---
OA_place: publisher
OA_type: gold
PlanS_conform: '1'
_id: '20733'
abstract:
- lang: eng
text: 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.
acknowledgement: We thank Georgios Katsaros for providing the device for this experiment.
K.A. and N.A. acknowledge the support provided by funding from the Engineering and
Physical Sciences Research Council IAA (Grant No. EP/X525777/1). N.A. acknowledges
support from the European Research Council (Grant Agreement No. 948932) and the
Royal Society (URF-R1-191150). A.R. is supported by the Swiss National Science Foundation
through a Postdoc. Mobility (Grant No. P500PT 225461). M.T.M. is supported by a
Royal Society University Research Fellowship. M.P.-L. is supported by the Grant
RYC2022-036958-I funded by the Spanish MICIU/AEI/10.13039/501100011033 and by ESF+.
This project is cofunded by the European Union and UK Research & Innovation (Quantum
Flagship project ASPECTS, Grant Agreement No. 101080167). However, views and opinions
expressed are those of the authors only and do not necessarily reflect those of
the European Union, Research Executive Agency, or UK Research & Innovation. Neither
the European Union nor UK Research & Innovation can be held responsible for them.
article_number: L032017
article_processing_charge: Yes
article_type: letter_note
arxiv: 1
author:
- first_name: Kushagra
full_name: Aggarwal, Kushagra
last_name: Aggarwal
- first_name: Alberto
full_name: Rolandi, Alberto
last_name: Rolandi
- first_name: Yikai
full_name: Yang, Yikai
last_name: Yang
- first_name: Joseph
full_name: Hickie, Joseph
last_name: Hickie
- first_name: Daniel
full_name: Jirovec, Daniel
id: 4C473F58-F248-11E8-B48F-1D18A9856A87
last_name: Jirovec
orcid: 0000-0002-7197-4801
- first_name: Andrea
full_name: Ballabio, Andrea
last_name: Ballabio
- first_name: Daniel
full_name: Chrastina, Daniel
last_name: Chrastina
- first_name: Giovanni
full_name: Isella, Giovanni
last_name: Isella
- first_name: Mark T.
full_name: Mitchison, Mark T.
last_name: Mitchison
- first_name: Martí
full_name: Perarnau-Llobet, Martí
last_name: Perarnau-Llobet
- first_name: Natalia
full_name: Ares, Natalia
last_name: Ares
citation:
ama: Aggarwal K, Rolandi A, Yang Y, et al. Rapid optimal work extraction from a
quantum-dot information engine. Physical Review Research. 2025;7(3). doi:10.1103/q3dx-kyqj
apa: Aggarwal, K., Rolandi, A., Yang, Y., Hickie, J., Jirovec, D., Ballabio, A.,
… Ares, N. (2025). Rapid optimal work extraction from a quantum-dot information
engine. Physical Review Research. American Physical Society. https://doi.org/10.1103/q3dx-kyqj
chicago: Aggarwal, Kushagra, Alberto Rolandi, Yikai Yang, Joseph Hickie, Daniel
Jirovec, Andrea Ballabio, Daniel Chrastina, et al. “Rapid Optimal Work Extraction
from a Quantum-Dot Information Engine.” Physical Review Research. American
Physical Society, 2025. https://doi.org/10.1103/q3dx-kyqj.
ieee: K. Aggarwal et al., “Rapid optimal work extraction from a quantum-dot
information engine,” Physical Review Research, vol. 7, no. 3. American
Physical Society, 2025.
ista: Aggarwal K, Rolandi A, Yang Y, Hickie J, Jirovec D, Ballabio A, Chrastina
D, Isella G, Mitchison MT, Perarnau-Llobet M, Ares N. 2025. Rapid optimal work
extraction from a quantum-dot information engine. Physical Review Research. 7(3),
L032017.
mla: Aggarwal, Kushagra, et al. “Rapid Optimal Work Extraction from a Quantum-Dot
Information Engine.” Physical Review Research, vol. 7, no. 3, L032017,
American Physical Society, 2025, doi:10.1103/q3dx-kyqj.
short: K. Aggarwal, A. Rolandi, Y. Yang, J. Hickie, D. Jirovec, A. Ballabio, D.
Chrastina, G. Isella, M.T. Mitchison, M. Perarnau-Llobet, N. Ares, Physical Review
Research 7 (2025).
date_created: 2025-12-07T23:02:02Z
date_published: 2025-07-01T00:00:00Z
date_updated: 2025-12-09T14:07:49Z
day: '01'
ddc:
- '530'
department:
- _id: GeKa
doi: 10.1103/q3dx-kyqj
external_id:
arxiv:
- '2412.06916'
file:
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intvolume: ' 7'
issue: '3'
language:
- iso: eng
month: '07'
oa: 1
oa_version: Published Version
publication: Physical Review Research
publication_identifier:
eissn:
- 2643-1564
publication_status: published
publisher: American Physical Society
quality_controlled: '1'
related_material:
link:
- relation: software
url: https://doi.org/10.5281/zenodo.14516009
scopus_import: '1'
status: public
title: Rapid optimal work extraction from a quantum-dot information engine
tmp:
image: /images/cc_by.png
legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
short: CC BY (4.0)
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
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...