Noisy intermediate-scale quantum algorithms
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 …
integer factorization and unstructured database search requires millions of qubits with low …
Quantum walk and its application domains: A systematic review
K Kadian, S Garhwal, A Kumar - Computer Science Review, 2021 - Elsevier
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 …
random walk concept has long been used as a computational framework for designing …
Efficient on-chip training of optical neural networks using genetic algorithm
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 …
owing to their flexibility in the reconfiguration of various tasks. Its deployment of neural …
[HTML][HTML] Experimental quantum Hamiltonian learning
The efficient characterization of quantum systems,,, the verification of the operations of
quantum devices,, and the validation of underpinning physical models,,, are central …
quantum devices,, and the validation of underpinning physical models,,, are central …
Using an imperfect photonic network to implement random unitaries
We numerically investigate the implementation of Haar-random unitarity transformations and
Fourier transformations in photonic devices consisting of beam splitters and phase shifters …
Fourier transformations in photonic devices consisting of beam splitters and phase shifters …
Learning models of quantum systems from experiments
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 …
processes, it is crucial that they are faithful to the system they represent. However …
[HTML][HTML] Basic protocols in quantum reinforcement learning with superconducting circuits
L Lamata - Scientific reports, 2017 - nature.com
Superconducting circuit technologies have recently achieved quantum protocols involving
closed feedback loops. Quantum artificial intelligence and quantum machine learning are …
closed feedback loops. Quantum artificial intelligence and quantum machine learning are …
Calibration of multiparameter sensors via machine learning at the single-photon level
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 …
demanding task, as it relies on acquiring detailed modeling of the device, which can be …
Quantum autoencoders via quantum adders with genetic algorithms
L Lamata, U Alvarez-Rodriguez… - Quantum Science …, 2018 - iopscience.iop.org
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 …
which may enable an enhanced use of resources in quantum technologies. To this end …
Calibration of quantum sensors by neural networks
Introducing quantum sensors as a solution to real world problems demands reliability and
controllability outside of laboratory conditions. Producers and operators ought to be …
controllability outside of laboratory conditions. Producers and operators ought to be …