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This study establishes a fundamental thermodynamic limit for quantum engines, demonstrating that minimizing output fluctuations necessitates higher information consumption and operational costs rather than simply improving efficiency. By mapping these trade-offs via Pareto fronts using genetic algorithms, researchers provide a critical framework for designing reliable quantum devices where precision comes at the expense of average work extraction. These findings are essential for understanding the physical constraints inherent in scaling up practical quantum thermodynamic systems.

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Quantum Engines Face Higher Costs for Greater Measurement Precision

Quantum ZeitgeistAugust 14, 20265 min read

This research explores the thermodynamic cost of increased measurement precision in quantum engines.

Jonas Berx of Niels Bohr International Academy, Niels Bohr Institute, University of Copenhagen, and colleagues at Chalmers University of Technology have demonstrated a quantum engine where the work it produces is directly linked to the precision of its measurements. The research details how extracting work conditionally, based on measurement outcomes of a two-level system, presents a trade-off between extractable work and its fluctuations. Reducing fluctuations in work output, the team found, requires greater information consumption, more engine cycles, longer operation time, and ultimately, reduced average work output. In the limit of highly accurate measurement, the engine’s work statistics reduce to those of a qubit interacting with…

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