HORIZON EUROPE
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Expected Outcome:To significantly advance the following development priority:
FR-3 Investigate quantum sensing and computing applied to ATM. Scope:1. Quantum computing (QC) applications in ATM
Quantum computing is a domain that integrates computer science, physics, and mathematics. Quantum computing’s ability to perform complex calculations at higher speeds than classical computing opens new opportunities for solving complex problems (as ATM related NP-hard problems coming from ATM (e.g., large-scale trajectory planning, airspace configuration optimization, etc.)) in real-time.
It is acknowledged that quantum computers are not yet widely available. The objective of this research element is to explore the advantage of quantum computing in ATM. It is not expected that research will write quantum algorithms or make use of quantum machines. Quantum annealing is also in scope as a short-term, high-yield, low-risk method to quantise existing optimisation algorithms.
Research aims at exploring how quantum computing could be applied in air traffic management and how it could impact ATM. Potential (and non-exhaustive) applications include:...
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Expected Outcome:To significantly advance the following development priority:
FR-3 Investigate quantum sensing and computing applied to ATM. Scope:1. Quantum computing (QC) applications in ATM
Quantum computing is a domain that integrates computer science, physics, and mathematics. Quantum computing’s ability to perform complex calculations at higher speeds than classical computing opens new opportunities for solving complex problems (as ATM related NP-hard problems coming from ATM (e.g., large-scale trajectory planning, airspace configuration optimization, etc.)) in real-time.
It is acknowledged that quantum computers are not yet widely available. The objective of this research element is to explore the advantage of quantum computing in ATM. It is not expected that research will write quantum algorithms or make use of quantum machines. Quantum annealing is also in scope as a short-term, high-yield, low-risk method to quantise existing optimisation algorithms.
Research aims at exploring how quantum computing could be applied in air traffic management and how it could impact ATM. Potential (and non-exhaustive) applications include:
Trajectory optimisation: classical computing methods can find it challenging to compute the most efficient trajectory in real time, especially when considering that flights operate in a very dynamic environment subject to many variables (e.g., air traffic restrictions, weather conditions, changing fuel prices, etc.). Quantum computing could handle multidimensional optimisation problems with higher speed and accuracy than classical computing. These algorithms could help airspace users to identify the most energy-efficient and time-effective trajectories, significantly reducing operational costs and environmental / societal impact.Traffic flow optimisation: quantum computing could help optimising flight schedules and flight plans, and therefore to smoother traffic demand, traffic flows and potential regulations in capacity constrained scenarios. By optimising traffic flows, it could help reducing delays (e.g., ATFCM, drone delivery, etc.) and making a better use of available capacity.Emergency and contingency management: in emergency situations, an efficient and on-time decision-making is crucial. Thanks to its ability to simulate a high number of potential scenarios in a fraction of the time required by classical computing, quantum computing could help defining the best possible strategy to manage an emergency and minimise risk to passengers, flight crew, and aircraft.Separation management: quantum computing could analyse huge datasets from (e.g., radar, satellite, transponder data, etc.) in real time, to mitigate the risk of collisions and support improving sequencing and spacing and thus more effectively managing an increasingly congested airspace.Improvement of network impact assessment (NIA) functionalities towards optimiser capabilities, to provide performance-driven dynamic airspace configurations (DAC) and optimised DCB solutions.Simulation infrastructure: quantum computers could be used to train deep learning models significantly faster than classical computers, leading to breakthroughs in areas like natural language processing and image recognition.Machine learning and artificial intelligence: quantum computing could improve and accelerate machine learning algorithms by solving certain optimisation and pattern recognition tasks more efficiently. Quantum machine learning might lead to improvements in data analysis, pattern recognition, performance assessment and optimization problems. Research could also explore the interfacing of quantum programs with existing models/simulators, in order to speed up the latter.Reinforcement learning: quantum computing could be applied to accelerate the agent’s learning cycle, so the reinforcement learning process converges faster to a stable trained agent.Climate modelling: quantum computers could resolve complex climate models with greater precision, helping to understand climate change patterns, weather forecasting, and environmental impact assessments.C-UAS detection and identification - timely, quasi-immediate detection and identification of drone around sensible ground infrastructure could be handled thanks to the QC capacity. The classification of this drone (friendly, erroneous or malicious) could by identified and appropriate counter measure selected. Depending on the proposed use case(s), research shall analyse which quantum technologies / algorithms are applicable / relevant.
2. Post-quantum cryptography in ATM
Quantum computing also poses challenges in ATM as quantum capabilities could potentially break traditional encryption methods. Although quantum computers capable of breaking current encryption algorithms are not yet developed to their maximum expected capabilities, the first operational quantum computers are being deployed world-wide. The EU needs to anticipate the maturing of quantum computers and start developing transition strategies towards a quantum-safe digital infrastructure now. The Commission has been funding research and development post-quantum cryptography[1] for over a decade, recognizing the potential threat quantum computing poses to present public key cryptography.
In the short-term, post-quantum cryptography (PQC) is considered to be the most promising approach to make communications and data resistant to quantum attacks. PQC allows for a swift transition to higher protection levels to secure against a cryptanalytic attack by quantum computers. In a next step, a limited scope quantum network could be used to provide perfect forward secrecy without reliance on any asymmetric algorithms (including PQC) based on Quantum Key Distribution (QKD), which could potentially be expanded to a fully-fledged quantum communication network.
The objective of the research must be to assess the cyber-security/cryptographic needs in ATM with a sense of priority, including both the ground-ground and air-ground segments, and define a short-term roadmap for introducing PQC (phase-in and hybridization) to secure the ATM infrastructure. The project must leverage previous PQC research and consider how it may apply to ATM rather than start from a clean-sheet approach. Proposals on this topic must demonstrate awareness of the European ATM communications infrastructure. The research may optionally explore how ATM may transition to QKD (e.g., as a user of the European Quantum Communication Infrastructure (EuroQCI)).
3. Quantum sensing applications
The objective of the research is to explore how quantum sensing could be applied for air navigation of crewed aircraft and drones, for example to:
Provide high-performing alternative position, navigation and timing (A-PNT), addressing in particular resilient high-precision inertial navigation that is usable on all phases of flight. Recent geopolitical events have demonstrated the limitations of relying on satellite navigation. Indeed, while global navigation satellite systems (GNSS) including Galileo and the European geostationary navigation overlay service (EGNOS), are usually considered as suitable technologies for providing position, navigation, and timing (PNT) information as required, they can be subject to local (e.g., interference, spoofing, jamming) or global (ionospheric issues, system fault) outages, and it also presents service limitations in those areas where there is limited sky visibility. With the objective of having a back-up solution for GNSS as the source of PNT in the situations above, several potential technological solutions have been or are being developed to provide alternate position navigation and timing (A-PNT). While classical inertial sensors can provide the bandwidth and range, they do not provide sufficient accuracy for approach and landing. It is expected that the integration of quantum sensors into navigation systems could cover this gap, achieving high accuracy in autonomous positioning and increase resilience of trajectory based operations (quantum sensors do not refer to any external land- or satellite-based navigation infrastructure).Impact on datalink communications.Etc. Proposals may address alternative applications of quantum sensing to ATM provided adequate background and justification is provided.
[1] https://www.enisa.europa.eu/publications/post-quantum-cryptography-integration-study
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