Power Spectrum Analysis of the 2dF QSO Sample Revisited

We revisit the power spectrum analysis of the complete sample of the two degree field (2dF) QSO redshift (2QZ) survey, as a complementary test of the work by Outram et al. (2003). A power spectrum consistent with that of the 2QZ group is obtained. Differently from their approach, fitting of the power spectrum is investigated incorporating the nonlinear effects, the geometric distortion and the light-cone effect. It is shown that the QSO power spectrum is consistent with the $\Lambda$ cold dark matter (CDM) model with the matter density parameter $\Omega_m=0.2\sim0.5$. Our constraint on the density parameter is rather weaker than that of the 2QZ group. We also show that the constraint slightly depends on the equation of state parameter $w$ of the dark energy. The constraint on $w$ from the QSO power spectrum is demonstrated, though it is not very tight.Comment: 15 pages, 5 figures, accepted for publication in the Astrophysical Journa

Formation time distribution of dark matter haloes: theories versus N-body simulations

This paper uses numerical simulations to test the formation time distribution of dark matter haloes predicted by the analytic excursion set approaches. The formation time distribution is closely linked to the conditional mass function and this test is therefore an indirect probe of this distribution. The excursion set models tested are the extended Press-Schechter (EPS) model, the ellipsoidal collapse (EC) model, and the non-spherical collapse boundary (NCB) model. Three sets of simulations (6 realizations) have been used to investigate the halo formation time distribution for halo masses ranging from dwarf-galaxy like haloes ($M=10^{-3} M_*$, where $M_*$ is the characteristic non-linear mass scale) to massive haloes of $M=8.7 M_*$. None of the models can match the simulation results at both high and low redshift. In particular, dark matter haloes formed generally earlier in our simulations than predicted by the EPS model. This discrepancy might help explain why semi-analytic models of galaxy formation, based on EPS merger trees, under-predict the number of high redshift galaxies compared with recent observations.Comment: 7 pages, 5 figures, accepted for publication in MNRA

Unique gap structure and symmetry of the charge density wave in single-layer VSe2_2

Single layers of transition metal dichalcogenides (TMDCs) are excellent candidates for electronic applications beyond the graphene platform; many of them exhibit novel properties including charge density waves (CDWs) and magnetic ordering. CDWs in these single layers are generally a planar projection of the corresponding bulk CDWs because of the quasi-two-dimensional nature of TMDCs; a different CDW symmetry is unexpected. We report herein the successful creation of pristine single-layer VSe$_2$, which shows a ($\sqrt7 \times \sqrt3$) CDW in contrast to the (4 $\times$ 4) CDW for the layers in bulk VSe$_2$. Angle-resolved photoemission spectroscopy (ARPES) from the single layer shows a sizable ($\sqrt7 \times \sqrt3$) CDW gap of $\sim$100 meV at the zone boundary, a 220 K CDW transition temperature twice the bulk value, and no ferromagnetic exchange splitting as predicted by theory. This robust CDW with an exotic broken symmetry as the ground state is explained via a first-principles analysis. The results illustrate a unique CDW phenomenon in the two-dimensional limit

Scaling properties of the redshift power spectrum: theoretical models

We report the results of an analysis of the redshift power spectrum $P^S(k,\mu)$ in three typical Cold Dark Matter (CDM) cosmological models, where $\mu$ is the cosine of the angle between the wave vector and the line-of-sight. Two distinct biased tracers derived from the primordial density peaks of Bardeen et al. and the cluster-underweight model of Jing, Mo, & B\"orner are considered in addition to the pure dark matter models. Based on a large set of high resolution simulations, we have measured the redshift power spectrum for the three tracers from the linear to the nonlinear regime. We investigate the validity of the relation - guessed from linear theory - in the nonlinear regime $$P^S(k,\mu)=P^R(k)[1+\beta\mu^2]^2D(k,\mu,\sigma_{12}(k)),$$ where $P^R(k)$ is the real space power spectrum, and $\beta$ equals $\Omega_0^{0.6}/b_l$. The damping function $D$ which should generally depend on $k$, $\mu$, and $\sigma_{12}(k)$, is found to be a function of only one variable $k\mu\sigma_{12}(k)$. This scaling behavior extends into the nonlinear regime, while $D$ can be accurately expressed as a Lorentz function - well known from linear theory - for values $D > 0.1$. The difference between $\sigma_{12}(k)$ and the pairwise velocity dispersion defined by the 3-D peculiar velocity of the simulations (taking $r=1/k$) is about 15%. Therefore $\sigma_{12}(k)$ is a good indicator of the pairwise velocity dispersion. The exact functional form of $D$ depends on the cosmological model and on the bias scheme. We have given an accurate fitting formula for the functional form of $D$ for the models studied.Comment: accepted for publication in ApJ;24 pages with 7 figures include

