Range-Angle-Dependent Beamforming by Frequency Diverse Array Antenna

This paper proposes a range-angle-dependent beamforming for frequency diverse array (FDA) antenna systems. Unlike conventional phased-array antenna, the FDA antenna employs a small amount of frequency increment compared to the carrier frequency across the array elements. The use of frequency increment generates an antenna pattern that is a function of range, time and angle. The range-angle-dependent beamforming allows the FDA antenna to transmit energy over a desired range or angle. This provides a potential to suppress range-dependent clutter and interference which is not accessible for conventional phased-array systems. In this paper, a FDA radar signal model is formed and the range-angle-dependent beamforming performance is examined by analyzing the transmit/receive beampatterns and the output signal-to-interference-plus-noise ratio (SINR) performance. Extensive simulation examples and results are provided

Macrophage migration inhibitory factor (MIF) family in arthropods : Cloning and expression analysis of two MIF and one D-dopachrome tautomerase (DDT) homologues in Mud crabs, Scylla paramamosain

Acknowledgements This research was supported by grants from the National Natural Science Foundation of China (Nos. 31172438 and U1205123), the Natural Science Foundation of Fujian Province (No. 2012J06008 and 201311180002) and the projects-sponsored by SRF. TW received funding from the MASTS pooling initiative (The Marine Alliance for Science and Technology for Scotland) funded by the Scottish Funding Council (grant reference HR09011) and contributing institutions.Peer reviewedPostprin

Optical absorption properties of Ge2–44 and P-doped Ge nanoparticles

The optical absorption properties of non-crystalline and crystalline Ge nanoparticles with the sizes from ∼2.5 to 15 Å have been studied at the B3LYP/6-31G level using time-dependent density functional theory. Hydrogen passivation and phosphorus doping on some selected Ge nanoparticles were also calculated. With the increase of cluster size, the optical absorption spectra of the non-crystalline Ge nanoparticles change from many peaks to a continuous broad band and at the same time exhibit a systematic red-shift. Doping phosphorus also causes the absorption spectra to shift toward the lower energy region for both non-crystalline and crystalline Ge nanoparticles. The non-crystalline Ge nanoparticles are found to have stronger absorption in the visible region in comparison with the crystalline ones, regardless phosphorus doping

Threshold quantum cryptograph based on Grover's algorithm

Grover's operator in the two-qubit case can transform a basis into its conjugated basis. A permutation operator can transform a state in the two conjugated bases into its orthogonal state. These properties are included in a threshold quantum protocol. The proposed threshold quantum protocol is secure based the proof that the legitimate participators can only eavesdrop 2 bits of 3 bits operation information on one two-qubit with error probability 3/8. We propose a scheme to detect the Trojan horse attack without destroying the legal qubit.Comment: 7 pages, 1 figure

Multilevel leapfrogging initialization for quantum approximate optimization algorithm

The quantum approximate optimization algorithm (QAOA) is a prospective hybrid quantum-classical algorithm widely used to solve combinatorial optimization problems. However, the external parameter optimization required in QAOA tends to consume extensive resources to find the optimal parameters of the parameterized quantum circuit, which may be the bottleneck of QAOA. To meet this challenge, we first propose multilevel leapfrogging learning (M-Leap) that can be extended to quantum reinforcement learning, quantum circuit design, and other domains. M-Leap incrementally increases the circuit depth during optimization and predicts the initial parameters at level $p+r$ ($r>1$) based on the optimized parameters at level $p$, cutting down the optimization rounds. Then, we propose a multilevel leapfrogging-interpolation strategy (MLI) for initializing optimizations by combining M-Leap with the interpolation technique. We benchmark its performance on the Maxcut problem. Compared with the Interpolation-based strategy (INTERP), MLI cuts down at least half the number of rounds of optimization for the classical outer learning loop. Remarkably, the simulation results demonstrate that the running time of MLI is 1/3 of INTERP when MLI gets quasi-optimal solutions. In addition, we present the greedy-MLI strategy by introducing multi-start, which is an extension of MLI. The simulation results show that greedy-MLI can get a higher average performance than the remaining two methods. With their efficiency to find the quasi-optima in a fraction of costs, our methods may shed light in other quantum algorithms

5,6-Dihydro-2H-1,3-dithiolo[4,5-b][1,4]dioxine-2-thione

The title mol­ecule, C5H4O2S3, consists of a planar [mean deviation = 0.020 (1) Å] 1,3-dithiole-2-thione unit with an ethyl­enedi­oxy group in the 4,5-positions. The dioxine ring is in a twist-chair conformation