Geometric quantum computation using nuclear magnetic resonance
Jonathan A. Jones (),
Vlatko Vedral,
Artur Ekert and
Giuseppe Castagnoli
Additional contact information
Jonathan A. Jones: Centre for Quantum Computation, Clarendon Laboratory
Vlatko Vedral: Centre for Quantum Computation, Clarendon Laboratory
Artur Ekert: Centre for Quantum Computation, Clarendon Laboratory
Giuseppe Castagnoli: Elsag, Via Puccini 2
Nature, 2000, vol. 403, issue 6772, 869-871
Abstract:
Abstract A significant development in computing has been the discovery1 that the computational power of quantum computers exceeds that of Turing machines. Central to the experimental realization of quantum information processing is the construction of fault-tolerant quantum logic gates. Their operation requires conditional quantum dynamics, in which one sub-system undergoes a coherent evolution that depends on the quantum state of another sub-system2; in particular, the evolving sub-system may acquire a conditional phase shift. Although conventionally dynamic in origin, phase shifts can also be geometric3,4. Conditional geometric (or ‘Berry’) phases depend only on the geometry of the path executed, and are therefore resilient to certain types of errors; this suggests the possibility of an intrinsically fault-tolerant way of performing quantum gate operations. Nuclear magnetic resonance techniques have already been used to demonstrate both simple quantum information processing5,6,7,8,9 and geometric phase shifts10,11,12. Here we combine these ideas by performing a nuclear magnetic resonance experiment in which a conditional Berry phase is implemented, demonstrating a controlled phase shift gate.
Date: 2000
References: Add references at CitEc
Citations: View citations in EconPapers (2)
Downloads: (external link)
https://www.nature.com/articles/35002528 Abstract (text/html)
Access to the full text of the articles in this series is restricted.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:nat:nature:v:403:y:2000:i:6772:d:10.1038_35002528
Ordering information: This journal article can be ordered from
https://www.nature.com/
DOI: 10.1038/35002528
Access Statistics for this article
Nature is currently edited by Magdalena Skipper
More articles in Nature from Nature
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().