article published yes Kushagra Aggarwal author Alberto Rolandi author Yikai Yang author Joseph Hickie author Daniel Jirovec author 4C473F58-F248-11E8-B48F-1D18A9856A870000-0002-7197-4801 Andrea Ballabio author Daniel Chrastina author Giovanni Isella author Mark T. Mitchison author Martí Perarnau-Llobet author Natalia Ares author GeKa department 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. https://research-explorer.ista.ac.at/download/20733/20753/2025_PhysReviewResearch_Aggarwal.pdf application/pdfno American Physical Society2025 eng 2643-1564 2412.0691610.1103/q3dx-kyqj 73 https://doi.org/10.5281/zenodo.14516009 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). Aggarwal K, Rolandi A, Yang Y, et al. Rapid optimal work extraction from a quantum-dot information engine. <i>Physical Review Research</i>. 2025;7(3). doi:<a href="https://doi.org/10.1103/q3dx-kyqj">10.1103/q3dx-kyqj</a> 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.” <i>Physical Review Research</i>. American Physical Society, 2025. <a href="https://doi.org/10.1103/q3dx-kyqj">https://doi.org/10.1103/q3dx-kyqj</a>. Aggarwal, Kushagra, et al. “Rapid Optimal Work Extraction from a Quantum-Dot Information Engine.” <i>Physical Review Research</i>, vol. 7, no. 3, L032017, American Physical Society, 2025, doi:<a href="https://doi.org/10.1103/q3dx-kyqj">10.1103/q3dx-kyqj</a>. 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. K. Aggarwal <i>et al.</i>, “Rapid optimal work extraction from a quantum-dot information engine,” <i>Physical Review Research</i>, vol. 7, no. 3. American Physical Society, 2025. 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. <i>Physical Review Research</i>. American Physical Society. <a href="https://doi.org/10.1103/q3dx-kyqj">https://doi.org/10.1103/q3dx-kyqj</a> 207332025-12-07T23:02:02Z2025-12-09T14:07:49Z