Zobrazeno 1 - 10
of 360
pro vyhledávání: '"NGUYEN, N. H."'
Autor:
Zhu, D., Johri, S., Nguyen, N. H., Alderete, C. Huerta, Landsman, K. A., Linke, N. M., Monroe, C., Matsuura, A. Y.
Publikováno v:
Phys. Rev. A 103, 032606 (2021)
A disordered system of interacting particles exhibits localized behavior when the disorder is large compared to the interaction strength. Studying this phenomenon on a quantum computer without error correction is challenging because even weak couplin
Externí odkaz:
http://arxiv.org/abs/2006.12355
Autor:
Rungger, I., Fitzpatrick, N., Chen, H., Alderete, C. H., Apel, H., Cowtan, A., Patterson, A., Ramo, D. Munoz, Zhu, Y., Nguyen, N. H., Grant, E., Chretien, S., Wossnig, L., Linke, N. M., Duncan, R.
The developments of quantum computing algorithms and experiments for atomic scale simulations have largely focused on quantum chemistry for molecules, while their application in condensed matter systems is scarcely explored. Here we present a quantum
Externí odkaz:
http://arxiv.org/abs/1910.04735
Autor:
Zhu, D., Johri, S., Linke, N. M., Landsman, K. A., Nguyen, N. H., Alderete, C. H., Matsuura, A. Y., Hsieh, T. H., Monroe, C.
Finite-temperature phases of many-body quantum systems are fundamental to phenomena ranging from condensed-matter physics to cosmology, yet they are generally difficult to simulate. Using an ion trap quantum computer and protocols motivated by the Qu
Externí odkaz:
http://arxiv.org/abs/1906.02699
Designing and implementing algorithms for medium and large scale quantum computers is not easy. In previous work we have suggested, and developed, the idea of using machine learning techniques to train a quantum system such that the desired process i
Externí odkaz:
http://arxiv.org/abs/1902.07754
Autor:
Zhu, D., Linke, N. M., Benedetti, M., Landsman, K. A., Nguyen, N. H., Alderete, C. H., Perdomo-Ortiz, A., Korda, N., Garfoot, A., Brecque, C., Egan, L., Perdomo, O., Monroe, C.
Publikováno v:
Science Advances 5, eaaw9918 (2019)
Generative modeling is a flavor of machine learning with applications ranging from computer vision to chemical design. It is expected to be one of the techniques most suited to take advantage of the additional resources provided by near-term quantum
Externí odkaz:
http://arxiv.org/abs/1812.08862
Publikováno v:
IEEE TNNLS vol 31 pp 2522-2531 (2020)
The power of quantum computers is still somewhat speculative. While they are certainly faster than classical ones at some tasks, the class of problems they can efficiently solve has not been mapped definitively onto known classical complexity theory.
Externí odkaz:
http://arxiv.org/abs/1807.03253
Autor:
Zhu, D., Johri, S., Linke, N. M., Landsman, K. A., Alderete, C. Huerta, Nguyen, N. H., Matsuurad, A. Y., Hsieh, T. H., Monroe, C.
Publikováno v:
Proceedings of the National Academy of Sciences of the United States of America, 2020 Oct . 117(41), 25402-25406.
Externí odkaz:
https://www.jstor.org/stable/26969611
This paper consists of a few results, discovered and proved during the 2012-2013 research group at Eastern Oregon University. Inertia tables are a visual representation of the possible inertias of a given graph. The inertia of a graph counts the numb
Externí odkaz:
http://arxiv.org/abs/1511.02520
Publikováno v:
Quantum Inspired Computational Intelligence: Research and Applications, S. Bhattacharyya, ed. (Morgan Kaufmann, Elsevier, 2016) rks and Learning Systems 25, 1696-1703 (2014)
In previous work, we have proposed an entanglement indicator for a general multiqubit state, which can be "learned" by a quantum system, acting as a neural network. The indicator can be used for a pure or a mixed state, and it need not be "close" to
Externí odkaz:
http://arxiv.org/abs/1510.09173
Autor:
PHUNG, D., HUANG, C., RUTHERFORD, S., CHU, C., WANG, X., NGUYEN, M., NGUYEN, N. H., DO, C. M., NGUYEN, T. H.
Publikováno v:
Epidemiology and Infection, 2015 Dec 01. 143(16), 3488-3497.
Externí odkaz:
https://www.jstor.org/stable/26513025