Winners announced in the Airbus-BMW Group Quantum Computing Challenge

This post was contributed by Damian Steiger, Martin Schuetz, Alexander Opfolter, and Helmut Katzgraber

The five winning teams of the Airbus and BMW Group Quantum Computing Challenge were announced today at the Q2B conference in Silicon Valley, California.

The challenge, focused on tackling the most pressing applications in aviation and the automative industry, was a collaboration between Airbus, BMW Group, The Quantum Insider (TQI), and the Quantum Computing Team at AWS.

We’ve discussed the importance and details of the specific use cases before, so today we get to congratulate the five winning teams for their innovative proposals to tackle these use cases.

Use Case – Smart Coating: University of Southern California

The winning team from the University of Southern California (Naman Jain and Rosa Di Felice) proposed a three-step, systematic hybrid classical/quantum protocol to study corrosion inhibitors using classical density functional theory calculations and quantum embedding models to study selected candidates using quantum hardware. The team successfully implemented variational quantum algorithm proof-of-concepts on both quantum simulators and quantum hardware.

Use Case – Quantum Powered Logistics: 4colors Research Ltd

4colors Research Ltd, a company based in Cambridge, UK, introduced an integrated (and quantum-ready) solver for production and transportation planning, designed to handle supply chain business problems at scale today on classical compute resources, with optional plug-ins for novel quantum components. Proof-of-concept experiments run on Amazon Braket demonstrate the feasibility of those quantum plug-ins.

Use Case – Quantum Enhanced Autonomy: Quandela

The training of reliable and safe AI-vision systems requires large datasets. Quandela, a company from Massy, France, proposed a hybrid approach using a quantum generative adverserial network (qGAN) to generate night-time images from day-time images.

Use Case – Quantum Solvers: University of Hamburg

A team of scientists from the University of Hamburg (Nis-Luca van Hülst, Theofanis Panagos, Greta Sophie Reese, Shahram Panahiyan, and Tomohiro Hashizume) applied techniques from quantum physics to more efficiently simulate fluid flows and sound propagation. Their method compresses the information needed to represent the fluid, potentially allowing much faster simulations.

Use Case – “Golden App” – pushing the boundaries of quantum technology for mobility: TU Delft

A team of researchers from TU Delft (Arne Wulff, Swapan Madabhushi Venkata, Boyang Chen, Sebastian Feld, Matthias Möller, and Yinglu Tang) proposed to solve the stacking sequence retrieval problem applicable, for example, for optimization of carbon fiber-reinforced plastic (CFRP) in cars and aircraft.

They use a variational quantum algorithm, which the authors simulate on a classical computer for 8 and 10 plies. Additionally, the authors present a heuristic quantum-inspired algorithm based on density matrix renormalization group (DMRG), which can be run on classical computers. They show that it outperforms existing classical solutions in many cases.

About the event

In the first phase of this competition, organizers received detailed proposals from over 100 teams from more than 25 countries, spanning from university teams to quantum companies.

Airbus and BMW Group, together with AWS, selected 15 finalists to advance to Phase II of the challenge – focused on implementing and demonstrating their innovative solutions.

Challenge participants were given AWS credits to use on Amazon Braket, the quantum computing service of AWS, where they had access to available QPUs from IonQ, IQM, QuEra, and Rigetti, and also quantum circuit simulators. An independent jury of world experts then selected the winners for each track.

Congratulations to all the winners!