Even small quantum processors perform better than conventional algorithms. (Symbol image, photo: Freepik, Wahyucuy99)
Vienna – Quantum computers on a small scale can improve the performance of algorithms of machine learning based on artificial intelligence (AI). This is what researchers of University of Vienna shown on a photonic quantum processor. In “Nature Photonics”, the experts demonstrate promising new applications for optical quantum computers.
“Quantum Machine Learning”
“Quantum Machine Learning” is the name of the new discipline, one of which is to find possible improvements in speed, efficiency or accuracy of algorithms when they run on quantum platforms. However, it remains an open challenge to achieve such an advantage with today’s quantum computing technology, it is said.
The researchers have used a photonic quantum chip on the Politecnico di Milano was developed. This indicated one of scientists in the experiment Quantinuum proposed algorithm for machine learning. The aim was to classify data points using a photonic quantum computer and to make out the contribution of quantum effects in order to understand the advantage over classic computers.
Tuned little processors
The experiment shows that even small quantum processors provide better performance than conventional algorithms. “We have found that our algorithm makes fewer mistakes in certain tasks than its classic counterpart,” said Viennese project manager Philip Walther. This means that existing quantum computers can perform well without having to exceed the current state of the art.
Source: www.pressetext.com
(PTE009/06.06.2025/11: 30)