Neuromorphic computing uses brain-inspired principles to design circuits that can perform
computational tasks with superior power efficiency to conventional computers. Approaches …

Strongly interacting artificial spin systems are moving beyond mimicking naturally occurring
materials to emerge as versatile functional platforms, from reconfigurable magnonics to …

The assumption that there was a “water problem” at the emergence of life—that the Hadean
Ocean was simply too wet and salty for life to have emerged in it—is here subjected to …

The pursuit of many research questions requires massive computational resources. State-of-
the-art research in physical processes using simulations, the training of neural networks for …

In-materia reservoir computing (RC) leverages the intrinsic physical responses of functional
materials to perform complex computational tasks. Magnetic metamaterials are exciting …

Neural networks have revolutionized the area of artificial intelligence and introduced
transformative applications to almost every scientific field and industry. However, this …

Artificial spin ice (ASI) consisting patterned array of nano-magnets with frustrated dipolar
interactions offers an excellent platform to study frustrated physics using direct imaging …

Traditional electronics employs charge currents to control and transmit information and
therefore suffer from energy dissipation due to electron scattering. In the past decade, spin …

The reservoir computing (RC) framework states that any nonlinear, input-driven dynamical
system (the reservoir) exhibiting properties such as a fading memory and input separability …

An idea to use a magnetic nano-dots array for a reservoir computing is introduced. The
mechanism of how the nonlinear calculation is carried out in the magnetic system is …