Can Geometric Test Probe the Cosmic Equation of State ?

Feasibility of the geometric test as a probe of the cosmic equation of state of the dark energy is discussed assuming the future 2dF QSO sample. We examine sensitivity of the QSO two-point correlation functions, which are theoretically computed incorporating the light-cone effect and the redshift distortions, as well as the nonlinear effect, to a bias model whose evolution is phenomenologically parameterized. It is shown that the correlation functions are sensitive on a mean amplitude of the bias and not to the speed of the redshift evolution. We will also demonstrate that an optimistic geometric test could suffer from confusion that a signal from the cosmological model can be confused with that from a stochastic character of the bias.Comment: 11 pages, including 3 figures, accepted for publication in ApJ

Metabolic responses of alfalfa (Medicago Sativa L.) leaves to low and high temperature induced stresses

To explore adaptation mechanism of alfalfa to cold and heat stresses, status of sucrose metabolism and relative water content (RWC) in leaves under low and high temperature treatments were studied. Seedlings (35 day old) were transferred to chambers for treatments. First group was subjected to 5°C as low temperature (LT) stress, second group at 33°C as high temperature (HT) stress and third group at 25°C as the control (CK). Results indicated that, both stresses led to an increase in degree and duration of genes expression and corresponding enzymes activities of sucrose phosphate synthase (SPS) and sucrose synthase (SS), but LT showed a more significant effect. As a result, lower starch content and higher contents of soluble reducing sugar, fructose and sucrose were observed under LT stress. Moreover, LT stress lowered malondialdehyde (MDA) content and electrolyte leakage in leaves, thus achieving a higher RWC. It was suggested that, relatively higher RWC in leaves by LT stress resulted from lowered water potential, and transpiration can explain the reason that alfalfa plants are cold-tolerant but heat-sensitive.Key words: Alfalfa, temperature stress, sucrose, sucrose phosphate synthase (SPS), relative water content

Genome-Wide Localization of Protein-DNA Binding and Histone Modification by a Bayesian Change-Point Method with ChIP-seq Data

Next-generation sequencing (NGS) technologies have matured considerably since their introduction and a focus has been placed on developing sophisticated analytical tools to deal with the amassing volumes of data. Chromatin immunoprecipitation sequencing (ChIP-seq), a major application of NGS, is a widely adopted technique for examining protein-DNA interactions and is commonly used to investigate epigenetic signatures of diffuse histone marks. These datasets have notoriously high variance and subtle levels of enrichment across large expanses, making them exceedingly difficult to define. Windows-based, heuristic models and finite-state hidden Markov models (HMMs) have been used with some success in analyzing ChIP-seq data but with lingering limitations. To improve the ability to detect broad regions of enrichment, we developed a stochastic Bayesian Change-Point (BCP) method, which addresses some of these unresolved issues. BCP makes use of recent advances in infinite-state HMMs by obtaining explicit formulas for posterior means of read densities. These posterior means can be used to categorize the genome into enriched and unenriched segments, as is customarily done, or examined for more detailed relationships since the underlying subpeaks are preserved rather than simplified into a binary classification. BCP performs a near exhaustive search of all possible change points between different posterior means at high-resolution to minimize the subjectivity of window sizes and is computationally efficient, due to a speed-up algorithm and the explicit formulas it employs. In the absence of a well-established "gold standard" for diffuse histone mark enrichment, we corroborated BCP's island detection accuracy and reproducibility using various forms of empirical evidence. We show that BCP is especially suited for analysis of diffuse histone ChIP-seq data but also effective in analyzing punctate transcription factor ChIP datasets, making it widely applicable for numerous experiment types