Deterministic generation of a twin-Fock state of two nitrogen-vacancy ensembles via a superconducting flux qubit

The twin-Fock state plays a central role in quantum metrology and quantum information processing. Here, we propose a method to generate a twin-Fock state of two nitrogen-vacancy-center (NV) ensembles using a superconducting flux qubit. This state is deterministically prepared by simultaneously exciting two NV ensembles with the flux qubit. Numerical simulations demonstrate that twin-Fock states with n⩽6 can be prepared with high fidelity using current experimental technology. This proposal is universal and can be employed with other solid-state devices coupled to a superconducting qubit.

Authors

Institutions

Publication Details

Journal
Applied Physics Letters
Published
2025-10-13
DOI
https://doi.org/10.1063/5.0297004
Primary Topic
Molecular Junctions and Nanostructures
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Deterministic generation of a twin-Fock state of two nitrogen-vacancy ensembles via a superconducting flux qubit

Tong Liu, Jin Xu
Applied Physics Letters
Molecular Junctions and Nanostructures
article

Deterministic generation of a twin-Fock state of two nitrogen-vacancy ensembles via a superconducting flux qubit

Tong Liu, Jin Xu
article en

Abstract

The twin-Fock state plays a central role in quantum metrology and quantum information processing. Here, we propose a method to generate a twin-Fock state of two nitrogen-vacancy-center (NV) ensembles using a superconducting flux qubit. This state is deterministically prepared by simultaneously exciting two NV ensembles with the flux qubit. Numerical simulations demonstrate that twin-Fock states with n⩽6 can be prepared with high fidelity using current experimental technology. This proposal is universal and can be employed with other solid-state devices coupled to a superconducting qubit.

Applied Physics LettersVol. 127(15)
Shangrao Normal University (CN)
Openalex Percentile: Top 71%
Molecular Junctions and Nanostructures
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.