Photometric Variability in the CSTAR Field: Results From the 2008 Data Set

The Chinese Small Telescope ARray (CSTAR) is the first telescope facility built at Dome A, Antarctica. During the 2008 observing season, the installation provided long-baseline and high-cadence photometric observations in the i-band for 18,145 targets within 20 deg2 CSTAR field around the South Celestial Pole for the purpose of monitoring the astronomical observing quality of Dome A and detecting various types of photometric variability. Using sensitive and robust detection methods, we discover 274 potential variables from this data set, 83 of which are new discoveries. We characterize most of them, providing the periods, amplitudes and classes of variability. The catalog of all these variables is presented along with the discussion of their statistical properties.

Eclipsing Binaries From the CSTAR Project at Dome A, Antarctica

The Chinese Small Telescope ARray (CSTAR) has observed an area around the Celestial South Pole at Dome A since 2008. About $20,000$ light curves in the i band were obtained lasting from March to July, 2008. The photometric precision achieves about 4 mmag at i = 7.5 and 20 mmag at i = 12 within a 30 s exposure time. These light curves are analyzed using Lomb--Scargle, Phase Dispersion Minimization, and Box Least Squares methods to search for periodic signals. False positives may appear as a variable signature caused by contaminating stars and the observation mode of CSTAR. Therefore the period and position of each variable candidate are checked to eliminate false positives. Eclipsing binaries are removed by visual inspection, frequency spectrum analysis and locally linear embedding technique. We identify 53 eclipsing binaries in the field of view of CSTAR, containing 24 detached binaries, 8 semi-detached binaries, 18 contact binaries, and 3 ellipsoidal variables. To derive the parameters of these binaries, we use the Eclipsing Binaries via Artificial Intelligence (EBAI) method. The primary and the secondary eclipse timing variations (ETVs) for semi-detached and contact systems are analyzed. Correlated primary and secondary ETVs confirmed by false alarm tests may indicate an unseen perturbing companion. Through ETV analysis, we identify two triple systems (CSTAR J084612.64-883342.9 and CSTAR J220502.55-895206.7). The orbital parameters of the third body in CSTAR J220502.55-895206.7 are derived using a simple dynamical model.

Planetary Transit Candidates in the CSTAR Field: Analysis of the 2008 Data

The Chinese Small Telescope ARray (CSTAR) is a group of four identical, fully automated, static 14.5 cm telescopes. CSTAR is located at Dome A, Antarctica and covers 20 square degree of sky around the South Celestial Pole. The installation is designed to provide high-cadence photometry for the purpose of monitoring the quality of the astronomical observing conditions at Dome A and detecting transiting exoplanets. CSTAR has been operational since 2008, and has taken a rich and high-precision photometric data set of 10,690 stars. In the first observing season, we obtained 291,911 qualified science frames with 20-second integrations in the i-band. Photometric precision reaches about 4 mmag at 20-second cadence at i=7.5, and is about 20 mmag at i=12. Using robust detection methods, ten promising exoplanet candidates were found. Four of these were found to be giants using spectroscopic follow-up. All of these transit candidates are presented here along with the discussion of their detailed properties as well as the follow-up observations.

Semi-Penalized Inference with Direct False Discovery Rate Control in High-Dimensions

We propose a new method, semi-penalized inference with direct false discovery rate control (SPIDR), for variable selection and confidence interval construction in high-dimensional linear regression. SPIDR first uses a semi-penalized approach to constructing estimators of the regression coefficients. We show that the SPIDR estimator is ideal in the sense that it equals an ideal least squares estimator with high probability under a sparsity and other suitable conditions. Consequently, the SPIDR estimator is asymptotically normal. Based on this distributional result, SPIDR determines the selection rule by directly controlling false discovery rate. This provides an explicit assessment of the selection error. This also naturally leads to confidence intervals for the selected coefficients with a proper confidence statement. We conduct simulation studies to evaluate its finite sample performance and demonstrate its application on a breast cancer gene expression data set. Our simulation studies and data example suggest that SPIDR is a useful method for high-dimensional statistical inference in practice.

Gap formation in a self-gravitating disk and the associated migration of the embedded giant planet

We present the results of our recent study on the interactions between a giant planet and a self-gravitating gas disk. We investigate how the disks self-gravity affects the gap formation process and the migration of the giant planet. Two series of 1-D and 2-D hydrodynamic simulations are performed. We select several surface densities and focus on the gravitationally stable region. To obtain more reliable gravity torques exerted on the planet, a refined treatment of disks gravity is adopted in the vicinity of the planet. Our results indicate that the net effect of the disks self-gravity on the gap formation process depends on the surface density of the disk. We notice that there are two critical values, Sigma_I and Sigma_II. When the surface density of the disk is lower than the first one, Sigma_0 < Sigma_I, the effect of self-gravity suppresses the formation of a gap. When Sigma_0 > Sigma_I, the self-gravity of the gas tends to benefit the gap formation process and enlarge the width/depth of the gap. According to our 1-D and 2-D simulations, we estimate the first critical surface density Sigma_I approx 0.8MMSN. This effect increases until the surface density reaches the second critical value Sigma_II. When Sigma_0 > Sigma_II, the gravitational turbulence in the disk becomes dominant and the gap formation process is suppressed again. Our 2-D simulations show that this critical surface density is around 3.5MMSN. We also study the associated orbital evolution of a giant planet. Under the effect of the disks self-gravity, the migration rate of the giant planet increases when the disk is dominated by gravitational turbulence. We show that the migration timescale associates with the effective viscosity and can be up to 10^4 yr.

