Ly-alpha forest: efficient unbiased estimation of second-order properties with missing data

Context. One important step in the statistical analysis of the Ly-alpha forest data is the study of their second order properties. Usually, this is accomplished by means of the two-point correlation function or, alternatively, the K-function. In the computation of these functions it is necessary to take into account the presence of strong metal line complexes and strong Ly-alpha lines that can hidden part of the Ly-alpha forest and represent a non negligible source of bias. Aims. In this work, we show quantitatively what are the effects of the gaps introduced in the spectrum by the strong lines if they are not properly accounted for in the computation of the correlation properties. We propose a geometric method which is able to solve this problem and is computationally more efficient than the Monte Carlo (MC) technique that is typically adopted in Cosmology studies. The method is implemented in two different algorithms. The first one permits to obtain exact results, whereas the second one provides approximated results but is computationally very efficient. The proposed approach can be easily extended to deal with the case of two or more lists of lines that have to be analyzed at the same time. Methods. Numerical experiments are presented that illustrate the consequences to neglect the effects due to the strong lines and the excellent performances of the proposed approach. Results. The proposed method is able to remarkably improve the estimates of both the two-point correlation function and the K-function.Comment: A&A accepted, 12 pages, 15 figure

Measurement of the Drell-Yan differential cross section at 7 TeV

The Drell-Yan differential cross section is measured in pp collisions at sqrt(s) = 7 TeV, from a data sample collected with the CMS detector at the LHC, corresponding to an integrated luminosity of 36 pb^{-1}. The cross section measurement, normalized to the measured cross section in the Z region, is reported for both the dimuon and dielectron channels in the dilepton invariant mass range 15-600 GeV. The normalized cross section values are quoted both in the full phase space and within the detector acceptance. The effect of final state radiation is also identified. The results are found to agree with theoretical predictions.Comment: 8 pages, 4 figures, 2 tables, presented at the DPF conference (August 9-13, 2011

A Physicsl Model of Electron According to the Basic Structures of Matter Hypothesis

A physical model of the electron is suggested according to the basic structures of matter (BSM) hypothesis. BSM is based on an alternative concept about the physical vacuum, assuming that space contains an underlying grid structure of nodes formed of superdense subelementary particles, which are also involved in the structure of the elementary particles. The proposed grid structure is formed of vibrating nodes that possess quantum features and energy well. It is admitted that this hypothetical structure could account for the missing “dark matter” in the universe. The signature of this dark matter is apparent in the galactic rotational curves and in the relation between masses of the supermassive black hole in the galactic center and the host galaxy. The suggested model of the electron possesses oscillation features with anomalous magnetic moment and embedded signatures of the Compton wavelength and the fine-structure constant. The analysis of the interactions between the oscillating electron and the nodes of the vacuum grid structure allows us to obtain physical meaning for some fundamental constants

A New method for Analysis of Biomolecules Using the BSM-SG Atomic Models

Biomolecules and particularly proteins and DNA exhibit some mysterious features that cannot find satisfactory explanation by quantum mechanical modes of atoms. One of them, known as a Levinthal’s paradox, is the ability to preserve their complex three-dimensional structure in appropriate environments. Another one is that they possess some unknown energy mechanism. The Basic Structures of Matter Supergravitation Unified Theory (BSM-SG) allows uncovering the real physical structures of the elementary particles and their spatial arrangement in atomic nuclei. The resulting physical models of the atoms are characterized by the same interaction energies as the quantum mechanical models, while the structure of the elementary particles influence their spatial arrangement in the nuclei. The resulting atomic models with fully identifiable parameters and angular positions of the quantum orbits permit studying the physical conditions behind the structural and bonding restrictions of the atoms connected in molecules. A new method for a theoretical analysis of biomolecules is proposed. The analysis of a DNA molecule leads to formulation of hypotheses about the energy storage mechanism in DNA and its role in the cell cycle synchronization. This permits shedding a light on the DNA feature known as a C-value paradox. The analysis of a tRNA molecule leads to formulation of a hypothesis about a binary decoding mechanism behind the 20 flavors of the complex aminoacyle-tRNA synthetases - tRNA, known as a paradox

Robust fault-tolerant control

There are two main approaches to fault-tolerant control: passive and active.This thesis presents both methods for passive and for active FTC

Racah Sum Rule and Biedenharn-Elliott Identity for the Super-Rotation 6−j6-j symbols

It is shown that the well known Racah sum rule and Biedenharn-Elliott identity satisfied by the recoupling coefficients or by the $6-j$ symbols of the usual rotation $SO(3)$ algebra can be extended to the corresponding features of the super-rotation $osp(1|2)$ superalgebra. The structure of the sum rules is completely similar in both cases, the only difference concerns the signs which are more involved in the super-rotation case.Comment: 9 pages. Two misprints correcte

Randomized Dimension Reduction on Massive Data

Scalability of statistical estimators is of increasing importance in modern applications and dimension reduction is often used to extract relevant information from data. A variety of popular dimension reduction approaches can be framed as symmetric generalized eigendecomposition problems. In this paper we outline how taking into account the low rank structure assumption implicit in these dimension reduction approaches provides both computational and statistical advantages. We adapt recent randomized low-rank approximation algorithms to provide efficient solutions to three dimension reduction methods: Principal Component Analysis (PCA), Sliced Inverse Regression (SIR), and Localized Sliced Inverse Regression (LSIR). A key observation in this paper is that randomization serves a dual role, improving both computational and statistical performance. This point is highlighted in our experiments on real and simulated data.Comment: 31 pages, 6 figures, Key Words:dimension reduction, generalized eigendecompositon, low-rank, supervised, inverse regression, random projections, randomized algorithms, Krylov subspace method