Single-photon transport in a one dimentional waveguide coupling to a hybrid atom-optomechanical system

We explore theoretically the single-photon transport in a single-mode waveguide that is coupled to a hybrid atom-optomechanical system in a strong optomechanical coupling regime. Using a full quantum real-space approach, transmission and reflection coefficients of the propagating single-photon in the waveguide are ob- tained. The influences of atom-cavity detuning and the dissipation of atom on the transport are also studied. Intriguingly, the obtained spectral features can reveal the strong light-matter interaction in this hybrid system.Comment: 7pages, 8figure

Tunable one-dimensional microwave emissions from cyclic-transition three-level atoms

By strongly driving a cyclic-transition three-level artificial atom, demonstrated by such as a flux-based superconducting circuit, we show that coherent microwave signals can be excited along a coupled one-dimensional transmission line. Typically, the intensity of the generated microwave is tunable via properly adjusting the Rabi frequencies of the applied strong-driving fields or introducing a probe field with the same frequency. In practice, the system proposed here could work as an on-chip quantum device with controllable atom-photon interaction to implement a total-reflecting mirror or switch for the propagating probe field.Comment: 4 pages, 5 figure

Gain without inversion in quantum systems with broken parities

For a quantum system with broken parity symmetry, selection rules can not hold and cyclic transition structures are generated. With these loop-transitions we discuss how to achieve inversionless gain of the probe field by properly setting the control and auxiliary fields. Possible implementations of our generic proposal with specific physical objects with broken parities, e.g., superconducting circuits and chiral molecules, are also discussed.Comment: 12 pages, 4 figure

Vacuum induced Berry phases in single-mode Jaynes-Cummings models

Motivated by the work [Phys. Rev. Lett. 89, 220404 (2002)] for detecting the vacuum-induced Berry phases with two-mode Jaynes-Cummings models (JCMs), we show here that, for a parameter-dependent single-mode JCM, certain atom-field states also acquire the photon-number-dependent Berry phases after the parameter slowly changed and eventually returned to its initial value. This geometric effect related to the field quantization still exists, even the filed is kept in its vacuum state. Specifically, a feasible Ramsey interference experiment with cavity quantum electrodynamics (QED) system is designed to detect the vacuum-induced Berry phase.Comment: 10 pages, 4 figures

Atom-photon dressed states in a waveguide-QED system with multiple giant atoms coupled to a resonator-array waveguide

We study the properties of bound and scattering states in the single-excitation subspace in waveguide-QED systems consisting of multiple giant atoms coupled to a coupled-resonator waveguide. Based on the most general analytical expressions possible for these states and the corresponding energy spectra, we analyze in detail relevant phenomena due to the influence of a structured environment combined with the non-dipole effects of giant atoms. We analyze the threshold conditions for the appearance of bound states and the photon-mediated interactions between dressed atoms for different configurations. In addition, when multiple giant atoms are coupled to the waveguide, the bound states in the photonic band gaps can form different types of metaband structures, depending on coupling configurations. This makes the system a useful platform for quantum simulations. Finally the influence of the structured bath on the scattering spectra of multiple atoms also becomes remarkable in the strong coupling regime, leading to unconventional spectral structures.Comment: 24 pages, 12 figure

Research on UBI auto insurance pricing model based on parameter adaptive SAPSO optimal fuzzy controller

Aiming at the problem of “dynamic” accurate determination of rates in UBI auto insurance pricing, this paper proposes a UBI auto insurance pricing model based on fuzzy controller and optimizes it with a parameter adaptive SASPO. On the basis of the SASPO algorithm, the movement direction of the particles can be mutated and the direction can be dynamically controlled, the inertia weight value is given by the distance between the particle and the global optimal particle, and the learning factor is calculated according to the change of the fitness value, which realizes the parameter in the running process. Effective self-adjustment. A five-dimensional fuzzy controller is constructed by selecting the monthly driving mileage, the number of violations, and the driving time at night in the UBI auto insurance data. The weights are used to form fuzzy rules, and a variety of algorithms are used to optimize the membership function and fuzzy rules and compare them. The research results show that, compared with other algorithms, the parameter adaptive SAPAO algorithm can calculate more reasonable, accurate and high-quality fuzzy rules and membership functions when processing UBI auto insurance data. The accuracy and robustness of UBI auto insurance rate determination can realize dynamic and accurate determination of UBI auto insurance rates

Rapid RNA Exchange in Aqueous Two-Phase System and Coacervate Droplets

Compartmentalization in a prebiotic setting is an important aspect of early cell formation and is crucial for the development of an artificial protocell system that effectively couples genotype and phenotype. Aqueous two-phase systems (ATPSs) and complex coacervates are phase separation phenomena that lead to the selective partitioning of biomolecules and have recently been proposed as membrane-free protocell models. We show in this study through fluorescence recovery after photobleaching (FRAP) microscopy that despite the ability of such systems to effectively concentrate RNA, there is a high rate of RNA exchange between phases in dextran/polyethylene glycol ATPS and ATP/poly-L-lysine coacervate droplets. In contrast to fatty acid vesicles, these systems would not allow effective segregation and consequent evolution of RNA, thus rendering these systems ineffective as model protocells. Electronic supplementary material The online version of this article (doi:10.1007/s11084-014-9355-8) contains supplementary material, which is available to authorized users

Effect of finishing rolling reduction on microstructures and textures of grain oriented silicon steel

The effect of finishing rolling reduction on microstructures and textures of grain oriented silicon steel was researched by optical microscopy, zeiss ultra 55 Scanning Electron Microscope (SEM) and Electron Backscatter Diffraction (EBSD) technique severally. The results show that the grain size of hot rolled sheets and decarburized strips decreases, while the center grain size of the normalized sheet increases with the increase of the finishing rolling reduction. The pearlite content increases with the increase of the finishing rolling reduction after normalization. Compare with the previous research, the effect of finishing rolling reduction on the grain size of primary recrystallization is greater than that of roughing rolling reduction, and large rolling reduction is beneficial to the formation of {110} texture

Intelligent Tennis Robot Based on a Deep Neural Network

In this paper, an improved you only look once (YOLOv3) algorithm is proposed to make the detection effect better and improve the performance of a tennis ball detection robot. The depth-separable convolution network is combined with the original YOLOv3 and the residual block is added to extract the features of the object. The feature map output by the residual block is merged with the target detection layer through the shortcut layer to improve the network structure of YOLOv3. Both the original model and the improved model are trained by the same tennis ball data set. The results show that the recall is improved from 67.70% to 75.41% and the precision is 88.33%, which outperforms the original 77.18%. The recognition speed of the model is increased by half and the weight is reduced by half after training. All these features provide a great convenience for the application of the deep neural network in embedded devices. Our goal is that the robot is capable of picking up more tennis balls as soon as possible. Inspired by the maximum clique problem (MCP), the pointer network (Ptr-Net) and backtracking algorithm (BA) are utilized to make the robot find the place with the highest concentration of tennis balls. According to the training results, when the number of tennis balls is less than 45, the accuracy of determining the concentration of tennis balls can be as high as 80%.</jats:p