quantum-computingQuantum Engines Face Higher Costs for Greater Measurement Precision 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 a thermal bath; this suggests fundamental connections between complex quantum engines and basic quantum systems. Using a genetic algorithm for multi-objective optimization, they identified Pareto fronts representing the best possible trade-offs between extractable work and its fluctuations. The results provide a compact description of the trade-offs between work, its fluctuations, and thermodynamic costs in quantum information engines. Pareto-Optimal Work Extraction in Quantum Engines Maximizing work output from a quantum engine invariably introduces fluctuations, but a new analysis reveals a precise trade-off between performance and reliability. Researchers have demonstrated that diminishing these fluctuations demands increased thermodynamic costs, a finding with implications for the design of increasingly practical quantum-scale devices. The work, appearing this month, moves beyond simply maximizing average energy extraction to consider the broader implications of consistent, dependable output. Using a genetic algorithm for multi-objective optimization, they identified Pareto fronts representing the best possible trade-offs between extractable work and its fluctuations. This approach, widely used in engineering and economics, is onl