Quick Navigation
Topics
Trapped Ion Quantum Computing
Superconducting Qubits
Enhanced Nonreciprocal Quantum Battery Performance via Nonlinear Two-Photon Driving
arXiv
Authors: Luxin Xu, Changliang Ren
Year
2025
Paper ID
17113
Status
Preprint
Abstract Read
~2 min
Abstract Words
140
Citations
N/A
Abstract
Quantum batteries have attracted significant attention as efficient quantum energy storage devices.In this work, we propose a nonlinear two-photon driving quantum battery model featuring nonreciprocal dynamics that enables a highly efficient unidirectional charging mechanism through environmental engineering. Using a Markovian master-equation approach, we derive analytical solutions for the system dynamics and identify the parameter regime required for dynamical equilibration. Our results reveal that increasing the driving strength enhances both energy conversion and storage efficiency, albeit at the cost of longer equilibration times. Compared with single-photon driving, the two-photon process exhibits a pronounced advantage in energy capacity and entropy regulation, which becomes more prominent under stronger driving. Under asymmetric dissipation, optimizing the system-bath coupling can further improve performance. The proposed model is experimentally feasible and can be implemented across multiple quantum platforms, including photonic systems, superconducting circuits, and magnonic devices.
Why This Paper Matters
- This paper contributes to the Superconducting Qubits research area in the Quantum Articles archive.
- It adds a 2025 reference point for readers tracking recent quantum research.
- Quantum batteries have attracted significant attention as efficient quantum energy storage devices.In this work, we propose a nonlinear two-photon driving quantum battery model...
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.