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A quantum information processor with trapped ions

Authors :
Massachusetts Institute of Technology. Department of Physics
MIT-Harvard Center for Ultracold Atoms
Wang, Shannon X.
Schindler, Philipp
Nigg, Daniel
Monz, Thomas
Barreiro, Julio T.
Martinez, Esteban
Quint, Stephan
Brandl, Matthias F
Nebendahl, Volckmar
Roos, Christian F
Chwalla, Michael
Hennrich, Markus
Blatt, Rainer
Massachusetts Institute of Technology. Department of Physics
MIT-Harvard Center for Ultracold Atoms
Wang, Shannon X.
Schindler, Philipp
Nigg, Daniel
Monz, Thomas
Barreiro, Julio T.
Martinez, Esteban
Quint, Stephan
Brandl, Matthias F
Nebendahl, Volckmar
Roos, Christian F
Chwalla, Michael
Hennrich, Markus
Blatt, Rainer
Source :
IOP Publishing
Publication Year :
2014

Abstract

Quantum computers hold the promise to solve certain problems exponentially faster than their classical counterparts. Trapped atomic ions are among the physical systems in which building such a computing device seems viable. In this work we present a small-scale quantum information processor based on a string of [superscript 40]Ca[superscript +] ions confined in a macroscopic linear Paul trap. We review our set of operations which includes non-coherent operations allowing us to realize arbitrary Markovian processes. In order to build a larger quantum information processor it is mandatory to reduce the error rate of the available operations which is only possible if the physics of the noise processes is well understood. We identify the dominant noise sources in our system and discuss their effects on different algorithms. Finally we demonstrate how our entire set of operations can be used to facilitate the implementation of algorithms by examples of the quantum Fourier transform and the quantum order finding algorithm.<br />United States. Office of the Director of National Intelligence (United States. Army Research Office Grant W911NF-10-1-0284)

Details

Database :
OAIster
Journal :
IOP Publishing
Notes :
application/pdf, en_US
Publication Type :
Electronic Resource
Accession number :
edsoai.on1141890235
Document Type :
Electronic Resource