07/22/2024, 17:17

Changed the initial slightly to make it more clear that the manifesto PDF can be found through clicking the link.


Neue Begründung:

The signatories of this petition supportpetition support the Machine Learning in Quantum Science Manifesto. The manifesto can be found under the following link:

Machine Learning in Quantum Science Manifesto Authors: N. Ares, A. Bohrdt, A. Briggs, G. Carleo, P. Erker (coordination), S. Erne, F. Fedele, M. Gärttner, E. Gil-fuster, M. Granath, S. Grünbacher, M. Heyl, M. Huber, A. F. Kockum, M. Krenn, F. Marquardt, G. Muñoz-Gil, E. van Nieuwenburg, H. Poulsen-Nautrup, P. Rembold, J. Schmiedmayer, M. Schmitt, F. Vicentini, C. Weitenberg-------------------------------Executive Summary-------------------------------Why machine learning in quantum science? Thescience? The integration of machine learning in quantum science holds significant potential due to the data-intensive nature of some areas of quantum science and the computational strengths of modern machine learning tools. This synergy can enhance the efficiency of quantum research, drive advancements in quantum technologies, and offer novel approaches to fundamental physics, making it a key area for future research and development.What advances are to be expected? Machineexpected? Machine learning will significantly enhance quantum science by improving quantum computing hardware and software, leading to new discoveries in molecules and materials. It aids in automating and optimising quantum experiments, developing new quantum algorithms, and efficiently simulating complex quantum systems. This integration will also facilitate the precise manipulation of quantum devices and the development of energy-efficient control protocols. Overall, machine learning will drive both fundamental and practical advancements in quantum science.What needs to be done to unleash these synergies? Tosynergies? To fully unleash the synergies between machine learning and quantum science, significant investment in both fundamental and applied research is needed. This includes fostering interdisciplinary collaboration between quantum physicists, machine learning engineers, computer scientists as well as industry stakeholders. Establishing a robust ecosystem with open-source software, standardised data sets and community-driven projects will facilitate progress. Training the next generation of researchers through specialised programs and enhancing public engagement through science communication are also essential. Weessential. We believe that such actions will help Europe remain competitive and lead advancements in next-generation quantum technologies.