
Negative interference reshapes our understanding of quantum speed limits, offering tighter performance bounds for single‑shot quantum technologies and enhancing precision metrology under realistic, noisy conditions.
Traditional quantum information metrics, such as the Fisher Information, average over many experimental runs, masking the stochastic fluctuations that dominate real‑world quantum devices. By importing concepts from stochastic thermodynamics, the Conditional Quantum Fisher Information (CQFI) provides a mathematically rigorous way to quantify information flow along each individual quantum trajectory. This trajectory‑centric perspective aligns with the growing need for single‑shot analysis in quantum computing, sensing, and communication, where each measurement outcome can carry distinct operational value.
The CQFI’s three‑part decomposition isolates population changes, coherent basis rotations, and a transient interference contribution that can become negative. This negative term signals a genuine quantum‑classical clash, reducing the effective information gain on certain paths and tightening the fundamental speed limits governing state evolution. Compared with ensemble‑averaged bounds, the single‑trajectory limits derived from stochastic length and action capture rare but highly informative events, delivering more realistic constraints for non‑unitary processes subject to decoherence and dissipation.
Beyond theoretical elegance, the framework opens practical avenues for quantum metrology and thermodynamics. By pinpointing when and how interference suppresses information, experimentalists can design protocols that avoid destructive paths or exploit criticality to boost precision. The validation on a driven thermal qubit demonstrates compatibility with existing quantum‑jump simulation tools, suggesting immediate applicability to noisy intermediate‑scale quantum (NISQ) platforms. As industries push toward fault‑tolerant quantum hardware, trajectory‑level insights like those offered by CQFI will become essential for optimizing performance, managing energy costs, and establishing reliable benchmarks.
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