Quick Navigation
Topics
Trapped Ion Quantum Computing
Superconducting Qubits
Quantum Thermodynamics
Collective quantum enhancement in critical quantum sensing
arXiv
Authors: Uesli Alushi, Alessandro Coppo, Valentina Brosco, Roberto Di Candia, Simone Felicetti
Year
2024
Paper ID
64982
Status
Preprint
Abstract Read
~2 min
Abstract Words
153
Citations
N/A
Abstract
Critical systems represent a valuable resource in quantum sensing and metrology. Critical quantum sensing (CQS) protocols can be realized using finite-component phase transitions, where criticality arises from the rescaling of system parameters rather than the thermodynamic limit. Here, we show that a collective quantum advantage can be achieved in a multipartite CQS protocol using a chain of parametrically coupled critical resonators in the weak-nonlinearity limit. We derive analytical solutions for the low-energy spectrum of this unconventional quantum many-body system, which is composed of locally critical elements. We then assess the scaling of the quantum Fisher information with respect to fundamental resources. We demonstrate that the coupled chain outperforms an equivalent ensemble of independent critical sensors, achieving quadratic scaling in the number of resonators. Finally, we show that even with finite Kerr nonlinearity or Markovian dissipation, the critical chain retains its advantage, making it relevant for implementing quantum sensors with current microwave superconducting technologies.
Why This Paper Matters
- This paper contributes to the Quantum Thermodynamics research area in the Quantum Articles archive.
- It adds a 2024 reference point for readers tracking recent quantum research.
- Critical systems represent a valuable resource in quantum sensing and metrology.
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.