Quick charging of a quantum battery with superposed trajecotries
Po-Rong Lai, Jhen-Dong Lin, Yi-Te Huang, Yueh-Nan Chen

TL;DR
This paper introduces quantum superposition-based charging protocols for quantum batteries, demonstrating that interference effects can significantly accelerate charging and increase extractable work, validated through experiments on IBMQ and IonQ.
Contribution
The paper presents novel quantum superposition protocols for charging batteries, showing enhanced ergotropy and faster charging via quantum interference effects, with experimental validation.
Findings
Superposition protocols increase ergotropy with more trajectories.
Two superposed trajectories suffice for maximum ergotropy.
Experimental results confirm theoretical predictions of enhanced charging.
Abstract
We propose novel charging protocols for quantum batteries based on quantum superpositions of trajectories. Specifically, we consider that a qubit (the battery) interacts with multiple cavities or a single cavity at various positions, where the cavities act as chargers. Further, we introduce a quantum control prepared in a quantum superposition state, allowing the battery to be simultaneously charged by multiple cavities or a single cavity with different entry positions. To assess the battery's performance, we evaluate the maximum extractable work, referred to as ergotropy. Our main result is that the proposed protocols can utilize quantum interference effects to speed up the charging process. For the protocol involving multiple cavities, we observe a substantial increase in ergotropy as the number of superposed trajectories increases. In the case of the single-cavity protocol, we show…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsAdvanced Thermodynamics and Statistical Mechanics · Advanced Memory and Neural Computing · Neural dynamics and brain function
