37,378 research outputs found
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
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
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
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.
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