Uncertainty Relation between Detection Probability and Energy Fluctuations

A classical random walker starting on a node of a finite graph will always reach any other node since the search is ergodic, namely it fully explores space, hence the arrival probability is unity. For quantum walks, destructive interference may induce effectively non-ergodic features in such search processes. Under repeated projective local measurements, made on a target state, the final detection of the system is not guaranteed since the Hilbert space is split into a bright subspace and an orthogonal dark one. Using this we find an uncertainty relation for the deviations of the detection probability from its classical counterpart, in terms of the energy fluctuations.

Effect of the ambient solar wind speed on drag-based CME prediction accuracy

<p>In the last years, many kinds of CME models, based on a drag-based evolution through interplanetary space, have been developed and are now widely used by the community. The unbeatable advantage of those methods is that they are computationally cheap and are therefore suitable to be used as ensemble models. Additionally, their prediction accuracy is absolutely comparable to more sophisticated models.</p><p>The ELlipse Evolution model based on heliospheric imager (HI) observations (ELEvoHI) assumes an elliptic frontal shape within the ecliptic plane and allows the CME to adjust to the ambient solar wind speed, i.e. it is drag-based. ELEvoHI is used as an ensemble simulation by varying the CME frontal shape within given boundary values. The results include a frequency distribution of predicted arrival time and arrival speed and an estimation of the arrival probability.</p><p>In this study, we investigate the possibility of not only varying the parameters related to the CME's ecliptic extent but also the ambient solar wind speed for each CME ensemle member. Although we have used a range of +/-100 km/s for possible values of the solar wind speed in the past, only the best candidate was in the end used to contribute to the prediction. We present the results of this approach by applying it to a CME propagating in a highly structured solar wind and compare the frequency distribution of the arrival time and speed predictions to those of the usual ELEvoHI approach.</p>

Recent advances on urban taxi sharing systems with the path arrival probability

Background : Taxi sharing is an emerging transportation arrangement that helps improve the passengers’ travel efficiency and reduce costs. This study proposes an urban taxi sharing system. Methods: Considering each side congestion of the transport network, their corresponding reliability and failure probability are analyzed. Under the constraints of the number of passengers and their own time windows, the analysis is performed on passengers whose optimal path is inclusive. Results: According to the optimal strategy, the different passengers can be arranged into the same taxi to realize the taxi sharing. Then the shared taxi route can be optimized. Conclusion: Due to the reasonable vehicle route planning and passenger combination, these can effectively alleviate the traffic congestion, save the driving time, reduce the taxi no-load rate, and save the driving distance. At last, a numerical example is used to demonstrate the proposed method.