Generation and amplification of high-order sideband induced by two-level atoms in a hybrid optomechanical system

It is quite important to enhance and control the optomechanically induced high-order sideband generation to achieve low-power optical comb and high-sensitivity sensing with an integratable structure. Here we present and analyze a proposal for enhancement and manipulation of optical nonlinearity and high-order sideband generation in a hybrid atom-cavity optomechanical system that is coherently driven by a bichromatic input field consisting of a control field and a probe field and works beyond the perturbative regime. Our numerical analysis with experimentally achievable parameters confirms that robust high-order sideband generation and typical spectral structures with non-perturbative features can be created even under weak driven fields. The dependence of the high-order sideband generation on the atomic parameters are also discussed in detail, including the decay rate of the atoms and the coupling parameter between the atoms and the cavity field. We show that the cutoff order as well as the amplitude of the higher order sidebands can be well tuned by the atomic coupling strength and the atomic decay rate. The proposed mechanism of enhancing optical nonlinearity is quite general and can be adopted to optomechanical systems with different types of cavity

Vibration problem of a spherical tank containing jet propellant: numerical simulations

This document is the final report on the joint research project on vibration problem of a spherical tank containing jet propellant between IHI, Japan and SES, University of Southampton, UK. The background of the project is described. The fundamental principles and numerical method used in numerical simulations are presented. The detailed FEA models for each studied cases are given. The calculation results are presented using tables, curves, figures as well as the attached data files. The available experiment results are listed to compare with the numerical calculations. The calculation results show a fundamental agreement with the experiment results. The numerical analysis confirms that:1)Due to water – tank interaction, the natural frequencies of the water – tank system are decreased with the water level increase. For the 25% water level, the natural frequencies, especially heave mode frequency, shows a significant decrease compared with the empty case. However, with continuing increase the filed water more than 25% level, the decrease gradient of the natural frequencies gradually tends to zero. In the 100% water case, the natural frequency of heave mode is about 200 Hz which can not equal zero.2)Considering free surface wave effect produces a lot of sloshing modes of very low frequencies compared with the natural frequencies of the dry tank structure. Therefore, for dynamic response analysis with high frequency excitations, the free surface wave may be neglected. However, to assess loads caused by sloshing modes, the free surface waves have to be considered.3)There exist relative big deformations at the four tank support places in several vibration modes, which may produce a large local stress at support places to cause the product fail in vibration environment. A strengthen local design at the support places is needed.4)The dynamic response results are affected by damping coefficients of all modes used in the dynamic response analysis. The damping coefficients are approximately presented and therefore, the numerical results are good reference for practical designs.The report confirms that the original purpose of this joint research project has well completed by IHI and SES

Empirical properties of inter-cancellation durations in the Chinese stock market

Order cancellation process plays a crucial role in the dynamics of price formation in order-driven stock markets and is important in the construction and validation of computational finance models. Based on the order flow data of 18 liquid stocks traded on the Shenzhen Stock Exchange in 2003, we investigate the empirical statistical properties of inter-cancellation durations in units of events defined as the waiting times between two consecutive cancellations. The inter-cancellation durations for both buy and sell orders of all the stocks favor a $q$-exponential distribution when the maximum likelihood estimation method is adopted; In contrast, both cancelled buy orders of 6 stocks and cancelled sell orders of 3 stocks prefer Weibull distribution when the nonlinear least-square estimation is used. Applying detrended fluctuation analysis (DFA), centered detrending moving average (CDMA) and multifractal detrended fluctuation analysis (MF-DFA) methods, we unveil that the inter-cancellation duration time series process long memory and multifractal nature for both buy and sell cancellations of all the stocks. Our findings show that order cancellation processes exhibit long-range correlated bursty behaviors and are thus not Poissonian.Comment: 14 pages, 7 figures and 5 table

Joint multifractal analysis based on the partition function approach: Analytical analysis, numerical simulation and empirical application

Many complex systems generate multifractal time series which are long-range cross-correlated. Numerous methods have been proposed to characterize the multifractal nature of these long-range cross correlations. However, several important issues about these methods are not well understood and most methods consider only one moment order. We study the joint multifractal analysis based on partition function with two moment orders, which was initially invented to investigate fluid fields, and derive analytically several important properties. We apply the method numerically to binomial measures with multifractal cross correlations and bivariate fractional Brownian motions without multifractal cross correlations. For binomial multifractal measures, the explicit expressions of mass function, singularity strength and multifractal spectrum of the cross correlations are derived, which agree excellently with the numerical results. We also apply the method to stock market indexes and unveil intriguing multifractality in the cross correlations of index volatilities.Comment: 19 pages, 5 figure

Translating Phrases in Neural Machine Translation

Phrases play an important role in natural language understanding and machine translation (Sag et al., 2002; Villavicencio et al., 2005). However, it is difficult to integrate them into current neural machine translation (NMT) which reads and generates sentences word by word. In this work, we propose a method to translate phrases in NMT by integrating a phrase memory storing target phrases from a phrase-based statistical machine translation (SMT) system into the encoder-decoder architecture of NMT. At each decoding step, the phrase memory is first re-written by the SMT model, which dynamically generates relevant target phrases with contextual information provided by the NMT model. Then the proposed model reads the phrase memory to make probability estimations for all phrases in the phrase memory. If phrase generation is carried on, the NMT decoder selects an appropriate phrase from the memory to perform phrase translation and updates its decoding state by consuming the words in the selected phrase. Otherwise, the NMT decoder generates a word from the vocabulary as the general NMT decoder does. Experiment results on the Chinese to English translation show that the proposed model achieves significant improvements over the baseline on various test sets.Comment: Accepted by EMNLP 201