Deloitte’s Quantum Climate Challenge 2024 aims to explore the potential of quantum computers in enhancing flood forecasting to improve climate resilience. Climate change has amplified the urgency of disaster prediction in recent years. Rising temperatures and shifting weather patterns have led to more intense floods, wildfires, and other extreme occurrences. As our climate becomes increasingly volatile, accurate forecasting of extreme weather events can be the difference between life and death.
To advance disaster prediction methods, the challenge seeks to explore the application of Quantum Machine Learning (QML) to predict floods along the Wupper River in Germany. The challenge aims to develop a new approach in forecasting river floods by leveraging nascent quantum computing technologies. In doing so, it endeavors to assess the prerequisites for quantum hardware to significantly improve disaster prediction on a larger scale, and to gauge the potential timeframe for its implementation.
Due to the limitations of currently accessible quantum hardware, the goal of the challenge is two-fold:
1. Develop and train quantum models for next-day flood predictions: The primary focus lies on developing and improving a model that uses quantum computers. Due to the limitations of current quantum hardware, we do not expect models to outperform classical models at this stage.
2. Devise a path for handling more complex problems: Here, the focus lies on developing a concept for quantum or hybrid methods that may assist the improvement of flood prediction models on more advanced quantum computers. The central objective is to extend lead times for advanced warnings and to enhance the efficacy of disaster preparedness measures.
The key ingredients of our Quantum Climate Challenges are:
The Top 3 teams were:
1) ImperialQTSoc: Kuan-Cheng (Louis)Chen, Michael Ho, Felix Burt, Lily Lee
2) HHRI TeamQC: Chen-Yu Liu, Chu-Hsuan (Abraham) Lin
3) Tokenizers: Marek Grzesiak, Param Thakkar
In 2023 participants tackled a topic in the field of physical
simulation. Namely, the optimization of metal organic frameworks for carbon
capture. Capturing carbon dioxide directly from the air is a challenge that has
to be solved in order to reach the 2°C goal. Since direct air capture of carbon
dioxide is very energy intensive, more efficient filter materials are highly
sought after. Quantum computing may help improve those materials.
You can find a more detailed challenge description here.
Jurors included experts from AWS, IBM, Intel, Boehring Ingelheim,
Evonik, BASF Chemovator, Verband der Chemischen Industrie and Quantagonia.
The Top 3 teams were:
Deloitte's Quantum Climate Challenge 2022 explored how the contribution of air travel to climate change can be reduced by optimizing flight trajectories using quantum computing. The challenge scenario included a traffic sample of multiple flights with various paths and schedules. The flight trajectories were optimized such that the overall warming climate effect considering all flights is minimal while being compliant with flight safety regulations. Different climate effects depending on the fuel burn, the geographical location, altitude, weather conditions and timings were also consid-ered.
You can find a more detailed challenge description here.
Jurors included experts from AWS, IBM, RWTH, Lufthansa, DLR, MTU
and Deutsche Flugsicherung.
The Top 3 teams were: