New surveys of UBV photometry and absolute proper motions at intermediate latitude

A photometric and proper motion survey has been obtained in 2 directions at intermediate latitude: ($l=167.5^\circ$, $b=47.4^\circ$; $\alpha_{2000}=9^h41^m26^s$,$\delta_{2000}=+49^\circ53'27''$) and ($l=278^\circ$, $b=47^\circ$; $\alpha_{2000}=11^h42^m56^s$, $\delta_{2000}=-12^\circ31'42''$). The survey covers 7.13 and 20.84 square degrees, respectively. The limiting magnitude is about 18.5 in V for both directions. We have derived the density laws for stars (M$_{V}$ $\ge$ 3.5) as a function of distance from the galactic plane. The density laws for stars follow a sum of two exponentials with scale heights of 240 pc (thin disk) and 790 pc (thick disk), respectively. The local density of thick disk is found to be 6.1$\pm$3 % relative to the thin disk. The kinematical distribution of stars has been probed to distances up to 3.5 kpc above the galactic plane. New estimates of the parameters of velocity ellipsoid have been derived for the thick disk of the Galaxy. A comparison of our data sets with the Besan\c con model star count predictions has been performed, giving a good agreement in the magnitude range V = 13 to 18.Comment: 13 pages, 8 PS figures, To appear in A&

Evaluation of rice–legume–rice cropping system on grain yield, nutrient uptake, nitrogen fixation, and chemical, physical, and biological properties of soil

To achieve higher yields and better soil quality under rice–legume–rice (RLR) rotation in a rainfed production system, we formulated integrated nutrient management (INM) comprised of Azospirillum (Azo), Rhizobium (Rh), and phosphate-solubilizing bacteria (PSB) with phosphate rock (PR), compost, and muriate of potash (MOP). Performance of bacterial bioinoculants was evaluated by determining grain yield, nitrogenase activity, uptake and balance of N, P, and Zn, changes in water stability and distribution of soil aggregates, soil organic C and pH, fungal/bacterial biomass C ratio, casting activities of earthworms, and bacterial community composition using denaturing gradient gel electrophoresis (DGGE) fingerprinting. The performance comparison was made against the prevailing farmers’ nutrient management practices [N/P2O5/K2O at 40:20:20 kg ha−1 for rice and 20:30:20 kg ha−1 for legume as urea/single super-phosphate/MOP (urea/SSP/MOP)]. Cumulative grain yields of crops increased by 7–16% per RLR rotation and removal of N and P by six crops of 2 years rotation increased significantly (P < 0.05) in bacterial bioinoculants-based INM plots over that in compost alone or urea/SSP/MOP plots. Apparent loss of soil total N and P at 0–15 cm soil depth was minimum and apparent N gain at 15–30 cm depth was maximum in Azo/Rh plus PSB dual INM plots. Zinc uptake by rice crop and diethylenetriaminepentaacetate-extractable Zn content in soil increased significantly (P < 0.05) in bacterial bioinoculants-based INM plots compared to other nutrient management plots. Total organic C content in soil declined at 0–15 cm depth and increased at 15–30 cm depth in all nutrient management plots after a 2-year crop cycle; however, bacterial bioinoculants-based INM plots showed minimum loss and maximum gain of total organic C content in the corresponding soil depths. Water-stable aggregation and distribution of soil aggregates in 53–250- and 250–2,000 μm classes increased significantly (P < 0.05) in bacterial bioinoculants-based INM plots compared to other nutrient management plots. Fungal/bacterial biomass C ratio seems to be a more reliable indicator of C and N dynamics in acidic soils than total microbial biomass C. Compost alone or Azo/Rh plus PSB dual INM plots showed significantly (P < 0.05) higher numbers of earthworms’ casts compared to urea/SSP/MOP alone and bacterial bioinoculants with urea or SSP-applied plots. Hierarchical cluster analysis based on similarity matrix of DGGE profiles revealed changes in bacterial community composition in soils due to differences in nutrient management, and these changes were seen to occur according to the states of C and N dynamics in acidic soil under RLR rotation

Electronic structure interpolation via atomic orbitals

We present an efficient scheme for accurate electronic structure interpolations based on the systematically improvable optimized atomic orbitals. The atomic orbitals are generated by minimizing the spillage value between the atomic basis calculations and the converged plane wave basis calculations on some coarse $k$-point grid. They are then used to calculate the band structure of the full Brillouin zone using the linear combination of atomic orbitals (LCAO) algorithms. We find that usually 16 -- 25 orbitals per atom can give an accuracy of about 10 meV compared to the full {\it ab initio} calculations. The current scheme has several advantages over the existing interpolation schemes. The scheme is easy to implement and robust which works equally well for metallic systems and systems with complex band structures. Furthermore, the atomic orbitals have much better transferability than the Shirley's basis and Wannier functions, which is very useful for the perturbation calculations

