ORCA Computing today announced the unveiling of the PT-2, the latest advancement in its PT Series of photonic quantum systems. Building on the success of the PT-1, which has deployed seven on-premises systems, the PT-2 represents a significant leap forward in practical quantum computing.

Newly opened National Quantum Computing Centre will be home to new quantum computers, designed to push the boundaries of what is possible with the technology.

ORCA Computing has been selected to build and supply a quantum computing testbed for the National Quantum Computing Centre (NQCC). Starting early this year, ORCA is developing a photonic quantum computing testbed for machine learning using its novel hybrid quantum/classical neural network architectures and photonic quantum processors. The company will complete delivery and installation of the system at the NQCC’s facilities on Harwell Campus in Oxfordshire by March 2025.

In a landmark collaboration, Honda Research Institute (HRI) and quantum software company BlueQubit have successfully executed image classification on a quantum computer using Honda’s image dataset, a groundbreaking achievement that marks the first of its kind globally. This pioneering project showcases the transformative potential of quantum computing in AI-driven industries, setting the stage for future innovations in automotive technology and robotics.

Neural networks are one typical structure on which artificial intelligence can be based. The term ›neural‹ describes their learning ability, which to some extent mimics the functioning of neurons in our brains. To be able to work, several key ingredients are required: one of them is an activation function which introduces nonlinearity into the structure. A photonic activation function has important advantages for the implementation of optical neural networks based on light propagation. Researchers in the Stiller Research Group at the Max Planck Institute for the Science of Light (MPL) and Leibniz University Hannover (LUH) in collaboration with Dirk Englund at MIT have now experimentally shown an all-optically controlled activation function based on traveling sound waves. It is suitable for a wide range of optical neural network approaches and allows operation in the so-called synthetic frequency dimension.

Using artificial intelligence, scientists can now identify complex quantum phases in materials in just minutes—a process that used to take months. The breakthrough, published in Newton, could significantly speed up research into quantum materials, particularly low dimensional superconductors. The study, a collaboration between Yale and Emory University, was seeded by a multi-institute collaboration initiative three years ago. Yale’s side of the research, led by Jinming Yang, a graduate research assistant, and Yu He, assistant professor of Yale’s Department of applied physics, was initiated under a Yale Materials Research Science and Engineering Centers (MRSEC) internal preparatory project awarded in 2022. Other senior authors include Fang Liu and Yao Wang, assistant professors in Emory’s Department of Chemistry.

Scholars at the School of Engineering of the Hong Kong University of Science and Technology (HKUST) have unveiled an innovation that brings artificial intelligence (AI) closer to quantum computing – both physically and technologically.

UC Riverside has received a Collaborative Research and Training Award of nearly $4 million from the UC National Laboratory Fees Research Program to explore how antiferromagnetic spintronics can be used to advantage in advanced memory and computing.

In research inspired by the principles of quantum mechanics, researchers from Pompeu Fabra University (UPF) and the University of Oxford reveal new findings to understand why the human brain is able to make decisions quicker than the world’s most powerful computer in the face of a critical risk situation. The human brain has this capacity despite the fact that neurons are much slower at transmitting information than microchips, which raises numerous unknown factors in the field of neuroscience.

In the quest for ultra-secure, long-range quantum communication, two major challenges stand in the way: the unpredictable nature of atmospheric turbulence and the limitations of current optical wavefront correction techniques. Researchers at the University of Ottawa, under the supervision of Professor Ebrahim Karimi, the director of Nexus for Quantum Technologies, in collaboration with the National Research Council Canada (NRC) and the Max Planck Institute for the Science of Light (Germany), have made significant advances in overcoming both obstacles. Their two latest breakthroughs—an AI-powered turbulence forecasting tool called TAROQQO and a high-speed Adaptive Optics (AO) system for correcting turbulence in quantum channels—represent a turning point in developing free-space quantum networks.