A Robust Quantum Random Access Memory

A "bucket brigade" architecture for a quantum random memory of $N=2^n$ memory cells needs $n(n+5)/2$ times of quantum manipulation on control circuit nodes per memory call. Here we propose a scheme, in which only average $n/2$ times manipulation is required to accomplish a memory call. This scheme may significantly decrease the time spent on a memory call and the average overall error rate per memory call. A physical implementation scheme for storing an arbitrary state in a selected memory cell followed by reading it out is discussed.Comment: 5 pages, 3 figure

Optical and Gamma-Ray Variability Behaviors of 3C 454.3 from 2006 to 2011

We present our photometric monitoring of a flat spectrum radio quasar (FSRQ) 3C 454.3 at Yunnan observatories from 2006 to 2011. We find that the optical color of 3C 454.3 shows obvious redder-when-brighter trend, which reaches a saturation stage when the source is brighter than 15.15 mag at V band. We perform a simulation with multiple values of disk luminosity and spectral index to reproduce the magnitude-color diagram. The results show that the contamination caused by the disk radiation alone is difficult to produce the observed color variability. The variability properties during the outburst in December 2009 are also compared with $\gamma$-ray data derived from Fermi $\gamma$-ray space telescope. The flux variation of these two bands follow a linear relation with $F_{\gamma} \propto F_R^{1.14\pm0.07}$, which provides an observational evidence for external Compton process in 3C 454.3. Meanwhile, this flux correlation indicates that electron injection is the main mechanism for variability origin. We also explore the variation of the flux ratio $F_{\gamma}/F_R$ and the detailed structures in the lightcurves, and discuss some possible origins for the detailed variability behaviors.Comment: accepted for publication in The Astrophysical Journal, 5 figures, 2 table

The separability of tripartite Gaussian state with amplification and amplitude damping

Tripartite three mode Gaussian state undergoes parametric amplification and amplitude damping as well as thermal noise is studied. In the case of a state totally symmetrically interacting with the environment, the time dependent correlation matrix of the state in evolution is given. The conditions for fully separability and fully entanglement of the final tripartite three mode Gaussian state are worked out.Comment: 9 pages, 3 figure

Theory of control of optomechanical transducers for quantum networks

We present a scheme of control for the arbitrary optical interface mediated by a nanoscale mechanical oscillator between flying qubits and optical nonactive solid-state qubits. This quantum interface lays the foundation for many key functions of a quantum network, such as transferring, swapping, and entangling qubits between distant nodes of a quantum network. Numerical simulations of the quantum interface operations show high fidelities and robust tolerance under realistic experimental conditions. Compared with a previous scheme, it may significantly increase the speed of state transfer operation of high fidelity

Distributed evolutionary algorithms and their models: A survey of the state-of-the-art

The increasing complexity of real-world optimization problems raises new challenges to evolutionary computation. Responding to these challenges, distributed evolutionary computation has received considerable attention over the past decade. This article provides a comprehensive survey of the state-of-the-art distributed evolutionary algorithms and models, which have been classified into two groups according to their task division mechanism. Population-distributed models are presented with master-slave, island, cellular, hierarchical, and pool architectures, which parallelize an evolution task at population, individual, or operation levels. Dimension-distributed models include coevolution and multi-agent models, which focus on dimension reduction. Insights into the models, such as synchronization, homogeneity, communication, topology, speedup, advantages and disadvantages are also presented and discussed. The study of these models helps guide future development of different and/or improved algorithms. Also highlighted are recent hotspots in this area, including the cloud and MapReduce-based implementations, GPU and CUDA-based implementations, distributed evolutionary multiobjective optimization, and real-world applications. Further, a number of future research directions have been discussed, with a conclusion that the development of distributed evolutionary computation will continue to flourish