Suppressing measurement uncertainty in an inhomogeneous spin star system

The uncertainty principle is known as a foundational element of quantum theory, providing a striking lower bound to quantify our prediction for the measured result of two incompatible observables. In this work, we study the thermal evolution of the entropic uncertainty bound in the presence of quantum memory for an inhomogeneous four-qubit spin-star system that is in the thermal regime. Intriguingly, our results show that the entropic uncertainty bound can be controlled and suppressed by adjusting the inhomogeneity parameter of the system.

Testing the near-field Gaussian plume inversion flux quantification technique using unmanned aerial vehicle sampling

Methane emission fluxes from facility-scale sources may be poorly quantified, leading to uncertainties in the global methane budget. Accurate atmospheric measurement based flux quantification is urgently required to address this. This paper describes the test of a new near-field Gaussian plume inversion (NGI) technique, suitable for facility-scale flux quantification, using a controlled release of methane gas. Two unmanned aerial vehicle (UAV) platforms were used to perform 22 flight surveys downwind of a point-source release of methane gas from a regulated and flow-metered cylinder. One UAV was tethered to an instrument on the ground, while the other UAV carried an on-board high-precision prototype instrument, both of which used the same near-infrared laser technology. The performance of these instruments from UAV sampling is described. Both instruments were calibrated using certified standards, to account for variability in the instrumental gain factor. Furthermore, a modified approach to correcting for the effect of water vapour applied and is described here in detail. The NGI technique was used to derive emission fluxes for each UAV flight survey. We found good agreement of most NGI fluxes with the known controlled emission flux, within uncertainty, verifying the flux quantification methodology. The lower NGI flux uncertainty bound was, on average, 17 % ± 10(1σ) % of the controlled emission flux and the upper NGI flux uncertainty bound was, on average, 218 % ± 100(1σ) % of the controlled emission flux. These highly conservative uncertainty ranges incorporate factors including the variability in the position of the plume and the potential for under-sampling. While these average uncertainties are large compared to methods such as tracer dispersion, we suggest that UAV sampling can be highly complementary to a toolkit of flux approaches and may perform well in situations where site access for tracer release is problematic. We see tracer release applied to UAV sampling as an effective combination in future flux quantification studies. Successful flux quantification using this UAV sampling methodology demonstrates its future utility in identifying and quantifying emissions from methane sources such as oil and gas infrastructure facilities, livestock agriculture and landfill sites, where site access may be difficult.

Reducing uncertainties in flood inundation outputs of a two-dimensional hydrodynamic model by constraining roughness

The consideration of uncertainties in flood risk assessment has received increasing attention over the last 2 decades. However, the assessment is not reported in practice due to the lack of best practices and too wide uncertainty bounds. We present a method to constrain the model roughness based on measured water levels and reduce the uncertainty bounds of a two-dimensional hydrodynamic model. Results show that the maximum uncertainty in roughness generated an uncertainty bound in the water level of 1.26 m (90 % confidence interval) and by constraining roughness, the bounds can be reduced as much as 0.92 m.

Entropic Uncertainty Relations via Direct-Sum Majorization Relation for Generalized Measurements

We derive an entropic uncertainty relation for generalized positive-operator-valued measure (POVM) measurements via a direct-sum majorization relation using Schur concavity of entropic quantities in a finite-dimensional Hilbert space. Our approach provides a significant improvement of the uncertainty bound compared with previous majorization-based approaches (Friendland, S.; Gheorghiu, V.; Gour, G. Phys. Rev. Lett. 2013, 111, 230401; Rastegin, A.E.; Życzkowski, K. J. Phys. A, 2016, 49, 355301), particularly by extending the direct-sum majorization relation first introduced in (Rudnicki, Ł.; Puchała, Z.; Życzkowski, K. Phys. Rev. A 2014, 89, 052115). We illustrate the usefulness of our uncertainty relations by considering a pair of qubit observables in a two-dimensional system and randomly chosen unsharp observables in a three-dimensional system. We also demonstrate that our bound tends to be stronger than the generalized Maassen–Uffink bound with an increase in the unsharpness effect. Furthermore, we extend our approach to the case of multiple POVM measurements, thus making it possible to establish entropic uncertainty relations involving more than two observables.