5,651 research outputs found
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 symbols
It is shown that the well known Racah sum rule and Biedenharn-Elliott
identity satisfied by the recoupling coefficients or by the symbols of
the usual rotation algebra can be extended to the corresponding
features of the super-rotation 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
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