Results 61 to 70 of about 374,177 (189)

Programmable high-dimensional Hamiltonian in a photonic waveguide array

Nature Communications
Waveguide lattices offer a compact and stable platform for a range of applications, including quantum walks, condensed matter system simulation, and classical and quantum information processing.
Yang Yang, Robert J. Chapman, Ben Haylock, Francesco Lenzini, Yogesh N. Joglekar, Mirko Lobino, Alberto Peruzzo   +6 more
doaj   +1 more source

Two-electron spin correlations in precision placed donors in silicon

Nature Communications, 2018
Donor impurities in silicon are promising candidates as qubits but in order to create a large-scale quantum computer inter-qubit coupling must be introduced by precise positioning of the donors.
M. A. Broome, S. K. Gorman, M. G. House, S. J. Hile, J. G. Keizer, D. Keith, C. D. Hill, T. F. Watson, W. J. Baker, L. C. L. Hollenberg, M. Y. Simmons   +10 more
doaj   +1 more source

Quantum causal unravelling

npj Quantum Information, 2022
Complex processes often arise from sequences of simpler interactions involving a few particles at a time. These interactions, however, may not be directly accessible to experiments.
Ge Bai, Ya-Dong Wu, Yan Zhu, Masahito Hayashi, Giulio Chiribella   +4 more
doaj   +1 more source

Quantum computation with linear optics

, 1998
We present a constructive method to translate small quantum circuits into their optical analogues, using linear components of present-day quantum optics technology only.
A. Barenco, B. Yurke, C. H. Bennett, C. Miquel, C. Monroe, D. P. DiVincenzo, D. P. DiVincenzo, G. J. Milburn, I. L. Chuang, I. L. Chuang, J. P. Dowling, L. Vaidman, M. O. Scully, M. Reck, N. J. Cerf, P. W. Shor, R. P. Feynman, S. L. Braunstein, V. Degiorgio   +18 more
core   +2 more sources

Electromagnetically-induced transparency assists the Raman gradient echo memory at moderate detuning, dependent on gradient order

New Journal of Physics
Optical quantum memories are essential for quantum communications and photonic quantum technologies. Ensemble optical memories based on 3-level interactions are a popular basis for implementing these memories. All such memories, however, suffer from loss
Jesse L Everett, Ankit Papneja, Arindam Saha, Cameron Trainor, Aaron D Tranter, Ben C Buchler   +5 more
doaj   +1 more source

Surpassing the repeaterless bound with a photon-number encoded measurement-device-independent quantum key distribution protocol

npj Quantum Information, 2023
Decoherence is detrimental to quantum key distribution (QKD) over large distances. One of the proposed solutions is to use quantum repeaters, which divide the total distance between the users into smaller segments to minimise the effects of the losses in
Özlem Erkılıç, Lorcán Conlon, Biveen Shajilal, Sebastian Kish, Spyros Tserkis, Yong-Su Kim, Ping Koy Lam, Syed M. Assad   +7 more
doaj   +1 more source

Toponomic quantum computation

Modern Physics Letters A, 2022
Holonomic quantum computation makes use of non-abelian geometric phases, associated to the evolution of a subspace of quantum states, to encode logical gates. We identify a special class of subspaces, for which a sequence of rotations results in a non-abelian holonomy of a topological nature, so that it is invariant under any SO(3)-perturbation. Making
Chryssomalakos, C., Hanotel, L., Guzmán-González, E., Serrano-Ensástiga, E.   +3 more
openaire   +2 more sources

High-fidelity sub-microsecond single-shot electron spin readout above 3.5 K

Nature Communications
Electron spin qubits in semiconductors are a promising platform for large-scale quantum computing due to their small size, long coherence and manufacturability.
H. Geng, M. Kiczynski, A. V. Timofeev, E. N. Osika, D. Keith, J. Rowlands, L. Kranz, R. Rahman, Y. Chung, J. G. Keizer, S. K. Gorman, M. Y. Simmons   +11 more
doaj   +1 more source

Multiparameter optimisation of a magneto-optical trap using deep learning

Nature Communications, 2018
Dynamics in cold atomic ensembles involve complex many-body interactions that are hard to treat analytically. Here, the authors use machine learning to optimise the cooling and trapping of neutral atoms, showing an improvement in the resulting resonant ...
A. D. Tranter, H. J. Slatyer, M. R. Hush, A. C. Leung, J. L. Everett, K. V. Paul, P. Vernaz-Gris, P. K. Lam, B. C. Buchler, G. T. Campbell   +9 more
doaj   +1 more source

Flexible learning of quantum states with generative query neural networks

Nature Communications, 2022
The use of machine learning to characterise quantum states has been demonstrated, but usually training the algorithm using data from the same state one wants to characterise.
Yan Zhu, Ya-Dong Wu, Ge Bai, Dong-Sheng Wang, Yuexuan Wang, Giulio Chiribella   +5 more
doaj   +1 more source