A research group from the School of Engineering and Computer Science at the Hebrew University, under the direction of Prof. Amnon Shashua, has succeeded in proving mathematically that methods leading the field of artificial intelligence can help to understand phenomena in quantum physics,
"This is an exceptional event in which the leading scientific journal in physics publishes the work of researchers from another field - computer science, and we are at a turning point in which computing power and methods Modern artificial intelligence, allow cross-domain contribution, and for example will also be an important tool in understanding nature. "
Phenomenon in systems with many quantum particles (tiny particles such as electrons) are one of the hottest topics in contemporary physics research, but even the most esteemed and experienced researchers are unable to get more than a small glimpse into the range of these phenomena. Because of the vast number of particles (over one billion billion in one gram of matter) and the multitude of interactions between them, it is very difficult to perform a simulation that will allow a comprehensive understanding of multi-particle quantum systems. Even the most powerful computer programs found it difficult to meet this challenge, which seemed impossible to crack. Up to now.
A new study by a group of doctoral students from the Computer Science Department at the Hebrew University, Yoav Levin, Or Sharir and Nadav Cohen, under the direction and direction of Prof. Amnon Shashua, has proved mathematically that deep neuronal networks, algorithms that have revolutionized the artificial intelligence world and enabled the leapfrogging in the field, Are also applied in quantum research. The use of neural networks to study physical systems has been made in recent years, but for the first time it has been shown that the networks at the forefront of the field, enabling computers to introduce advanced vision and voice recognition capabilities, can also revolutionize quantum physics. The article was published in the leading journal Physical Review Letters.
Yoav Levin, Ph.D., a research associate with the research team, said: "The paper proves that artificial intelligence algorithms can represent very complex quantum systems more efficiently than any existing approach, paving the way for a new application of modern artificial intelligence - understanding the quantum nature of the world around us."
Quantum multi-particle physics is one of the most intriguing and popular fields in physics today. This is a study that identifies how elementary particles in nature "come together" and bring surprising properties in the materials they form, such as electrical conductivity, magnetism and more. A deep understanding of the field will have a tremendous impact on all aspects of our lives. The more you discover and understand the quantum properties of materials, the closer the next revolutions in computing, energy, transportation - and range is infinite. Connecting the artificial intelligence to this field ensures fascinating developments in the coming years.