Nonadiabatic Geometric Quantum Computation Using A Single-loop Scenario

A single-loop scenario is proposed to realize nonadiabatic geometric quantum computation. Conventionally, a so-called multi-loop approach is used to remove the dynamical phase accumulated in the operation process for geometric quantum gates. More intriguingly, we here illustrate in detail how to use a special single-loop method to remove the dynamical phase and thus to construct a set of universal quantum gates based on the nonadiabatic geometric phase shift. The present scheme is applicable to NMR systems and may be feasible in other physical systems.Comment: 4 pages, 3 figure

A Survey on Multisensor Fusion and Consensus Filtering for Sensor Networks

Multisensor fusion and consensus filtering are two fascinating subjects in the research of sensor networks. In this survey, we will cover both classic results and recent advances developed in these two topics. First, we recall some important results in the development ofmultisensor fusion technology. Particularly, we pay great attention to the fusion with unknown correlations, which ubiquitously exist in most of distributed filtering problems. Next, we give a systematic review on several widely used consensus filtering approaches. Furthermore, some latest progress on multisensor fusion and consensus filtering is also presented. Finally, conclusions are drawn and several potential future research directions are outlined.the Royal Society of the UK, the National Natural Science Foundation of China under Grants 61329301, 61374039, 61304010, 11301118, and 61573246, the Hujiang Foundation of China under Grants C14002 and D15009, the Alexander von Humboldt Foundation of Germany, and the Innovation Fund Project for Graduate Student of Shanghai under Grant JWCXSL140

Optimal Currency Composition for China’s Foreign Reserves: a Copula Approach

This paper investigates the optimal currency composition for a country's foreign reserves. In the context of China, we examine the asymmetric, fat-tail and complex dependence structure in distributions of currency returns. A skewed, fat-tailed and pair-copula construction is then built to capture features of higher moments. In a D-vine copula approach, we show that under the disappointment aversion effect, the central bank in our model can achieve sizeable gains in expected economic value from switching from the mean-variance to copula modelling. We find that this approach will lead to an optimal currency composition that allows China to have more space for international currency diversification while maintaining the leading position of the US dollar in the currency shares of China's reserves

Accuracy of the point-source model of a multi-LED array in high-speed visible light communication channel characterization

During the procedure of indoor visible light communication (VLC) channel modeling, the transmitter constituted by an array of LEDs is frequently modeled as single point-source for convenience. But how accurate this simplified treatment is remains unanswered. This paper compares the channel characteristics of both the simplified point-source model and six practical cases having various numbers of LEDs. Our numerical results show that the deviations in terms of the channel’s optical path loss (OPL) as well as its bandwidth and the channel’s delay spread are increased steadily upon increasing the number of LEDs of each transmitter, until LEDs spread almost over the entire ceiling. Even in the worst case, the deviation of the OPL remains below 0.41 dBo, while that of the 3-dB transmission bandwidth is below 1.67 MHz. However, the deviation in terms of the root mean square (RMS) delay spread can reach 1.88 ns. Moreover, in terms of spatial distribution of the RMS delay spread, there is a non-negligible difference between the simplified point-source model and different transmitter configurations

Investor learning and mutual fund family

In this paper we revisit the cross-fund learning method suggested by Jones and Shanken (2005) and construct a linear hierarchical model to consider the learning across funds within the fund family during the performance evaluation. We provide a full Bayesian treatment on all the factors of the pricing model and allow both the fund family and the individual manager to have dependent prior information regarding funds' alphas. The simulation results suggest that returns from peer funds within the family significantly affect investors' updating on fund alphas since the posterior distribution on fund alphas experiences a faster shrinkage than those reported in the previous literature. The model can also be simulated with specific prior belief on different factors of the pricing model, i.e. fund alphas, betas and factor loadings of each pricing benchmark, to better address the learning issue