Single Top Production as a Probe of B-prime Quarks

We show how single top production at the LHC can be used to discover (and characterize the couplings of) B' quarks, which are an essential part of many natural models of new physics beyond the Standard Model. We present the B' effective model and concentrate on resonant production via a colored anomalous magnetic moment. Generally, B's preferentially decay into a single top quark produced in association with a W boson; thus, this production process makes associated single top production essential to B' searches at the LHC. We demonstrate the background processes are manageable and the signal cross section is sufficient to yield a large signal significance even during the 7 TeV LHC run. Specifically, we show that B' masses of 700 GeV or more can be probed. Moreover, if a B' is found, then the chirality of its coupling can be determined. Finally, we present signal cross sections for several different LHC energies.Comment: 19 pages, 7 figures, 1 tabl

Direct reconstruction of dynamical dark energy from observational Hubble parameter data

Reconstructing the evolution history of the dark energy equation of state parameter $w(z)$ directly from observational data is highly valuable in cosmology, since it contains substantial clues in understanding the nature of the accelerated expansion of the Universe. Many works have focused on reconstructing $w(z)$ using Type Ia supernova data, however, only a few studies pay attention to Hubble parameter data. In the present work, we explore the merit of Hubble parameter data and make an attempt to reconstruct $w(z)$ from them through the principle component analysis approach. We find that current Hubble parameter data perform well in reconstructing $w(z)$; though, when compared to supernova data, the data are scant and their quality is worse. Both $\Lambda$CDM and evolving $w(z)$ models can be constrained within $10\%$ at redshifts $z \lesssim 1.5$ and even $5\%$ at redshifts 0.1 $\lesssim$ z $\lesssim$ 1 by using simulated $H(z)$ data of observational quality.Comment: 25 pages, 11 figure

Spin-quadrupole ordering of spin-3/2 ultracold fermionic atoms in optical lattices in the one-band Hubbard model

Based on a generalized one-band Hubbard model, we study magnetic properties of Mott insulating states for ultracold spin-3/2 fermionic atoms in optical lattices. When the \textit{s}-wave scattering lengths for the total spin $S=2,0$ satisfy conditions $a_{2}>a_{0}>0$, we apply a functional integral approach to the half filled case, where the spin-quadrupole fluctuations dominate. On a 2D square lattice, the saddle point solution yields a staggered spin-quadrupole ordering at zero temperature with symmetry breaking from SO(5) to SO(4). Both spin and spin-quadrupole static structure factors are calculated, displaying highly anisotropic spin antiferromagnetic fluctuations and antiferroquadrupole long-range correlations, respectively. When Gaussian fluctuations around the saddle point are taken into account, spin-quadrupole density waves with a linear dispersion are derived. Compared with the spin density waves in the half filled spin-1/2 Hubbard model, the quadrupole density wave velocity is saturated in the strong-coupling limit, and there are no transverse spin-quadrupole mode couplings, as required by the SO(4) invariance of the effective action. Finally, in the strong-coupling limit of the model Hamiltonian, we derive the effective hyperfine spin-exchange interactions for the Mott insulating phases in the quarter filled and half filled cases, respectively.Comment: 12 pages, 5 figure

Topological phases and fractional excitations of the exciton condensate in a special class of bilayer systems

We study the exciton condensate in zero temperature limit in a special class of electron-hole bilayer systems adjacent to insulating ferromagnetic films. With the self-consistent mean-field approximation, we find that the Rashba spin-orbit interaction in the electron and hole layers can induce the p \pm ip or p pairing states depending on the different magnetization of the overlapped ferromagnetic films. Correspondingly, the topologically nontrivial or trivial phases emerge. Furthermore, in the topologically nontrivial phase, the quasiparticle excitations of the U(1) vortex are attached to fractional quantum numbers and obey Abelian statistics.Comment: 7 pages, 5 figure

Datta-Das transistor: Significance of channel direction, size-dependence of source contacts, and boundary effects

We analyze the spin expectation values for injected spin-polarized electrons (spin vectors) in a [001]-grown Rashba-Dresselhaus two-dimensional electron gas (2DEG). We generalize the calculation for point spin injection in semi-infinite 2DEGs to finite-size spin injection in bounded 2DEGs. Using the obtained spin vector formula, significance of the channel direction for the Datta-Das transistor is illustrated. Numerical results indicate that the influence due to the finite-size injection is moderate, while the channel boundary reflection may bring unexpected changes. Both effects are concluded to decrease when the spin-orbit coupling strength is strong. Hence [110] is a robust channel direction and is therefore the best candidate for the design of the Datta-Das transistor.Comment: 5 pages, 4 figures, accepted for publication in Physical Review

DOUBLETIME Plays a Noncatalytic Role To Mediate CLOCK Phosphorylation and Repress CLOCK-Dependent Transcription within the Drosophila Circadian Clock

