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Journal article : Letter

Rapid optimal work extraction from a quantum-dot information engine

Abstract:
The conversion of thermal energy into work is usually more efficient in the slow-driving regime, where the power output is vanishingly small. Efficient work extraction for fast-driving protocols remains an outstanding challenge at the nanoscale, where fluctuations play a significant role. In this Letter, we use a quantum-dot Szilard engine to extract work from thermal fluctuations with maximum efficiency over two decades of driving speed. We design and implement a family of optimized protocols ranging from the slow- to the fast-driving regime, and we measure the engine's efficiency as well as the mean and variance of its power output in each case. These optimized protocols exhibit significant improvements in power and efficiency compared to the naive approach. Our results also show that, when optimizing for efficiency, boosting the power output of a Szilard engine inevitably comes at the cost of increased power fluctuations.
Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1103/q3dx-kyqj

Authors

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Institution:
University of Oxford
Division:
MPLS
Department:
Engineering Science
Role:
Author
More by this author
Institution:
University of Oxford
Division:
MPLS
Department:
Engineering Science
Role:
Author
More by this author
Institution:
University of Oxford
Division:
MPLS
Department:
Materials
Role:
Author


More from this funder
Funder identifier:
https://ror.org/001aqnf71
Grant:
101080167
Programme:
Quantum Flagship project ASPECTS
More from this funder
Funder identifier:
https://ror.org/03wnrjx87
Grant:
URF-R1-191150
More from this funder
Funder identifier:
https://ror.org/0472cxd90
Grant:
948932
More from this funder
Funder identifier:
https://ror.org/00yjd3n13
Grant:
P500PT 225461
More from this funder
Funder identifier:
https://ror.org/003x0zc53
Grant:
RYC2022-036958-I


Publisher:
American Physical Society
Journal:
Physical Review Research More from this journal
Volume:
7
Issue:
3
Article number:
l032017
Publication date:
2025-07-15
Acceptance date:
2025-06-16
DOI:
EISSN:
2643-1564


Language:
English
Subtype:
Letter
Pubs id:
2253610
Local pid:
pubs:2253610
Deposit date:
2025-08-01
ARK identifier:

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