Entanglement in the anisotropic Heisenberg XYZ model with different Dzyaloshinskii-Moriya interaction and inhomogeneous magnetic field

We investigate the entanglement in a two-qubit Heisenberg XYZ system with different Dzyaloshinskii-Moriya(DM) interaction and inhomogeneous magnetic field. It is found that the control parameters ($D_{x}$, $B_{x}$ and $b_{x}$) are remarkably different with the common control parameters ($D_{z}$,$B_{z}$ and $b_{z}$) in the entanglement and the critical temperature, and these x-component parameters can increase the entanglement and the critical temperature more efficiently. Furthermore, we show the properties of these x-component parameters for the control of entanglement. In the ground state, increasing $D_{x}$ (spin-orbit coupling parameter) can decrease the critical value $b_{xc}$ and increase the entanglement in the revival region, and adjusting some parameters (increasing $b_{x}$ and $J$, decreasing $B_{x}$ and $\Delta$) can decrease the critical value $D_{xc}$ to enlarge the revival region. In the thermal state, increasing $D_{x}$ can increase the revival region and the entanglement in the revival region (for $T$ or $b_{x}$), and enhance the critical value $B_{xc}$ to make the region of high entanglement larger. Also, the entanglement and the revival region will increase with the decrease of $B_{x}$ (uniform magnetic field). In addition, small $b_{x}$ (nonuniform magnetic field) has some similar properties to $D_{x}$, and with the increase of $b_{x}$ the entanglement also has a revival phenomenon, so that the entanglement can exist at higher temperature for larger $b_{x}$.Comment: 8 pages, 8 figure

Storage and retrieval of continuous-variable polarization-entangled cluster states in atomic ensembles

We present a proposal for storing and retrieving a continuous-variable quadripartite polarization-entangled cluster state, using macroscopic atomic ensembles in a magnetic field. The Larmor precession of the atomic spins leads to a symmetry between the atomic canonical operators. In this scheme, each of the four spatially separated pulses passes twice through the respective ensemble in order to map the polarization-entangled cluster state onto the long-lived atomic ensembles. The stored state can then be retrieved by another four read-out pulses, each crossing the respective ensemble twice. By calculating the variances, we analyzed the fidelities of the storage and retrieval, and our scheme is feasible under realistic experimental conditions.Comment: 6 pages, 4 figure

Identification of SNP barcode biomarkers for genes associated with facial emotion perception using particle swarm optimization algorithm

BACKGROUND: Facial emotion perception (FEP) can affect social function. We previously reported that parts of five tested single-nucleotide polymorphisms (SNPs) in the MET and AKT1 genes may individually affect FEP performance. However, the effects of SNP-SNP interactions on FEP performance remain unclear. METHODS: This study compared patients with high and low FEP performances (n = 89 and 93, respectively). A particle swarm optimization (PSO) algorithm was used to identify the best SNP barcodes (i.e., the SNP combinations and genotypes that revealed the largest differences between the high and low FEP groups). RESULTS: The analyses of individual SNPs showed no significant differences between the high and low FEP groups. However, comparisons of multiple SNP-SNP interactions involving different combinations of two to five SNPs showed that the best PSO-generated SNP barcodes were significantly associated with high FEP score. The analyses of the joint effects of the best SNP barcodes for two to five interacting SNPs also showed that the best SNP barcodes had significantly higher odds ratios (2.119 to 3.138; P < 0.05) compared to other SNP barcodes. In conclusion, the proposed PSO algorithm effectively identifies the best SNP barcodes that have the strongest associations with FEP performance. CONCLUSIONS: This study also proposes a computational methodology for analyzing complex SNP-SNP interactions in social cognition domains such as recognition of facial emotion