Dynamics from noisy data with extreme timing uncertainty

R. Fung, A. M. Hanna, O. Vendrell, S. Ramakrishna, T. Seideman, R. Santra and A. Ourmazd ()
Additional contact information
R. Fung: University of Wisconsin Milwaukee
A. M. Hanna: Center for Free-Electron Laser Science, DESY
O. Vendrell: Center for Free-Electron Laser Science, DESY
S. Ramakrishna: Northwestern University
T. Seideman: Northwestern University
R. Santra: Center for Free-Electron Laser Science, DESY
A. Ourmazd: University of Wisconsin Milwaukee

Nature, 2016, vol. 532, issue 7600, 471-475

Abstract: A data-analytical approach that can extract the history and dynamics of complex systems from noisy snapshots on timescales much shorter than the uncertainty with which the data were recorded is described; the approach is demonstrated by extracting the dynamics on the few-femtosecond timescale from experimental data recorded with 300-femtosecond timing uncertainty.

Date: 2016
References: Add references at CitEc
Citations:

Downloads: (external link)
https://www.nature.com/articles/nature17627 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:532:y:2016:i:7600:d:10.1038_nature17627

Ordering information: This journal article can be ordered from
https://www.nature.com/

DOI: 10.1038/nature17627

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 ().