European Researchers Apply for Funding to Combine Machine Learning and Quantum Science

Inside Short

• European scientists and quantum advocates have launched a call for more funding for research in the field of machine learning and quantum technology.
• Machine learning is expected to play an important role in developing quantum computing hardware and software, enabling the discovery of new molecules and materials, and automating complex quantum experiments.
• Proponents suggest that there is a need for more investment to unlock the potential of integrated fields to drive significant technological and operational advances.

A group of leading European researchers has launched a call for increased funding for machine learning and quantum technologies, with the aim of positioning Europe as a leader in the latest quantum technologies. The appeal highlights the transformative potential of combining machine learning and quantum technologies, underscoring the need for significant investment to unlock synergies that can drive significant advances in both fields.

The Potential of Machine Learning in Quantum Science

The application shows the great promise that machine learning holds for quantum science, especially because of the data-intensive nature of quantum research and the advanced computing capabilities of modern learning tools. by machine. By combining these studies, researchers aim to improve the efficiency and effectiveness of quantum experiments, which could lead to breakthroughs in quantum science and fundamental physics.

According to the petition, machine learning is expected to play an important role in developing quantum computing hardware and software, facilitating the discovery of new molecules and materials, and automating complex quantum experiments. In addition, machine learning algorithms can improve quantum processes, develop new quantum algorithms, and enable the precise manipulation of quantum devices, paving the way for energy efficient protocols and other practical benefits.

Expected Development

The combination of machine learning and quantum technology is expected to bring many advances in various fields. The researchers highlight several key areas where significant progress is expected:

1. Advances in Quantum Computing: Machine learning can improve the hardware and software aspects of quantum computing, making these systems more efficient and accessible.
2. Molecular and Information Studies: A combination of machine learning algorithms and quantum simulations can accelerate the discovery of new molecules and materials with unique properties.
3. Improved Quantum Experiments: Automating and optimizing quantum experiments with machine learning techniques can lead to faster and more accurate results.
4. New Quantum Algorithms: Developing new quantum algorithms through machine learning can solve complex problems currently beyond the reach of traditional computing.
5. Principles of Energy Management: Machine learning can help design energy-efficient protocols for controlling quantum systems, improving their performance and scalability.

Call Investment and Cooperation

To realize these advances, the appeal highlights the need for significant investment in basic and applied research. Collaboration between quantum physicists, machine learning engineers, computer scientists and industry stakeholders needs to be encouraged. Researchers argue that creating a dynamic environment with open source software, common datasets, and community-driven projects will facilitate development and innovation.

The request also emphasizes the importance of training the next generation of researchers through special programs and strengthening public relations through effective scientific communication. By creating a strong interdisciplinary research and development base, Europe can maintain its competitive edge and lead in the rapidly evolving field of quantum technologies.

For more information and to view the manifesto in detail, visit the official application site. The petition, itself, is available at the Open Petition site here.