The power of quantum computing technologies is based on the fundamentals of quantum
mechanics, such as quantum superposition, quantum entanglement, or the no-cloning …

The growth of machine learning, combined with the approaching limits of conventional
digital computing, are driving a search for alternative and complementary forms of …

Memristive devices are a class of physical systems with history-dependent dynamics
characterized by signature hysteresis loops in their input–output relations. In the past few …

Memristors are regarded as one of the key devices to break through the traditional Von
Neumann computer architecture due to their capability of simulating the function of neural …

The growing adoption of data-driven applications, such as artificial intelligence (AI), is
transforming the way we interact with technology. Currently, the deployment of AI and …

We present the first experimental realization of a quantum artificial life algorithm in a
quantum computer. The quantum biomimetic protocol encodes tailored quantum behaviors …

Quantum machine learning has emerged as an exciting and promising paradigm inside
quantum technologies. It may permit, on the one hand, to carry out more efficient machine …

Superconducting circuit technologies have recently achieved quantum protocols involving
closed feedback loops. Quantum artificial intelligence and quantum machine learning are …

The quantum autoencoder is a recent paradigm in the field of quantum machine learning,
which may enable an enhanced use of resources in quantum technologies. To this end …

Technology based on memristors, resistors with memory whose resistance depends on the
history of the crossing charges, has lately enhanced the classical paradigm of computation …