Snapshotting quantum dynamics at multiple time points

Pengfei Wang, Hyukjoon Kwon (), Chun-Yang Luan, Wentao Chen, Mu Qiao, Zinan Zhou, Kaizhao Wang, M. S. Kim () and Kihwan Kim ()
Additional contact information
Pengfei Wang: Beijing Academy of Quantum Information Sciences
Hyukjoon Kwon: Korea Institute for Advanced Study
Chun-Yang Luan: Department of Physics, Tsinghua University
Wentao Chen: Department of Physics, Tsinghua University
Mu Qiao: Department of Physics, Tsinghua University
Zinan Zhou: Department of Physics, Tsinghua University
Kaizhao Wang: Department of Physics, Tsinghua University
M. S. Kim: Korea Institute for Advanced Study
Kihwan Kim: Beijing Academy of Quantum Information Sciences

Nature Communications, 2024, vol. 15, issue 1, 1-13

Abstract: Abstract Measurement-induced state disturbance is a major challenge in obtaining quantum statistics at multiple time points. We propose a method to extract dynamic information from a quantum system at intermediate time points, namely snapshotting quantum dynamics. To this end, we apply classical post-processing after performing the ancilla-assisted measurements to cancel out the impact of the measurements at each time point. Based on this, we reconstruct a multi-time quasi-probability distribution (QPD) that correctly recovers the probability distributions at the respective time points. Our approach can also be applied to simultaneously extract exponentially many correlation functions with various time-orderings. We provide a proof-of-principle experimental demonstration of the proposed protocol using a dual-species trapped-ion system by employing 171Yb+ and 138Ba+ ions as the system and the ancilla, respectively. Multi-time measurements are performed by repeated initialization and detection of the ancilla state without directly measuring the system state. The two- and three-time QPDs and correlation functions are reconstructed reliably from the experiment, negativity and complex values in the QPDs clearly indicate a contribution of the quantum coherence throughout dynamics.

Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.nature.com/articles/s41467-024-53051-5 Abstract (text/html)

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:natcom:v:15:y:2024:i:1:d:10.1038_s41467-024-53051-5

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

DOI: 10.1038/s41467-024-53051-5

Access Statistics for this article

Nature Communications is currently edited by Nathalie Le Bot, Enda Bergin and Fiona Gillespie

More articles in Nature Communications from Nature
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().