Our projects

Winner of the Quantum Climate Challenge 2022 by Deloitte

In the Deloitte Climate Challenge, the task was to explore how the contribution of air travel to the anthropogenic climate change can be reduced by optimizing flight trajectories using quantum, quantum-classical hybrid, or quantum inspired solutions. Therefore, several flight paths with different schedules and a map showing the climate impact depending on the flight level and airplane position are given. Additionally basic safety regulations are taken into account. With respect to all these constraints the flight trajectories are optimized so that the overall negative climate effect is minimal.

In our work we implemented the nowadays fuel-efficient straight line solution and a classical genetic algorithm. Moreover, we discussed three types of quantum solutions: a Quantum Approximate Optimization Algorithm (QAOA) for Quadratic Unconstrained Binary Optimization (QUBO) problem, the quantum genetic algorithm and a quantum neural network.

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Second place of the global Qiskit Hackathon 2021

Climate change is one of the greatest challenges of our time. In order to meet the Paris Agreement, all countries have to cut down their emissions drastically. Electric mobility will play a key role in order to reduce greenhouse gas emission in the transport sector. If more and more electric vehicles enter the streets, it will become more challenging to manage the power supply. Smart charging will be necessary to improve the flexibility of the electric grid. However, smart charging faces large sized combinatorial optimization problems and many of them are NP-hard.

For our project we mainly followed a paper dealing with a case study in the field of smart charging of electrical vehicles by Constantin Dalyac and Loïc Henriet et al.

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Winner of the Qiskit Fall Fest Munich 2021

To slow down climate change, carbon capturing, and storage methods will gain in importance in the future. CCS refers to the storage of CO2 in the seabed so that it does not reach the atmosphere. Renewable energies also require large quantities of rare metals. To meet this demand, deep-sea mining, the extraction of these metals from the seabed, has recently become a topic of discussion.

To realize these projects, meaningful models of the seabed are important, but subsurface modelling is an NP hard problem. Quantum computers could help to improve these calculations, as classical computers have reached their limits with the simulations.

In our project we follow the approach of the paper "An approach to quantum-computational hydrologic inverse analysis" by Daniel O'Malley using a QAOA routine from Qiskit instead of a D-Wave quantum annealing protocol.

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Team formation