A Doubling Technique for the Power Method Transformations

Power method polynomials are used for simulating non-normal distributions with specified product moments or L-moments. The power method is capable of producing distributions with extreme values of skew (L-skew) and kurtosis (L-kurtosis). However, these distributions can be extremely peaked and thus not representative of real-world data. To obviate this problem, two families of distributions are introduced based on a doubling technique with symmetric standard normal and logistic power method distributions. The primary focus of the methodology is in the context of L-moment theory. As such, L-moment based systems of equations are derived for simulating univariate and multivariate non-normal distributions with specified values of L-skew, L-kurtosis, and L-correlation. Evaluation of the proposed doubling technique indicates that estimates of L-skew, L-kurtosis, and L-correlation are superior to conventional product-moments in terms of relative bias and relative efficiency when extreme non-normal distributions are of concern

Adaptive homodyne phase discrimination and qubit measurement

Fast and accurate measurement is a highly desirable, if not vital, feature of quantum computing architectures. In this work we investigate the usefulness of adaptive measurements in improving the speed and accuracy of qubit measurement. We examine a particular class of quantum computing architectures, ones based on qubits coupled to well controlled harmonic oscillator modes (reminiscent of cavity-QED), where adaptive schemes for measurement are particularly appropriate. In such architectures, qubit measurement is equivalent to phase discrimination for a mode of the electromagnetic field, and we examine adaptive techniques for doing this. In the final section we present a concrete example of applying adaptive measurement to the particularly well-developed circuit-QED architecture.Comment: 9 pages, 8 figures. Published versio

An L-Moment Based Characterization of the Family of Dagum Distributions

This paper introduces a method for simulating univariate and multivariate Dagum distributions through the method of L-moments and L-correlation. A method is developed for characterizing non-normal Dagum distributions with controlled degrees of L-skew, L-kurtosis, and L-correlations. The procedure can be applied in a variety of contexts such as statistical modeling (e.g., income distribution, personal wealth distributions, etc.) and Monte Carlo or simulation studies. Numerical examples are provided to demonstrate that -moment-based Dagum distributions are superior to their conventional moment-based analogs in terms of estimation and distribution fitting. Evaluation of the proposed method also demonstrates that the estimates of L-skew, L-kurtosis, and L-correlation are substantially superior to their conventional product-moment based counterparts of skew, kurtosis, and Pearson correlation in terms of relative bias and relative efficiency–most notably in the context of heavy-tailed distributions

An \u3ci\u3eL\u3c/i\u3e-Moment-Based Analog for the Schmeiser-Deutsch Class of Distributions

This paper characterizes the conventional moment-based Schmeiser-Deutsch (S-D) class of distributions through the method of L-moments. The system can be used in a variety of settings such as simulation or modeling various processes. A procedure is also described for simulating S-D distributions with specified L-moments and L-correlations. The Monte Carlo results presented in this study indicate that the estimates of L-skew, L-kurtosis, and L-correlation associated with the S-D class of distributions are substantially superior to their corresponding conventional product-moment estimators in terms of relative bias—most notably when sample sizes are small

Uniform-based and triangular-based third-order power method distributions using a doubling technique distributions

Power method (PM) polynomials have been used for simulating non-normal distributions in a variety of settings such as toxicology research, price risk, business-cycle features, microarray analysis, computer adaptive testing, and structural equation modeling. A majority of the applications associated with the PM polynomials are based on the method of matching conventional moments (e.g., skew and kurtosis). However, estimators of skew and kurtosis can be (a) substantially biased, (b) highly dispersed, or (c) influenced by outliers. To address this limitation, two families of third-order PM distributions are developed through the method of -moments (Hosking, 1990) using a doubling technique (Morgenthaler & Tukey, 2000) and contrasted with the method of moments in the contexts of estimation of parameters. The methodology is based on simulating uniform- and triangular-based third-order PM distributions with specified values of -skew and - kurtosis. Monte Carlo simulation results indicate that the estimators based on method of Lmoments are superior to their conventional moment-based counterparts

Characterizing Tukey \u3ci\u3eh\u3c/i\u3e and \u3ci\u3ehh\u3c/i\u3e-Distributions through \u3ci\u3eL\u3c/i\u3e-Moments and the \u3ci\u3eL\u3c/i\u3e-Correlation

This paper introduces the Tukey family of symmetric h and asymmetric hh-distributions in the contexts of univariate L-moments and the L-correlation. Included is the development of a procedure for specifying nonnormal distributions with controlled degrees of L-skew, L-kurtosis, and L-correlations. The procedure can be applied in a variety of settings such as modeling events (e.g., risk analysis, extreme events) and Monte Carlo or simulation studies. Further, it is demonstrated that estimates of L-skew, L-kurtosis, and L-correlation are substantially superior to conventional product-moment estimates of skew, kurtosis, and Pearson correlation in terms of both relative bias and efficiency when heavy-tailed distributions are of concern