QITES – Quantum Information Technologies in the Earth Sciences

This page summarises the inaugural report of QITES in plain language and is its DOI landing page. The corresponding bibliographic citation is:

Perdigão, R.A.P. (2020): QITES – Quantum Information Technologies in the Earth Sciences. https://doi.org/10.46337/qites.200628

The underlying scientific and technological developments are further explored in the monograph Perdigão (2021):

Perdigão, R.A.P. (2021): Quantum Technologies in the Earth and Space Sciences. https://doi.org/10.46337/qites.m210421



Empowering the Earth Sciences with Quantum Technologies


Welcome to the Quantum era for the Earth System Sciences and associated Services. The Meteoceanics QITES Alliance – Quantum Information Technologies in the Earth Sciences – emerged from our chair as a new structure to nest our interdisciplinary activities at the interface among Quantum Technologies, Physics of Complex Systems and Earth System Sciences, from fundamental research and algorithmic development to cutting-edge product development and institutional services including remote sensing, big data analytics, risk assessment, dynamic prediction and decision support. This is further empowered by our recently deployed Meteoceanics QITES Constellation with a new breed of technologies, developed in-house, at the synergistic interface among frontier physics of complex systems, gravitation, magnetohydrodynamics and quantum mechanics.

We develop novel quantum information and sensing technologies to see the “invisible” and predict the “unpredictable” in Earth System Dynamics and Natural Hazards. Our new constellation Meteoceanics QITES provides unprecedented 4D spatiotemporal coverage, resolution and lead.


Facing an herculean challenge

The increasingly demanding forecasting and prediction challenges pertaining the Earth system, especially the computation overstretch stemming from allying highly detailed spatiotemporal resolution to long-range prediction, along with massive amounts of data and complexity of interrelations to explore, call for the development of quantum computational techniques for enabling a swift but rigorous treatment of these problems.

The development of more computationally efficient and deeper phenomenologically mindful data analytics and model design tools is done in coordination with those in quantum technologies. This provides an excellent opportunity for cross-fertilisation and co-construction, along with a crucial opportunity for data analysts and modellers to actually reflect and reconnect with the underlying fundamentals at play in the processes.

While quantum computing hardware technologies are still at a relative infancy, our advances in the underlying mathematics and information physics already enable us now to design and develop novel efficient analytical and algorithmic approaches to tackle otherwise untreatable situations – if we stand at the forefront of both Quantum and Geophysical Sciences.

For example, we are at a stage wherein world class weather centres struggle to cope with overwhelming amounts of information and complexity, racing to exhaustion and frustration as Richardson’s human computers did in the past. With the introduction of the electronic computer, what once seemed unfathomable became seamless and Richardson’s vision of comprehensive weather forecasting became an operational reality.

Now, when classical computational geosciences reach their limits and high-resolution long-term prediction appears to be beyond reach, especially given the inherent complexity and predictability challenges of the Earth system, it is time to take a quantum leap into a new era of Earth system modelling across multiple spatiotemporal domains and scales.

More than faster computing, it is about smarter computing. One in which fundamental science is back to challenge our minds, and to reconnect us with nature.

The rise of QITES

Our chair has recently conquered the chance to enact such transition, starting with the reformulation of Earth prediction systems. To that end, we do not necessarily need full-fledged quantum computers right away, though we are already building and operating them with increasing levels of sophistication. At this stage, the mathematical physics of quantum information and complexity that we develop with geophysical applications in mind already enable us to stand at an unrivalled position to prepare for the new generation of models and applications.

The overall effort stems from the novel theoretical foundations of Fluid Dynamical Systems: from Quantum Gravitation to Thermodynamic Cosmology, introduced by Prof. Rui Perdigão (Perdigão, 2017). Since then, Rui Perdigão has been crafting novel Computational Fluid Dynamic and Dynamical System Analytics, Information Physics, Artificial Intelligence and Model Design techniques benefitting from a coevolutionary learning process at the interface between the geophysical sciences and quantum information sciences. Moreover, he has also unified coevolutionary deep learning and artificial intelligence based inverse modelling and first principle based forward modelling frameworks with his Synergistic Dynamic Theory of Complex Coevolutionary Systems (Perdigão 2018), along with the first methodological and applied developments onto the Geophysical Sciences in Perdigão, Pires and Hall (2019).

