This petition is a call for European funding of research at the interface of machine learning and quantum science as a foundation of future key technologies.
Reason
Razões
The signatories of this petition support the 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
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Executive Summary
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Why machine learning in quantum science? 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? 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? 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.
We believe that such actions will help Europe remain competitive and lead advancements in next-generation quantum technologies.
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Estatísticas da petição
Apoiadores por país
| País | Número | Quórum (?) |
|---|---|---|
| Österreich | 6 | 0,04% |
| United Kingdom | 6 | 0,01% |
| Deutschland | 5 | 0,01% |
| Nederland | 2 | 0,01% |
distribuição de assinatura
Porque as pessoas assinam
Jena
I am a quantum physicist working on leveraging ML for quantum science and vice versa.
Lewes
Quantum hardware enabled learning offers an alternative approach to using quantum technology for information processing and control. This is parallel to the current qubit+gare+circuit model but may not need the full error hardware layer.
Krakow
Machine learning can help solving problems in quantum mechanics
and quantum mechanics can help improving machine learning...
Hägersten
Machine learning has revolutionized many fields of science from biology to astrophysics. Comparatively speaking, quantum physics has lagged behind and therefore there is not only a big necessity to foster efforts to encourage a deeper cross fertilization between these two disciplines but also a huge potential for development of potentially revolutionary new results. I’m thinking in particular of using machine learning to encode quantum states efficiently, determine new protocols to operate with quantum systems, automate the search for materials with novel properties, explore phases with technological applications, and much more. This petition therefore has my strongest support.
Espoo
Many open challenges in quantum science and quantum technologies can be potentially solved by leveraging machine learning. Machine learning can enable breakthroughs in all areas of quantum technologies, including quantum sensing, quantum materials, quantum computing, quantum information and quantum communication. Fostering a vibrant community bringing together machine learning and quantum science will help us solve fundamental and applied problems in quantum science that may remain otherwise unsolvable. This would represent a strategic decision that will further establish and solidify European competitiveness in quantum technologies.
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