QIA

Empowering quantum computing with artificial intelligence (AI).

QIA develops AI-based tools aimed at optimising quantum algorithms and addressing hardware limitations associated with quantum computing.

Specifically, the project optimises computational resources for algorithms based on gates and tensor networks, with the help of AI to improve the execution of these algorithms through metrics and reduce operations necessary for their implementation.

AI-based tools are also developed for the design, control and mitigation of errors in quantum devices based on superconducting technology, especially in flux kubits.

Finally, an important part of the project is dedicated to the research of quantum AI algorithms, with special attention to Quantum Boltzmann Machines due to their adaptability to analogue hardware.

QIA is led by the company Qilimanjaro, with the participation of the Barcelona Supercomputing Center and Eurecat. On the part of the technology center, the Audiovisual Technologies Unit develops quantum machine learning algorithms applied to vision problems such as multiclass image classification, while the Applied Artificial Intelligence Unit creates reinforcement learning methods to optimise quantum circuits and calibrate quantum chips.