Quantum Metrology with Cold Atoms

Quantum metrology is the science that aims to achieve precision measurements by making use of quantum principles. Attribute to the well-developed techniques of manipulating and detecting cold atoms, cold atomic systems provide an excellent platform for implementing precision quantum metrology. In this chapter, we review the general procedures of quantum metrology and some experimental progresses in quantum metrology with cold atoms. Firstly, we give the general framework of quantum metrology and the calculation of quantum Fisher information, which is the core of quantum parameter estimation. Then, we introduce the quantum interferometry with single and multiparticle states. In particular, for some typical multiparticle states, we analyze their ultimate precision limits and show how quantum entanglement could enhance the measurement precision beyond the standard quantum limit. Further, we review some experimental progresses in quantum metrology with cold atomic systems.Comment: 53 pages, 9 figures, revised versio

5,8-Dibromo-14,15,17,18-tetra­methyl-2,11-dithia­[3.3]paracyclo­phane

In the title mol­ecule [systematic name: 12,15-dibromo-52,53,55,56-tetramethyl-3,7-dithia-1,5(1,4)-dibenzenacyclooctaphane], C20H22Br2S2, the distance between the centroids of the two benzene rings is 3.326 (4) Å, and their mean planes are almost parallel, forming a dihedral angle of 1.05 (7)°. The crystal packing exhibits no inter­molecular contacts shorter than the sum of van der Waals radii

A simplified model for modelling flexible end-plate connection in fire

In this paper a simplified robust 2-noded connection element has been developed for modelling the flexible end-plate connections at elevated temperatures. In this model, the two stage behaviours of flexible end-plate connection are considered. The model has the advantages of both the simple and component-based models. It is computationally efficient and has very good numerical stability under static solver conditions. A total of 14 tests are used to validate the model, demonstrating that this new connection model has the capability to accurately predict the behaviour of the flexible end-plate connections at elevated temperatures. The model can be used to simulate the flexible end-plate connections in real performance-based fire resistance design of steel-framed composite buildings

ANALYSIS OF COMPOSITE BUILDINGS UNDER FIRE CONDITIONS

In this paper, the performances of a generic three dimensional 45m x 45m composite floor subjected to ISO834 Fire and Natural Fire are investigated. The influences of reinforcing steel mesh and vertical support conditions on the tensile membrane action of floor slabs are investigated in details. Two robust 2-node connection element models developed by the authors are used to model the behaviour of end-plate and partial end-plate connections of composite structures under fire conditions. The impact of connections on the 3D behaviour of composite floor is considered. Based on the results obtained, some design recommendations are proposed to enhance the fire safety design of composite buildings

Kibble-Zurek dynamics in an array of coupled binary Bose condensates

Universal dynamics of spontaneous symmetry breaking is central to understanding the universal behavior of spontaneous defect formation in various system from the early universe, condensed-matter systems to ultracold atomic systems. We explore the universal real-time dynamics in an array of coupled binary atomic Bose-Einstein condensates in optical lattices, which undergo a spontaneous symmetry breaking from the symmetric Rabi oscillation to the broken-symmetry self-trapping. In addition to Goldstone modes, there exist gapped Higgs mode whose excitation gap vanishes at the critical point. In the slow passage through the critical point, we analytically find that the symmetry-breaking dynamics obeys the Kibble-Zurek mechanism. From the scalings of bifurcation delay and domain formation, we numerically extract two Kibble-Zurek exponents $b_{1}=\nu/(1+\nu z)$ and $b_{2}=1/(1+\nu z)$, which give the static correlation-length critical exponent $\nu$ and the dynamic critical exponent $z$. Our approach provides an efficient way to simultaneous determination of the critical exponents $\nu$ and $z$ for a continuous phase transition.Comment: 6 pages, 4 figures, accepted for publication in EPL (Europhysics Letters

A DISCUSSION OF THE RELATIONSHIP MODEL OF THE PURCHASE INTENTION OF BRANDS, AS BASED ON FOOD SAFETY ISSUES

In recent years, food safety issues have been occurring in Taiwan, making food safety increasingly concerned and valued. Some people think that they should not buy the brands that have had food safety problems, while others think they can continue to buy the brands that have had food safety problems because the brands have made adjustments. For brands that have had food safety issues, the complex and diverse consumer attitudes are worth discussing. This study examines the relationship model of the subjects regarding brand image, food safety certification trust, brand trust, brand loyalty, and purchase intention of brands with food safety problems. The research methods used in this study include literature review, expert interview, and questionnaire survey, and data analysis methods include exploratory factor analysis, confirmatory factor analysis, and regression analysis.  Finally, this study proposes the tested relationship model. The results of this study can provide a certain reference and theoretical basis for solving the food safety problems of brands

Decision-making and control with metasurface-based diffractive neural networks

The ultimate goal of artificial intelligence is to mimic the human brain to perform decision-making and control directly from high-dimensional sensory input. All-optical diffractive neural networks provide a promising solution for implementing artificial intelligence with high-speed and low-power consumption. To date, most of the reported diffractive neural networks focus on single or multiple tasks that do not involve interaction with the environment, such as object recognition and image classification. In contrast, the networks that can perform decision-making and control, to our knowledge, have not been developed yet. Here, we propose using deep reinforcement learning to implement diffractive neural networks that imitate human-level decision-making and control capability. Such networks allow for finding optimal control policies through interaction with the environment and can be readily realized with the dielectric metasurfaces. The superior performances of these networks are verified by engaging three types of classic games, Tic-Tac-Toe, Super Mario Bros., and Car Racing, and achieving the same or even higher levels comparable to human players. Our work represents a solid step of advancement in diffractive neural networks, which promises a fundamental shift from the target-driven control of a pre-designed state for simple recognition or classification tasks to the high-level sensory capability of artificial intelligence. It may find exciting applications in autonomous driving, intelligent robots, and intelligent manufacturing

A tunable plasmonic refractive index sensor with nanoring-strip graphene arrays

In this paper, a tunable plasmonic refractive index sensor with nanoring-strip graphene arrays is numerically investigated by the finite difference time domain (FDTD) method. The simulation results exhibit that by changing the sensing medium refractive index nmed of the structure, the sensing range of the system is large. By changing the doping level ng, we noticed that the transmission characteristics can be adjusted flexibly. The resonance wavelength remains entirely the same and the transmission dip enhancement over a big range of incidence angles [0,45] for both TM and TE polarizations, which indicates that the resonance of the graphene nanoring-strip arrays is insensitive to angle polarization. The above results are undoubtedly a new way to realize various tunable plasmon devices, and may have a great application prospect in biosensing, detection and imaging