell “mistook” deterministic correlations for non-locality, which misrepresents the nature of Bell's theorem. Bell did not conflate correlation with causation but derived inequalities from local realism assumptions, which quantum predictions (and experiments) violate.
The assertion that Bell’s theorem does not apply to Einstein’s view is speculative and not supported by mainstream quantum foundations literature.
Use of an Axiomatic Principle with Limited Physical Justification:
The General Principle of Measurements claims that precise space-time coordinates are physically meaningless, but this seems to conflate practical measurability with ontological inaccessibility. Physics routinely deals with idealizations.
Neglect of Experimental Evidence:
The manuscript largely dismisses decades of high-precision experiments violating Bell inequalities (e.g., Aspect, Zeilinger, and others) by attributing them to conceptual confusion or “imaginary objects,” without engaging with the robustness of those experimental setups.
Lack of Predictive Power:
Although the author argues that his framework retains the predictive power of standard quantum theory, the paper offers no new predictions or calculations within the completed theory that differ from the standard model.
The authors declare that they have no competing interests.
The authors declare that they used generative AI to come up with new ideas for their review.
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