PL_En.rar

Topology checking and optimization of pipeline data in browser-side using quadtree</p

Precipitation during the simulation period.

<p>Precipitation during the simulation period.</p

Root mean square error and the KGE value of the simulated soil moisture at different depths.

Root mean square error and the KGE value of the simulated soil moisture at different depths.</p

Root mean square error and the KGE value of the simulated net radiation, sensible, latent heat flux and soil temperature.

<p>Root mean square error and the KGE value of the simulated net radiation, sensible, latent heat flux and soil temperature.</p

All-optical pulse switching with a periodically driven dissipative quantum system

All-optical switching used to switch the input optical signals without any electro-optical conversion plays a vital role in the next generation of optical information processing devices. Even all-optical switchings (AOSs) with continuous input signals have been widely studied, all-optical pulse switchings (AOPSs) whose input signals are pulse sequences have rarely been investigated because of the time-dependent Hamiltonian, especially for dissipative quantum systems. In this paper, we propose an AOPS scheme, where a strong pulsed field is used to switch another pulsed input signal. With the help of Floquet-Lindblad theory, we identify the control field that can effectively turn on/off the input signal whose amplitude envelope is a square-wave (SW) pulse train in a three-level dissipative system. By comparing the properties of the AOPSs controlled by a continuous-wave (CW) field and an SW control field, we find that the SW field is more suitable to be a practical tool for controlling the input SW signal. It is interesting to impress that the switching efficacy is robust against pulse errors. The proposed protocol is readily implemented in atomic gases or superconducting circuits and corresponds to AOPSs or all-microwave pulse switchings

Comparison of the soil moistures calculated by different sets of simulation tests with the observational values.

<p>(a) 5cm (b) 10cm (c)20cm (d)40cm (e)80cm.</p

Scatter plots of the net radiation, sensible and latent heat fluxes, and soil temperature relative to the corresponding observational data in different sets of simulation tests.

<p>(a1-a4) Radiation (b1-b4) Sensible heat flux (c1-c4) Latent heat flux (d1-d4) Soil temperature at 5cm depth.</p

SHAW-PSO method flow chart.

<p>SHAW-PSO method flow chart.</p

Parameters optimized based upon different datasets.

<p>Parameters optimized based upon different datasets.</p

Input parameters for the SHAW-PSO model.

<p>Input parameters for the SHAW-PSO model.</p