Quick Navigation
Topics
Trapped Ion Quantum Computing
Localization and coherent control of 25 nuclear spins in Silicon Carbide
arXiv
Authors: Pierre Kuna, Erik Hesselmeier-Hüttmann, Phillip Schillinger, Felix Gloistein, István Takács, Viktor Ivády, Wolfgang Knolle, Jawad Ul-Hassan, Jörg Wrachtrup, Vadim Vorobyov
Year
2025
Paper ID
36328
Status
Preprint
Abstract Read
~2 min
Abstract Words
135
Citations
N/A
Abstract
Optically addressable spin defects are excellent candidate platform for quantum sensing and quantum network. Nuclear spins coupled to color centers naturally enable long lived quantum memories and local qubits registers. To fully leverage this potential precise characterization of the surrounding nuclear-spin environment augmented with refined DFT models is required. In this work, we report angstrom-level 3D localization of 25 nuclear spins around a single V2 center in 4H Silicon Carbide. Utilizing specially placed robust nuclear memory as a highly efficient readout ancilla for readout, we apply correlation based spectroscopy and by selecting multi-spin chains up to length four, we access and characterize extended nuclear spin cluster. Using the coupling map we reconstruct their couplings to the central electron spin and neighboring nuclei. This work paves the way towards advanced quantum register applications on Silicon Carbide platform.
Why This Paper Matters
- This paper contributes to the Trapped-Ion Quantum Computing research area in the Quantum Articles archive.
- It adds a 2025 reference point for readers tracking recent quantum research.
- Optically addressable spin defects are excellent candidate platform for quantum sensing and quantum network.
Paper Tools
Become a member to use research tools
Sign in to open papers, visit source links, share, cite, compare, copy DOI links, request category corrections, and build your reading list.
Show Paper arXiv Publisher Share
Cite This Paper
Copy URL
Compare
Copy DOI Add to Reading List
Category Correction Request
Category Correction Request
Help us improve classification quality by proposing a better category. Every request is reviewed by an admin.
Sign in to submit a category correction request for this paper.
Log In to SubmitReferences & Citation Signals
Community Reactions
Quick sentiment from readers on this paper.
Score:
0
Likes: 0
Dislikes: 0
Sign in to react to this paper.
Discussion & Reviews (Moderated)
Average Rating: 0.0 / 5 (0 ratings)
No written reviews yet.