Spacetime distortion as a reason for quantum stochasticity

Eduard Prugovečki

Sayantani Bera, Priyanka Giri, Tejinder P. Singh

Eduard Prugovečki

Jincheng Zhang

This paper investigates the theoretical feasibility of quantum information transmission leveraging artificially induced spacetime distortions. The core claim proposes that controlled spacetime curvature, mimicking the effects predicted by General Relativity, can facilitate quantum information transfer between entangled particles over distances exceeding the limitations imposed by the speed of light. The proposed mechanism utilizes a specifically designed apparatus capable of generating a localized, simulated spacetime distortion. This distortion, in turn, alters the effective distance between entangled particles, allowing for instantaneous information correlation despite the spatial separation. Mathematical modeling and key equations are presented to illustrate the theoretical framework, including the relationship between spacetime curvature, quantum entanglement, and information transfer rates. The potential implications of this approach for future quantum communication technologies are discussed, acknowledging the significant technological challenges involved in realizing such a system. The central focus remains on the theoretical exploration of this novel paradigm, providing a foundational understanding for potential future research.

Aneta Mertová, Kathrin Figl, Emmanuel Pothos

Artificial intelligence has long sought to mirror human intelligence through computational models of perception, learning, and reasoning. In parallel, cognitive science has shown that human judgment frequently deviates from classical logic and probability theory. This research-in-progress investigates how quantum-probabilistic models can be implemented as quantum circuits and examines the stability of such circuits, using the conjunction fallacy as a test case. Responses are compared across human behavioural data, Monte Carlo simulations, quantum simulations, and physical quantum hardware, explicitly testing how interference-driven reasoning patterns persist under controlled stochastic and decoherence-induced noise. This comparison provides insight into how cognitive probability structures are preserved—or distorted—across classical and quantum computational implementations. The paper demonstrates a proof-of-concept pipeline for encoding cognitively motivated probability structures in computational models and evaluating their behaviour under simulation and hardware noise, with implications for future decision support system design.