A universal fault-tolerant quantum computer that can efficiently solve problems such as
integer factorization and unstructured database search requires millions of qubits with low …

Quantum random walk is the quantum counterpart of a classical random walk. The classical
random walk concept has long been used as a computational framework for designing …

Recent advances in silicon photonic chips have made huge progress in optical computing
owing to their flexibility in the reconfiguration of various tasks. Its deployment of neural …

The efficient characterization of quantum systems,,, the verification of the operations of
quantum devices,, and the validation of underpinning physical models,,, are central …

As Hamiltonian models underpin the study and analysis of physical and chemical
processes, it is crucial that they are faithful to the system they represent. However …

We numerically investigate the implementation of Haar-random unitarity transformations and
Fourier transformations in photonic devices consisting of beam splitters and phase shifters …

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

Calibration of sensors is a fundamental step in validating their operation. This can be a
demanding task, as it relies on acquiring detailed modeling of the device, which can be …

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 …

In this work, we present a method to characterize the transmission matrices of complex
scattering media using a physics-informed, multi-plane neural network (MPNN) without the …