Teleportation of the one-qubit state in decoherence environments

We study standard quantum teleportation of one-qubit state for the situation in which the channel is subject to decoherence, and where the evolution of the channel state is ruled by a master equation in the Lindblad form. A detailed calculation reveals that the quality of teleportation is determined by both the entanglement and the purity of the channel state, and only the optimal matching of them ensures the highest fidelity of standard quantum teleportation. Also our results demonstrated that the decoherence induces distortion of the Bloch sphere for the output state with different rates in different directions, which implies that different input states will be teleported with different fidelities.Comment: 17 pages, 10 figure

All Maximal Independent Sets and Dynamic Dominance for Sparse Graphs

We describe algorithms, based on Avis and Fukuda's reverse search paradigm, for listing all maximal independent sets in a sparse graph in polynomial time and delay per output. For bounded degree graphs, our algorithms take constant time per set generated; for minor-closed graph families, the time is O(n) per set, and for more general sparse graph families we achieve subquadratic time per set. We also describe new data structures for maintaining a dynamic vertex set S in a sparse or minor-closed graph family, and querying the number of vertices not dominated by S; for minor-closed graph families the time per update is constant, while it is sublinear for any sparse graph family. We can also maintain a dynamic vertex set in an arbitrary m-edge graph and test the independence of the maintained set in time O(sqrt m) per update. We use the domination data structures as part of our enumeration algorithms.Comment: 10 page

Semantic Object Parsing with Graph LSTM

By taking the semantic object parsing task as an exemplar application scenario, we propose the Graph Long Short-Term Memory (Graph LSTM) network, which is the generalization of LSTM from sequential data or multi-dimensional data to general graph-structured data. Particularly, instead of evenly and fixedly dividing an image to pixels or patches in existing multi-dimensional LSTM structures (e.g., Row, Grid and Diagonal LSTMs), we take each arbitrary-shaped superpixel as a semantically consistent node, and adaptively construct an undirected graph for each image, where the spatial relations of the superpixels are naturally used as edges. Constructed on such an adaptive graph topology, the Graph LSTM is more naturally aligned with the visual patterns in the image (e.g., object boundaries or appearance similarities) and provides a more economical information propagation route. Furthermore, for each optimization step over Graph LSTM, we propose to use a confidence-driven scheme to update the hidden and memory states of nodes progressively till all nodes are updated. In addition, for each node, the forgets gates are adaptively learned to capture different degrees of semantic correlation with neighboring nodes. Comprehensive evaluations on four diverse semantic object parsing datasets well demonstrate the significant superiority of our Graph LSTM over other state-of-the-art solutions.Comment: 18 page

Rate-Distortion Optimized Vector SPIHT for Wavelet Image Coding

In this paper, a novel image coding scheme using rate-distortion optimized vector quantization of wavelet coefficients is presented. A vector set partitioning algorithm is used to locate significant wavelet vectors which are classified into a number of classes based on their energies, thus reducing the complexity of the vector quantization. The set partitioning bits are reused to indicate the vector classification indices to save the bits for coding of the classification overhead. A set of codebooks with different sizes is designed for each class of vectors, and a Lagrangian optimization algorithm is employed to select an optimal codebook for each vector. The proposed coding scheme is capable of trading off between the number of bits used to code each vector and the corresponding distortion. Experimental results show that our proposed method outperforms other zerotree-structured embedded wavelet coding schemes such as SPIHT and SFQ, and is competitive with JPEG2000

New Measurements of the EMC Effect in Few-Body Nuclei

Measurements of the EMC effect show that the quark distributions in nuclei are not simply the sum of the quark distributions of the constituent nucleons. However, interpretation of the EMC effect is limited by the lack of a reliable baseline calculation of the effects of Fermi motion and nucleon binding. We present preliminary results from JLab experiment E03-103, a precise measurement of the EMC effect in few-body and heavy nuclei. These data emphasize the large-x region, where binding and Fermi motion effects dominate, and thus will provide much better constraints on the effects of binding. These data will also allow for comparisons to calculations for few-body nuclei, where the uncertainty in the nuclear structure is minimized.Comment: Proceedings from talk at the Topical Group on Hadron Physics meeting, Nashville Tennessee, October 22-24, 2006. 9 pages, 6 figure

Searching for Dark Matter Signals in the Left-Right Symmetric Gauge Model with CP Symmetry

We investigate singlet scalar dark matter (DM) candidate in a left-right symmetric gauge model with two Higgs bidoublets (2HBDM) in which the stabilization of the DM particle is induced by the discrete symmetries P and CP. According to the observed DM abundance, we predict the DM direct and indirect detection cross sections for the DM mass range from 10 GeV to 500 GeV. We show that the DM indirect detection cross section is not sensitive to the light Higgs mixing and Yukawa couplings except the resonance regions. The predicted spin-independent DM-nucleon elastic scattering cross section is found to be significantly dependent on the above two factors. Our results show that the future DM direct search experiments can cover the most parts of the allowed parameter space. The PAMELA antiproton data can only exclude two very narrow regions in the 2HBDM. It is very difficult to detect the DM direct or indirect signals in the resonance regions due to the Breit-Wigner resonance effect.Comment: 24 pages, 8 figures. minor changes and a reference added, published in Phys. Rev.