SOURCE-LINKED INTELLIGENCE

Artificial Scientific Discovery of advanced Quantum Hardware with high-performance Simulators

CORDIS · observation · Publication date unknown

t more advanced, designing new quantum experiments and hardware becomes ever more intricate for human scientists. To exploit the full potential of quantum physics, researchers have started to involve artificial intelligence in the automated design of quantum experiments. Unfortunately, even the currently most powerful methodologies have severe limitations and therefore cannot cope with the enormous potential that quantum mechanics promises us. For that reason, in ARTDISQ, I propose to build high-performance physical simulators which are at the heart of all AI-driven discovery and design efforts. The key idea is to use a framework originally developed for the efficient training and execution of large neural networks, called JAX. JAX is powerful enough to encode not only neural networks but a wide range of computer algorithms. It allows for modern high-performance computational techniques such as just-in-time compilation, auto-differentiation and direct access to the GPU. In ARTDISQ I will exploit this dramatic acceleration, which will open previously unchartered applications, includ

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award

status

SIGNED

region

EU

value

1499221

unit

EUR