One of the crucial advances entailed the unveiling and treatment of causal dynamics across coevolutionary space-times, which is elusive to traditional quantum theory but present in multiscale Earth System Dynamics. The recent monograph Synergistic Dynamic Causation and Prediction in Coevolutionary Spacetimes (Perdigão, 2020) takes a detailed account of novel neo-classical, quantum and post-quantum treatments of causation and prediction introduced by the author Prof. Rui Perdigão, thereby shedding not only fundamental light onto the problem but also providing methodological pathways to enact practical predictions and evaluate the associated predictability and uncertainty.

Dissemination and Outlook

The independent funding structure of the endeavour and the ongoing intricate web of intellectual property proceedings currently precludes free sharing of the products and services. However, these are gradually becoming available to relevant institutional entities entrusted with high-level environmental, security and other socially relevant missions.

The collaborative links being established between our Institute and institutions positioned at both geophysical and quantum sides of the alliance further strengthens the upcoming developments, including towards novel quantum technologies optimised for Earth system dynamic analysis, modelling and decision support.

Training and course programs are also available for students enrolled at the Meteoceanics Doctoral School, directly or through partner institutions, along with other training opportunities for public and private sector professionals and institutions seeking to engage with us in this enthusiastic quest.


Perdigão R.A.P. (2017): Fluid Dynamical Systems: from Quantum Gravitation to Thermodynamic Cosmology. https://doi.org/10.46337/mdsc.5091.
Perdigão R.A.P. (2018): Synergistic Dynamic Theory of Complex Coevolutionary Systems. https://doi.org/10.46337/mdsc.5182.
Perdigão R.A.P., Pires C.A.L., & Hall J. (2019): Disentangling Nonlinear Spatiotemporal Controls on Precipitation: Dynamical Source Analysis and Predictability. https://doi.org/10.46337/mdsc.5273.
Perdigão R.A.P. (2020): Synergistic Dynamic Causation and Prediction in Coevolutionary Spacetimes. https://doi.org/10.46337/mdsc.5546.


Further Work on this project (after the publication of this report):

Perdigão R.A.P. (2021): Quantum Technologies in the Earth and Space Sciences. doi: 10.46337/qites.m210421

Perdigão R.A.P. (2021): Designing Quantum Computational Models for the Earth and Space Sciences. doi: 10.46337/qites.m210421.qcm
Perdigão R.A.P. (2021): Enhancing Natural Hazard Early Warning Systems with Quantum Satellite Technologies. 10.46337/qites.m210421.qst
Perdigão R.A.P. (2021): Quantum Machine Learning and Artificial Intelligence in Astrophysics and Cosmology. doi: 10.46337/qites.m210421.qas
Perdigão R.A.P. (2021): Quantum Machine Learning and Artificial Intelligence in the Geophysical Sciences. doi: 10.46337/qites.m210421.qgs
Perdigão R.A.P. (2021): Sensing Earth System Dynamics with Quantum Gravitational Interferometry. doi: 10.46337/qites.m210421.qgi

Perdigão R.A.P. (2022): Quantum Leaps in Complex System Sciences and Technologies. doi: 10.46337/qites.m211115

Perdigão R.A.P. (2022): Quantum Leaps in Gravitational and Electrodynamic Sensing. doi: qites.m211115.qge
Perdigão R.A.P. (2022): Quantum Leaps in Computation and Prediction. doi: 10.46337/qites.m211115.qcp
Perdigão R.A.P. (2022): Taking the Quantum Pulse of the Planet. doi: 10.46337/qites.m211115.qpp
Perdigão R.A.P. (2022): Beyond Quantum, towards the Firmament of Complexity. doi: 10.46337/qites.m211115.qfc
Perdigão R.A.P. (2022): Paving Emerging Pathways in Frontier Physics. doi: 10.46337/qites.m211115.qfp
Perdigão R.A.P. (2022): From Frontier Physics to the Environment and Society. doi: 10.46337/qites.m211115.qes

Perdigão R.A.P. and Hall J. (2022): Deciphering Hydroclimatic Complexity with Information Physics and Quantum Technologies, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-8372, https://doi.org/10.5194/egusphere-egu22-8372, 2022.

Perdigão R.A.P. and Hall J. (2023): Augmented Information Physical Systems Intelligence (AIPSI) for enhanced spatiotemporal early detection, attribution, prediction and decision support on multi-hazards, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-6617, https://doi.org/10.5194/egusphere-egu23-6617, 2023.

Source document details:

Title: QITES – Quantum Information Technologies in the Earth Sciences.
Author: Perdigão, Rui A. P.
Date: June 28th, 2020
DOI: https://doi.org/10.46337/qites.200628
Indexed: Yes (Crossref)
Cite as: Perdigão R.A.P. (2020): QITES – Quantum Information Technologies in the Earth Sciences. https://doi.org/10.46337/qites.200628

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