Explanation
The quantum technology being developed is primarily aimed at addressing six major types of challenge:
1. Complex optimisation problems
It is applied to supply chains, last-mile delivery, routes with time restrictions, maintenance and procurement planning, resource allocation, urban traffic management, power grid topology, power plant operations, communications networks and the relocation of virtual machines. In other words, problems where there are a vast number of possible combinations and the best decision needs to be found within a reasonable timeframe and at a reasonable cost.
2. Prediction, classification and advanced data analysis
The project covers applications such as customer analysis, fraud detection, assembly time prediction, image classification for industrial inspection, satellite image processing and the analysis of pharmacological responses in patients. Here, quantum computing is used to support hybrid quantum-classical models and more demanding machine learning tasks.
3. Cybersecurity and secure communications
Another clear challenge is the protection of infrastructure and data in the new ‘quantum-safe’ landscape. Such use cases include post-quantum cryptography in OT/IoT environments, anomaly detection to anticipate cyberattacks, secure interconnection of nodes using QKD, and the synchronisation and control of secure quantum communications in critical infrastructure.
4. Health, biotechnology and drug discovery
Quantum technology is linked to the discovery of new drugs, pharmacological analysis, the prediction of treatment responses and the early detection of biomarkers for cognitive disorders. In these types of applications, the main challenge is to manage highly complex systems—whether molecular, biological or clinical—in order to accelerate diagnosis and precision medicine.
5. Simulation, sensor integration and control of complex physical systems
The project also focuses on advanced digital twins, quantum sensors in industrial systems, Earth-space quantum links, and components for quantum computing such as low-noise amplifiers for qubit readout. The aim is not merely to optimise decision-making, but to improve measurement, simulation and the operation of highly complex physical systems.
6. Defence and critical scenarios
Several applications relate to asymmetric warfare, smart defence, defence logistics and the protection of scientific or strategic infrastructure. In this context, quantum technology is a dual-use technology: useful both for security and resilience and for operational superiority in complex environments.
Sectors of use
As for the sectors in which they are used, the most common are:
Manufacturing industry
Assembly, maintenance, quality control, resource allocation and industrial logistics.
Energy
Electricity grids, renewable energy, ports, hydrolysis and operational efficiency.
Logistics and transport / smart mobility
Supply chain, last mile, routes, urban traffic and mixed fleets.
Finance
Customer analysis, fraud, risk, pricing and financial advice.
Telecommunications and IT
Networks, data centres, QKD and satellite image processing.
Health, biotechnology and the pharmaceutical industry
Medicine discovery, pharmacological response and early diagnosis.
Defence and security
Cybersecurity, asymmetric warfare, secure communications and critical logistics.
Aerospace
Digital twins, Earth-space quantum links and image processing.
List
1. Quantum-Enabled Digital Twin (QEDT).
2. PQC in quantum-safe environments within industrial settings (OT, IoT).
3. Quant-AIR: characterisation and prediction of assembly times.
4. Customer analysis.
5. Maintenance planning and resource procurement.
6. QFAIR: Quantum Fraud Analysis & Intelligent Recognition.
7. Supply chain optimisation.
8. Quantum sensors in industrial systems. Development of quantum sensor technology for the certification of water obtained by reverse sublimation, ensuring it is free from contaminants.
9. Urban traffic management.
10. Pharmacological analysis: discovery of new drugs.
11. Communications network optimisation.
12. Anomaly detection in IoT systems for anticipating cyberattacks.
13. Quantum optimisation of last-mile delivery and sustainable urban logistics with heterogeneous fleets.
14. Secure interconnection of nodes via point-to-point QKD.
15. Earth-Space quantum link demonstrator.
16. Optimisation of virtual machine allocation and relocation in data centres.
17. Advanced planning of specialised human resources.
18. Market-based optimisation of energy assets.
19. Quantum computing applied to the analysis and prediction of pharmacological response in patients.
20. Optimisation of resource allocation using quantum annealing.
21. Energy Management System for network operations in port environments.
22. Soolvie, a sustainable objective-oriented logic for valuable impact efficiency based on quantum collective AI.
23. Synchronisation and control for secure quantum communications (QKD) in critical scientific infrastructures.
24. Satellite image processing via Quantum Machine Learning (QML) and hybrid architectures with AI.
25. Intelligent defence system in asymmetric warfare.
26. Implementation of quantum-secure solutions in OT communications at an energy generation plant.
27. Network traffic shielding against anomalous traffic.
28. Route optimisation with time constraints for goods logistics.
29. Quantum-inspired optimisation of electricity grids using Tensor Networks (TN).
30. Global optimisation of grid operations with the aim of maximising service efficiency.
31. Optimisation of Mobile Network Densification in Urban Environments.
32. hAIckers SHIELD: A Quantum Collective AI Defence Solution for Cybersecurity & Digital Trust based on QGANS.
33. QAI-SCENIC – The Quantum Collective AI Core for Complex Scenario Optimisation.
34. Low-noise amplifiers for qubit readout in quantum computers.
35. Quantum Annealing for the Integrated Optimisation of Logistics and Manufacturing.
36. Agent optimisation using Quantum Reinforcement Learning (QRL) applied to autonomous navigation and conflict resolution in aerospace environments.
