Neuro-Quantum Cyber-Geophysical Platform for Operational Multi-Hazard System Dynamic Intelligence

We present the latest developments on our integrated information physical quantum technological system dynamic framework for multiscale multidomain spatiotemporal multi-hazard intelligence. Advancing system dynamic sensing, awareness, understanding and prediction of multiscale spatiotemporal compound, cascading, coevolutionary and synergistic multi-hazards.

Our next-generation platform leverages the methodological, technological and operational capabilities of Neuro-Quantum Cyber-Physical Intelligence (NQCPI), introduced in Perdigão (2024). NQCPI entails a novel framework for nonlinear natural-based neural post-quantum information physics, along with further advances in far-from-equilibrium thermodynamics and evolutionary cognition in post-quantum neurobiochemistry, for next-generation information physical systems intelligence and security. Rooted in the inherent information physical properties of nature, NQCPI seamlessly operates across classical, quantum and post-quantum environments.

Fundamentally, NQCPI harnesses and operates with emerging nonlinear quantum properties elusive to traditional classical and quantum technological and systems intelligence structures, including new classes of high-order coevolution, emergence and entanglement. It further harnesses new neuro-quantum physical properties, with higher-order post-quantum-proof improvements in security, storage and relaying of information, crucial to fast, robust and secure operation in sensitive prediction and emergency systems.

In the scope of the Earth System Sciences and Natural Hazards, our technology is implemented as a coherent coevolutionary information physical solution spanning across the operational value chain ranging from sensing, analytics, prediction and decision support. For this purpose, it synergistically articules with our maturing technologies including QITES (Perdigão 2020), AIPSI (Perdigão and Hall 2023) and SynQ-WIN (Perdigão and Hall 2024).

The implementation is devised and operated in a cross-platform manner, encompassing seamless articulation and backward compatibility with state-of-art systems across diverse sectors. These include, but are not limited, to hydro-meteorological, naval and aerospace, civil protection and emergency management, among others.

Practical use cases are also addressed, ranging from event-scale early-warning systems to long-term decision support, where our technology has been tested and implemented. Benchmarking tests are also conducted, validating our simulations relative to observational records and assessing the added value of our solution relative to state-of-art approaches, ranging from purely physically and purely data-based to hybrid physically informed machine learning, deep learning and systems intelligence.

A window of opportunity is thus provided for further collaborations and co-creative tailored developments with further end-users, ranging from research laboratories to operational centers, given the cross-platform capabilities for workflow articulation among novel and existing infrastructures.

 

Acknowledgements: This contribution is developed in the scope of the Meteoceanics Flagship on Quantum Information Technologies in the Earth Sciences (QITES), and of the C2IMPRESS project supported by the Εuropean Union under the Horizon Europe grant 101074004.

 

References:

• Perdigão, R.A.P.; Hall, J. (2023): Augmented Information Physical Systems Intelligence (AIPSI). https://doi.org/10.46337/230414
• Perdigão, R.A.P.; Hall, J. (2024): Synergistic Nonlinear Quantum Wave Intelligence Networks (SyNQ-WIN). https://doi.org/10.46337/240118
• Perdigão, R.A.P. (2020): QITES – Quantum Information Technologies in the Earth Sciences. https://doi.org/10.46337/qites.200628
• Perdigão, R.A.P. (2024): Neuro-Quantum Cyber-Physical Intelligence (NQCPI). https://doi.org/10.46337/241024