Fully open-flavor tetraquark states bcqˉsˉbc\bar{q}\bar{s} and scqˉbˉsc\bar{q}\bar{b} with JP=0+,1+J^{P}=0^{+},1^{+}

We have studied the masses for fully open-flavor tetraquark states $bc\bar{q}\bar{s}$ and $sc\bar{q}\bar{b}$ with quantum numbers $J^{P}=0^{+},1^{+}$. We systematically construct all diquark-antiquark interpolating currents and calculate the two-point correlation functions and spectral densities in the framework of QCD sum rule method. Our calculations show that the masses are about $7.1-7.2$ GeV for the $bc\bar{q}\bar{s}$ tetraquark states and $7.0-7.1$ GeV for the $sc\bar{q}\bar{b}$ tetraquarks. The masses of $bc\bar{q}\bar{s}$ tetraquarks are below the thresholds of $\bar{B}_{s}D$ and $\bar{B}_{s}^{*}D$ final states for the scalar and axial-vector channels respectively. The $sc\bar{q}\bar{b}$ tetraquark states with $J^{P}=1^{+}$ lie below the $B_{c}^{+}K^{*}$ and $B_{s}^{*}D$ thresholds. Such low masses for these possible tetraquark states indicate that they can only decay via weak interaction and thus are very narrow and stable.Comment: 17 pages, 4 figure

Design and Implementation of a FPGA and DSP Based MIMO Radar Imaging System

The work presented in this paper is aimed at the implementation of a real-time multiple-input multiple-output (MIMO) imaging radar used for area surveillance. In this radar, the equivalent virtual array method and time-division technique are applied to make 16 virtual elements synthesized from the MIMO antenna array. The chirp signal generater is based on a combination of direct digital synthesizer (DDS) and phase locked loop (PLL). A signal conditioning circuit is used to deal with the coupling effect within the array. The signal processing platform is based on an efficient field programmable gates array (FPGA) and digital signal processor (DSP) pipeline where a robust beamforming imaging algorithm is running on. The radar system was evaluated through a real field experiment. Imaging capability and real-time performance shown in the results demonstrate the practical feasibility of the implementation

A Fast Algorithm for Approximate Quantiles in High Speed Data Streams

We present a fast algorithm for computing approx-imate quantiles in high speed data streams with deter-ministic error bounds. For data streams of size N where N is unknown in advance, our algorithm par-titions the stream into sub-streams of exponentially increasing size as they arrive. For each sub-stream which has a xed size, we compute and maintain a multi-level summary structure using a novel algorithm. In order to achieve high speed performance, the algo-rithm uses simple block-wise merge and sample oper-ations. Overall, our algorithms for xed-size streams and arbitrary-size streams have a computational cost of O(N log ( 1 log N)) and an average per-element update cost of O(log log N) if is xed.