Simultaneous energy and mass calibration of large-radius jets with the ATLAS detector using a deep neural network

The energy and mass measurements of jets are crucial tasks for the Large Hadron Collider experiments. This paper presents a new calibration method to simultaneously calibrate these quantities for large-radius jets measured with the ATLAS detector using a deep neural network (DNN). To address the specificities of the calibration problem, special loss functions and training procedures are employed, and a complex network architecture, which includes feature annotation and residual connection layers, is used. The DNN-based calibration is compared to the standard numerical approach in an extensive series of tests. The DNN approach is found to perform significantly better in almost all of the tests and over most of the relevant kinematic phase space. In particular, it consistently improves the energy and mass resolutions, with a 30% better energy resolution obtained for transverse momenta pT > 500 GeV

The Seepage Characteristics of Heterogeneous Body With Different Spreading Solution Modes and its Applications

As the dump was a typically heterogeneous body, the seepage was different with varied spreading solution modes. The phenomenon of lamination that occured in the site was simulated using three layers in an indoor experiment, and the seepage effect comparison experiment of the inside spreading solution model and the top spreading solution model have been carried out. In the inside spreading solution mode, the phreatic planar flew without infiltration and the parallel layer motion model was used to calculate the seepage coefficient and equivalent seepage coefficient of each state respectively. In the top spreading solution model, the phreatic planar flew with an even infiltration on the surface, and the vertical layer motion model was adopted to calculate the above coefficient. The results showed that the seepage coefficient of the inside model was larger than the top model in the heterogeneous body, The ratio of them was between 1.42 and 3.07. On the basis of these results, the following new technologies were discussed: installing a few small diameter mechanical pore sand piles with every lamination in the using dump; drilling some holes one-off in the unused dump. These two methods could changed the top spreading solution into the inside model, thus the seepage in the dump was improved

Study on grey forecasting model of copper extraction rate with bioleaching of primary sulfide ore

A model GM (grey model) (1, 1) for forecasting the rate of copper extraction during the bioleaching of primary sulphide ore was established on the basis of the mathematical theory and the modeling process of grey system theory. It was used for forecasting the rate of copper extraction from the primary sulfide ore during a laboratory microbial column leaching experiment. The precision of the forecasted results were examined and modified via “posterior variance examination”. The results show that the forecasted values coincide with the experimental values. GM (1, 1) model has high forecast accuracy; and it is suitable for simulation control and prediction analysis of the original data series of the processes that have grey characteristics, such as mining, metallurgical and mineral processing, etc. The leaching rate of such copper sulphide ore is low. The grey forecasting result indicates that the rate of copper extraction is approximately 20% even after leaching for six months

Doping of GaN{sub 1-x}As{sub x} with high As content

Recent work has shown that GaN{sub 1-x}As{sub x} can be grown across the entire composition range by low temperature molecular beam epitaxy with intermediate compositions being amorphous, but control of the electrical properties through doping is critical for functionalizing this material. Here we report the bipolar doping of GaN{sub 1-x}As{sub x} with high As content to conductivities above 4 S/cm at room temperature using Mg or Te. The carrier type was confirmed by thermopower measurements. Doping requires an increase in Ga flux during growth resulting in a mixed phase material of polycrystalline GaAs:N embedded in amorphous GaN{sub 1-x}As{sub x}