6 research outputs found

    The twist-3 gluon contribution to Sivers asymmetry in J/ψJ/\psi production in semi-inclusive deep inelastic scattering

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    We carry out the first calculation for the twist-3 gluon contribution to the single transverse-spin asymmetry(SSA) in J/ψJ/\psi production in semi-inclusive deep inelastic scattering. Our result shows that the J/ψJ/\psi SSA is an ideal observable to pin down the CC-even type twist-3 gluon distribution that has a direct relationship with the gluon transverse-momentum-dependent distribution function. We also perform some numerical simulations of the J/ψJ/\psi SSA for the kinematics accessible at the future electron-ion-collider experiment. For color-singlet contribution, the hadronization effect of J/ψJ/\psi is completely canceled at the level of the SSA and the spin-dependent structure functions directly reflect the behavior of the CC-even twist-3 gluon distribution.Comment: 19 pages, 5 figure

    The Effects of Different Anode Positions on the Electrical Properties of Square-Silicon Drift Detector

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    The Silicon Drift Detector (SDD) with square structure is often used in pixel-type SDD arrays to reduce the dead region considerably and to improve the detector performance significantly. Usually, the anode is located in the center of the active region of the SDD with square structure (square-SDD), but the different anode positions in the square-SDD active area are also allowed. In order to explore the effect on device performance when the anode is located at different positions in the square-SDD active region, we designed two different types of square-SDD in this work, where the anode is located either in the center (SDD-1) or at the edge (SDD-2) of its active region. The simulation results of current density and potential distribution show that SDD-1 and SDD-2 have both formed a good electron drift path to make the anode collect electrons. The experimental results of device performance at the temperature range from −60 °C to 60 °C show that the anode current of the two fabricated SDDs both decreased with the decrease of temperature, but their voltage divider characteristics exhibited high stability resistance value and low temperature coefficient, thereby indicating that they could both provide corresponding continuous and uniform electric field at different temperatures. Finally, SDD-1 and SDD-2 have energy resolutions of 248 and 257 eV corresponding to the 5.9 keV photon peak of the Fe-55 radioactive source, respectively. Our experimental results demonstrate that there is no significant impact on the device performance irrespective of the anode positions in the square-SDD devices

    Neighbor Similarity Based Agglomerative Method for Community Detection in Networks

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    Community structures can reveal organizations and functional properties of complex networks; hence, detecting communities from networks is of great importance. With the surge of large networks in recent years, the efficiency of community detection is demanded critically. Therefore, many local methods have emerged. In this paper, we propose a node similarity based community detection method, which is also a local one consisted of two phases. In the first phase, we first take out the node with the largest degree from the network to take it as an exemplar of the first community and insert its most similar neighbor node into the community as well. Then, the one with the largest degree in the remainder nodes is selected; if its most similar neighbor has not been classified into any community yet, we create a new community for the selected node and its most similar neighbor. Otherwise, if its most similar neighbor has been classified into a certain community, we insert the selected node into the community to which its most similar neighbor belongs. This procedure is repeated until every node in the network is assigned to a community; at that time, we obtain a series of preliminary communities. However, some of them might be too small or too sparse; edges connecting to outside of them might go beyond the ones inside them. Keeping them as the final ones will lead to a low-quality community structure. Therefore, we merge some of them in an efficient approach in the second phase to improve the quality of the resulting community structure. To testify the performance of our proposed method, extensive experiments are performed on both some artificial networks and some real-world networks. The results show that the proposed method can detect high-quality community structures from networks steadily and efficiently and outperform the comparison algorithms significantly

    Simulation of Silicon Surface Barrier Detector with PN Junction Guard Rings to Improve the Breakdown Voltage

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    Silicon surface barrier detectors (SSBDs) are normally used to detect high-energy particles due to their excellent properties. For better charge collection efficiency (CCE), the SSBD device should be operated at higher reverse voltages, but this can lead to device breakdown. Therefore, we used a PN junction as a guard ring to increase the breakdown voltage of the SSBD. The structures of two SSBD devices are drawn and simulated in this work. Compared with a conventional SSBD (c-SSBD), the use of a PN junction as a guard ring for an SSBD (Hybrid-SSBD) achieves higher breakdown voltages, of over 1500 V under reverse bias. This means that Hybrid-SSBD devices can operate at higher reverse voltages for better charge collection efficiency (CCE) to detect high-energy particles. Then, we simulated the different structure parameters of the Hybrid-SSBD guard rings. Among them, the doping depth and gap width of the guard ring (between the innermost guard ring and the active area) have a greater impact on the breakdown voltage. Finally, for Hybrid-SSBD devices, the optimal characteristics of the guard ring were 1 × 1019 cm−3 doping concentration, 1 μm doping depth, and innermost guard ring width and gap width of 5 μm and 3 μm, respectively
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