Circadian clocks keep time via gene expression feedback loops that are controlled by time-of-day-specific changes in the synthesis, activity, and degradation of transcription factors. Within the Drosophila melanogaster circadian clock, DOUBLETIME (DBT) kinase is necessary for the phosphorylation of PERIOD (PER), a transcriptional repressor, and CLOCK (CLK), a transcriptional activator, as CLK-dependent transcription is being repressed. PER- and DBT-containing protein complexes feed back to repress CLK-dependent transcription, but how DBT promotes PER and CLK phosphorylation and how PER and CLK phosphorylation contributes to transcriptional repression have not been defined. Here, we show that DBT catalytic activity is not required for CLK phosphorylation or transcriptional repression and that PER phosphorylation is dispensable for repressing CLK-dependent transcription. These results support a model in which DBT plays a novel noncatalytic role in recruiting additional kinases that phosphorylate CLK, thereby repressing transcription. A similar mechanism likely operates in mammals, given the conserved activities of PER, DBT, and CLK orthologs

Spin precession due to spin-orbit coupling in a two-dimensional electron gas with spin injection via ideal quantum point contact

We present the analytical result of the expectation value of spin resulting from an injected spin polarized electron into a semi-infinitely extended 2DEG plane with [001] growth geometry via ideal quantum point contact. Both the Rashba and Dresselhaus spin-orbit couplings are taken into account. A pictorial interpretation of the spin precession along certain transport directions is given. The spin precession due to the Rashba term is found to be especially interesting since it behaves simply like a windshield wiper which is very different from the ordinary precession while that due to the Dresselhaus term is shown to be crystallographic-direction-dependent. Some crystallographic directions with interesting and handleable behavior of spin precession are found and may imply certain applicability in spintronic devices.Comment: 5 pages, 2 figures, submitted to Phys. Rev.

Transcript analysis and expression profiling of three heat shock protein 70 genes in the ectoparasitoid \u3ci\u3eHabrobracon hebetor\u3c/i\u3e (Hymenoptera: Braconidae)

Heat shock proteins (HSPs) are known as chaperones that help with folding of other proteins when cells are under environmental stresses. The upregulation of HSPs is essential for cold survival during insect diapause. The ectoparasitoid Habrobracon hebetor, a potential biological control agent, can enter reproductive diapause when reared at low temperature and short photoperiod. However, the expression of HSPs during diapause of H. hebetor has not been studied. In this study, we sequenced and characterized the full-length complementary DNAs of three Hsp70 genes (HhHsp70I, HhHsp70II and HhHsp70III) from H. hebetor. Their deduced amino acid sequences showed more than 80% identities to their counterparts from other insect species. However, the multiple sequence alignment among the three deduced amino acid sequences of HhHsp70s showed only 46% identities. A phylogenetic analysis of the three HhHsp70s and all other known Hsp70 sequences from Hymenoptera clustered all the Hsp70s into four groups, and the three HhHsp70s were distributed into three different groups. Real-time quantitative polymerase chain reaction analysis showed that the expression of the three HhHsp70 genes in H. hebetor reared at different conditions was quite different. HhHsp70I showed higher relative expression when H. hebetor were reared at 27.5◦C than at two lower temperatures (17.5◦C and 20◦C) regardless of the photoperiod, whereas HhHsp70II showed higher expression when H. hebetor were reared at 20◦C and 10 : 14 L : D than when reared at 17.5◦C and either 16 : 8 L : D or 10 : 14 L : D. In contrast, HhHSP70III was expressed at similar levels regardless of the rearing conditions. These results may suggest functional differences among the three HhHsp70 genes in H. hebetor

ThumbNet: One Thumbnail Image Contains All You Need for Recognition

Although deep convolutional neural networks (CNNs) have achieved great success in computer vision tasks, its real-world application is still impeded by its voracious demand of computational resources. Current works mostly seek to compress the network by reducing its parameters or parameter-incurred computation, neglecting the influence of the input image on the system complexity. Based on the fact that input images of a CNN contain substantial redundancy, in this paper, we propose a unified framework, dubbed as ThumbNet, to simultaneously accelerate and compress CNN models by enabling them to infer on one thumbnail image. We provide three effective strategies to train ThumbNet. In doing so, ThumbNet learns an inference network that performs equally well on small images as the original-input network on large images. With ThumbNet, not only do we obtain the thumbnail-input inference network that can drastically reduce computation and memory requirements, but also we obtain an image downscaler that can generate thumbnail images for generic classification tasks. Extensive experiments show the effectiveness of ThumbNet, and demonstrate that the thumbnail-input inference network learned by ThumbNet can adequately retain the accuracy of the original-input network even when the input images are downscaled 16 times