
The Quantum Turing Test (QTT) is proposed as a heuristic framework for evaluating whether outputs generated by non-conventional physical or informational systems exhibit structured behavior distinguishable from stochastic noise. Unlike the classical Turing Test, the QTT does not attempt to infer intelligence, consciousness, or agency. Instead, the framework focuses on the statistical, structural, and parametric properties of decoded outputs, including coherence, reproducibility, sensitivity to parameter perturbation, and resistance to post-hoc tuning. The Quantum Turing Test is explicitly agnostic regarding the origin of observed structure and is designed to be transparent, reproducible, and falsifiable. This work presents the conceptual foundations, scope, and limitations of the Quantum Turing Test as a methodological filter for determining when an observed result warrants further investigation beyond random processes.
Quantum Turing Test, structured signals, pattern vs noise, parameter sensitivity, Turing Test extension, non-conventional systems, QTT, signal processing, reproducibility
Quantum Turing Test, structured signals, pattern vs noise, parameter sensitivity, Turing Test extension, non-conventional systems, QTT, signal processing, reproducibility
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