The New Generation of Holographic, Quantum, and ψ–Intelligence-Based Smart Mobile Devices.
All Articles are Available: Orcid ID: https://orcid.org/my-orcid?orcid=0009-0009-3175-8563 Science Open ID: https://www.scienceopen.com/user/2c98a8bc-b8bb-49b3-9c91-2f2986a7e16e Safe Creative register the work titled "The Theory of Intelligent Evolution, the Hamzah Equation, and the Quantum Civilisation". Safe Creative registration #2504151474836. .................................................................................................................................................................................................. The rapid convergence of quantum technologies, holographic interfaces, and ψ–intelligence architectures marks the dawn of a transformative era in mobile computing. This paper explores the foundational principles and innovations underpinning the development of next-generation smart mobile devices that integrate quantum computation, real-time holographic display systems, and ψ–intelligence—a multidimensional AI paradigm inspired by cognitive quantum field models and Hamzah’s equation. These devices transcend traditional limitations by enabling ultra-fast, entangled data processing, immersive 3D holographic interactions, and adaptive machine cognition that responds dynamically to user emotions, intentions, and neurofeedback. We detail the core hardware architecture—including ψ–QPU (Quantum Processing Unit), ψ–OS (Cognitive Operating System), and ψ–HoloDisplay modules—alongside novel communication protocols such as quantum-encrypted ψ-link and neuromorphic feedback loops. The paper also discusses the implications of these technologies for fields such as education, medicine, security, and multi-language real-time translation. By uniting quantum mechanics, holography, and cognitive AI within a mobile framework, this new generation of devices redefines the human-machine interface and lays the groundwork for ubiquitous, intelligent personal computing across dimensions.
Publication Details
- Journal
- Zenodo (CERN European Organization for Nuclear Research)
- Published
- 2025-08-04
- DOI
- https://doi.org/10.5281/zenodo.16739777
- Primary Topic
- Neural Networks and Reservoir Computing
- Type
- article
- Field-Weighted Citation Impact
- 0.00