Recent developments have led to the possibility of embedding machine learning tools into
experimental platforms to address key problems, including the characterization of the …

Quantum computers require precise control over parameters and careful engineering of the
underlying physical system. In contrast, neural networks have evolved to tolerate …

Squeezing is known to be a quantum resource in many applications in metrology,
cryptography, and computing, being related to entanglement in multimode settings. In this …

A two-level system is the most fundamental building block of matter. Its response to classical
light is well known, as it converts pulses of coherent light into antibunched emission …

In the ever-changing technological environment, the combination of artificial intelligence (AI)
with quantum computing represents an enormous potential frontier. This collaboration has …

Quantum extreme reservoir computation (QERC) is a versatile quantum neural network
model that combines the concepts of extreme machine learning with quantum reservoir …

[eng] Reservoir computing (RC) is a machine learning paradigm that exploits dynamical
systems to solve temporal tasks. This technique finds applications in very diverse fields such …