Open Access
Open access
volume 26 issue 10 pages 103029

Quantum sensing with tunable superconducting qubits: optimization and speed-up

Sergey Danilin
Nicholas Nugent
N Nugent
Publication typeJournal Article
Publication date2024-10-01
scimago Q1
wos Q2
SJR0.936
CiteScore5.5
Impact factor2.8
ISSN13672630
Abstract

Sensing and metrology are crucial in both fundamental science and practical applications. They meet the constant demand for precise data, enabling more dependable assessments of theoretical models’ validity. Sensors, now a common feature in many fields, play a vital role in applications like gravity imaging, geology, navigation, security, timekeeping, spectroscopy, chemistry, magnetometry, healthcare, and medicine. The advancements in quantum technologies have sparked interest in employing quantum systems as sensors, offering enhanced capabilities and new possibilities. This article describes the optimization of the quantum-enhanced sensing of magnetic fluxes with a Kitaev phase estimation algorithm based on frequency tunable transmon qubits. It provides the optimal flux biasing point for sensors with different qubit transition frequencies and gives an estimation of decoherence rates and achievable sensitivity. The use of 2- and 3-qubit entangled states are compared in simulation with the single-qubit case. The flux sensing accuracy reaches 10 8 Φ 0 and scales inversely with time, which proves the speed-up of sensing with high ultimate accuracy.

Found 
Found 

Top-30

Journals

1
Physical Review B
1 publication, 9.09%
Nature Communications
1 publication, 9.09%
IEEE Transactions on Applied Superconductivity
1 publication, 9.09%
Frontiers in Computer Science
1 publication, 9.09%
Physical Review A
1 publication, 9.09%
PRX Quantum
1 publication, 9.09%
Applied Physics Reviews
1 publication, 9.09%
Physical Review Research
1 publication, 9.09%
Quantum Science and Technology
1 publication, 9.09%
SciPost Physics Core
1 publication, 9.09%
Scientific Reports
1 publication, 9.09%
1

Publishers

1
2
3
4
American Physical Society (APS)
4 publications, 36.36%
Springer Nature
2 publications, 18.18%
Institute of Electrical and Electronics Engineers (IEEE)
1 publication, 9.09%
Frontiers Media S.A.
1 publication, 9.09%
AIP Publishing
1 publication, 9.09%
IOP Publishing
1 publication, 9.09%
Stichting SciPost
1 publication, 9.09%
1
2
3
4
  • We do not take into account publications without a DOI.
  • Statistics recalculated weekly.

Are you a researcher?

Create a profile to get free access to personal recommendations for colleagues and new articles.
Metrics
12
Share
Cite this
GOST |
Cite this
GOST Copy
Danilin S. et al. Quantum sensing with tunable superconducting qubits: optimization and speed-up // New Journal of Physics. 2024. Vol. 26. No. 10. p. 103029.
GOST all authors (up to 50) Copy
Danilin S., Nugent N., Nugent N., Weides M. P. Quantum sensing with tunable superconducting qubits: optimization and speed-up // New Journal of Physics. 2024. Vol. 26. No. 10. p. 103029.
RIS |
Cite this
RIS Copy
TY - JOUR
DO - 10.1088/1367-2630/ad49c5
UR - https://iopscience.iop.org/article/10.1088/1367-2630/ad49c5
TI - Quantum sensing with tunable superconducting qubits: optimization and speed-up
T2 - New Journal of Physics
AU - Danilin, Sergey
AU - Nugent, Nicholas
AU - Nugent, N
AU - Weides, Martin P.
PY - 2024
DA - 2024/10/01
PB - IOP Publishing
SP - 103029
IS - 10
VL - 26
SN - 1367-2630
ER -
BibTex |
Cite this
BibTex (up to 50 authors) Copy
@article{2024_Danilin,
author = {Sergey Danilin and Nicholas Nugent and N Nugent and Martin P. Weides},
title = {Quantum sensing with tunable superconducting qubits: optimization and speed-up},
journal = {New Journal of Physics},
year = {2024},
volume = {26},
publisher = {IOP Publishing},
month = {oct},
url = {https://iopscience.iop.org/article/10.1088/1367-2630/ad49c5},
number = {10},
pages = {103029},
doi = {10.1088/1367-2630/ad49c5}
}
MLA
Cite this
MLA Copy
Danilin, Sergey, et al. “Quantum sensing with tunable superconducting qubits: optimization and speed-up.” New Journal of Physics, vol. 26, no. 10, Oct. 2024, p. 103029. https://iopscience.iop.org/article/10.1088/1367-2630/ad49c5.
Profiles