The next ELLIS-ESA workshop on Quantum Algorithms and Machine learning is coming
ELLIS and ESA Φ-lab are co-organising the next workshop on Quantum Algorithms and Machine Learning for huge data analysis, simulation and potential Earth observation applications on Thursday 27 May, from 13:00 to 19:00 CEST. Registrations are available through the workshop website.
Quantum Computing has the potential of revolutionising information processing and becoming a key enabler for computationally hard engineering and scientific problems. Recent advances in quantum technologies and quantum algorithms make this game-changing turn more likely.
Quantum computers promise to redefine computing and allow to make certain complex computations in a drastically reduced time. In terms of data analytics, they might enable us to sample and explore huge volumes of scattered data, to identify and retrieve specific patterns, and optimize functionals for many kinds of use-cases. In terms of physics simulation, they will enable solving inverse problems entailing partial differential equations with applications to e.g. geophysical fluid dynamics. Today, thanks to progress in Noisy Intermediate-Scale Quantum (NISQ) devices and classical-quantum hybrid computing, promising approaches are already tested on real machines.
Earth observation (EO) gathers global information about our planet’s physical, chemical and biological systems via sensing devices. A recurrent issue in EO is the solution of inverse, ill-conditioned problems, which includes specific land-cover identification, biophysical parameter estimation and feature extraction, atmospheric inverse problems, gravimetry, etc. EO needs the unprecedented power of Quantum Computers to face computing challenges such as those in:
- Synthetic Aperture Radar (SAR) processing: phase unwrapping for SAR, polarimetric SAR and interferometric SAR, with applications to elevation modelling for SAR imaging;
- Multispectral / hyperspectral processing: machine learning applied to images and hyperspectral data cubes, resulting in a new range of AI4EO methods, optimised and scaleable to the challenging volumes of global EO daily imaging and archives, key to all downstream products;
- Processing of Earth system measurements (aerosols, atmospheric or ocean measurements, etc.) in climate and weather modeling and data assimilation, with better solvers and optimisers, leading to improved temporal modelling, forecasting and Earth system simulation.
The programme will include:
- 13:00-17:00 CEST – Keynote talks (with audience)
- 17:00-19:00 CEST – Roundtable and panel discussion (closed session)