We’re accelerating quantum-safe readiness—and sharing what organizations can do now to transition earlier and with confidence ...

Quantum computing is advancing fast, and nations are racing to field the first machines powerful enough to break modern encryption. This race has direct consequences for the commercial space industry, ...

Tensor networks enable researchers to tackle quantum physics problems previously thought to be solvable only by quantum computers. Credit: Lucy Reading-Ikkanda/Simons Foundation By applying a 1980s ...

Physics-aware machine learning integrates domain-specific physical knowledge into machine learning models, leading to the development of physics-informed neural networks (PINNs). PINNs embed physical ...

Will computers ever match or surpass human-level intelligence — and, if so, how? When the Association for the Advancement of Artificial Intelligence (AAAI), based in Washington DC, asked its members ...

Classiq Technologies Ltd., a maker of quantum software development tools, today announced that it has raised “tens of millions of dollars” in new funding. The capital was provided as an extension to a ...

A distinguishing feature of the neural network models used in Physics and Chemistry is that they must obey basic underlying symmetries, such as symmetry to translations, rotations, and the exchange of ...

Transition metal complexes (TMCs) are of great scientific and practical interest for applications in catalysis, biological systems, photochemistry, and sustainability, with properties highly dependent ...

Integrated quantum computing company Quantinuum Ltd. today unveiled new open-source software tools designed to accelerate software development for quantum computing with a more intuitive programming ...