Watch the recordings below!
This webinar will explore how quantum algorithms can be integrated into aerospace design and operations, potentially leading to more efficient efficient aircraft and satellite systems.
Programme
📅 Date: 25 June 2025
⏰ Time: 14:00 – 15:40 CET
14:00 – 14:10 | Welcome & Introduction - Hendrik Meer (Capgemini)
Overview of the EQUALITY project's mission to develop quantum algorithms for strategic industrial problems.
14:10 – 15:10 | Session 1: Three use cases from Aerospace industry - Moriz Scharpenberg, Sebastian Lange, Vincent Baudoui (Airbus)
Within the scope of EQUALITY, three uses cases from Airbus will be presented.
(i) Space Mission Optimization: Agile Earth observation satellite scheduling is a complex optimization problem that aims at selecting a maximum number of images to be taken by the satellite among a set of user requests while respecting the satellite's physical constraints. In the EQUALITY project, we study three different approaches to tackle this problem using quantum computing: "Quantum Approximate Optimization Algorithm" (QAOA), "Maximal Independent Set" (MIS) and a custom graph algorithm.
(ii) Space Data Analysis: Earth observation satellites based on Synthetic Aperture Radar technology requires sophisticated and computing intensive processing to transform raw data into images. Non-Uniform Fourier-Transformations are central elements to this processing. We found a description using a Parametrized Quantum Circuit solving these operations intrinsically. This suggest certain QML methods may have suitable inductive bias for efficient processing of SAR data.
(iii) Aerodynamics: This usecase explores quantum algorithms
as an alternative to traditional Computational Fluid Dynamic (CFD)
methods in aircraft design. It focuses on applying the DQC approach to
solve Partial Differential Equations (PDEs) of interest.
15:10 – 15:40 | Session 2: Performance of DQC on industry-relevant use cases - Smit Schaudhary (Pasqal)
We investigate the performance of the DQC algorithm on use cases
relevant to the aerospace industry. The method is applied to
differential equations of increasing complexity, aligned with the
broader objective of airfoil design. We present preliminary results,
identify current challenges and limitations, and discuss strategies for
their mitigation.