Asymptotic normality and optimalities in estimation of large Gaussian graphical models

The Gaussian graphical model, a popular paradigm for studying relationship among variables in a wide range of applications, has attracted great attention in recent years. This paper considers a fundamental question: When is it possible to estimate low-dimensional parameters at parametric square-root rate in a large Gaussian graphical model? A novel regression approach is proposed to obtain asymptotically efficient estimation of each entry of a precision matrix under a sparseness condition relative to the sample size. When the precision matrix is not sufficiently sparse, or equivalently the sample size is not sufficiently large, a lower bound is established to show that it is no longer possible to achieve the parametric rate in the estimation of each entry. This lower bound result, which provides an answer to the delicate sample size question, is established with a novel construction of a subset of sparse precision matrices in an application of Le Cams lemma. Moreover, the proposed estimator is proven to have optimal convergence rate when the parametric rate cannot be achieved, under a minimal sample requirement. The proposed estimator is applied to test the presence of an edge in the Gaussian graphical model or to recover the support of the entire model, to obtain adaptive rate-optimal estimation of the entire precision matrix as measured by the matrix $ell_q$ operator norm and to make inference in latent variables in the graphical model. All of this is achieved under a sparsity condition on the precision matrix and a side condition on the range of its spectrum. This significantly relaxes the commonly imposed uniform signal strength condition on the precision matrix, irrepresentability condition on the Hessian tensor operator of the covariance matrix or the $ell_1$ constraint on the precision matrix. Numerical results confirm our theoretical findings. The ROC curve of the proposed algorithm, Asymptotic Normal Thresholding (ANT), for support recovery significantly outperforms that of the popular GLasso algorithm.

Feature Selection Based on Term Frequency and T-Test for Text Categorization

Much work has been done on feature selection. Existing methods are based on document frequency, such as Chi-Square Statistic, Information Gain etc. However, these methods have two shortcomings: one is that they are not reliable for low-frequency terms, and the other is that they only count whether one term occurs in a document and ignore the term frequency. Actually, high-frequency terms within a specific category are often regards as discriminators. This paper focuses on how to construct the feature selection function based on term frequency, and proposes a new approach based on $t$-test, which is used to measure the diversity of the distributions of a term between the specific category and the entire corpus. Extensive comparative experiments on two text corpora using three classifiers show that our new approach is comparable to or or slightly better than the state-of-the-art feature selection methods (i.e., $chi^2$, and IG) in terms of macro-$F_1$ and micro-$F_1$.

Detect Related Bugs from Source Code Using Bug Information

Open source projects often maintain open bug repositories during development and maintenance, and the reporters often point out straightly or implicitly the reasons why bugs occur when they submit them. The comments about a bug are very valuable for developers to locate and fix the bug. Meanwhile, it is very common in large software for programmers to override or overload some methods according to the same logic. If one method causes a bug, it is obvious that other overridden or overloaded methods maybe cause related or similar bugs. In this paper, we propose and implement a tool Rebug- Detector, which detects related bugs using bug information and code features. Firstly, it extracts bug features from bug information in bug repositories; secondly, it locates bug methods from source code, and then extracts code features of bug methods; thirdly, it calculates similarities between each overridden or overloaded method and bug methods; lastly, it determines which method maybe causes potential related or similar bugs. We evaluate Rebug-Detector on an open source project: Apache Lucene-Java. Our tool totally detects 61 related bugs, including 21 real bugs and 10 suspected bugs, and it costs us about 15.5 minutes. The results show that bug features and code features extracted by our tool are useful to find real bugs in existing projects.

Universal $sqrt{2}timessqrt{2}$ structure and short-range charge order at the surfaces of BaFe$_{2-x}$Co$_{x}$As$_{2}$ compounds with various Co doping levels

The structure and electronic order at the cleaved (001) surfaces of the newly-discovered pnictide superconductors BaFe$_{2-x}$Co$_{x}$As$_{2}$ with x ranging from 0 to 0.32 are systematically investigated by scanning tunneling microscopy. A $sqrt{2}timessqrt{2}$ surface structure is revealed for all the compounds, and is identified to be Ba layer with half Ba atoms lifted-off by combination with theoretical simulation. A universal short-range charge order is observed at this $sqrt{2}timessqrt{2}$ surface associated with an energy gap of about 30 meV for all the compounds.

On the Yang-Mills two-loop effective action with wordline methods

We derive the two-loop effective action for covariantly constant field strength of pure Yang-Mills theory in the presence of an infrared scale. The computation is done in the framework of the worldline formalism, based on a generalization procedure of constructing multiloop effective actions in terms of the bosonic worldline path integral. The two-loop beta-function is correctly reproduced. This is the first derivation in the worldline formulation, and serves as a nontrivial check on the consistency of the multiloop generalization procedure in the worldline formalism.