527 research outputs found
Benchmark Parameters for CMB Polarization Experiments
The recently detected polarization of the cosmic microwave background (CMB)
holds the potential for revealing the physics of inflation and gravitationally
mapping the large-scale structure of the universe, if so called B-mode signals
below 10^{-7}, or tenths of a uK, can be reliably detected. We provide a
language for describing systematic effects which distort the observed CMB
temperature and polarization fields and so contaminate the B-modes. We identify
7 types of effects, described by 11 distortion fields, and show their
association with known instrumental systematics such as common mode and
differential gain fluctuations, line cross-coupling, pointing errors, and
differential polarized beam effects. Because of aliasing from the small-scale
structure in the CMB, even uncorrelated fluctuations in these effects can
affect the large-scale B modes relevant to gravitational waves. Many of these
problems are greatly reduced by having an instrumental beam that resolves the
primary anisotropies (FWHM << 10'). To reach the ultimate goal of an
inflationary energy scale of 3 \times 10^{15} GeV, polarization distortion
fluctuations must be controlled at the 10^{-2}-10^{-3} level and temperature
leakage to the 10^{-4}-10^{-3} level depending on effect. For example pointing
errors must be controlled to 1.5'' rms for arcminute scale beams or a percent
of the Gaussian beam width for larger beams; low spatial frequency differential
gain fluctuations or line cross-coupling must be eliminated at the level of
10^{-4} rms.Comment: 11 pages, 5 figures, submitted to PR
The Murchison Widefield Array: the Square Kilometre Array Precursor at low radio frequencies
The Murchison Widefield Array (MWA) is one of three Square Kilometre Array
Precursor telescopes and is located at the Murchison Radio-astronomy
Observatory in the Murchison Shire of the mid-west of Western Australia, a
location chosen for its extremely low levels of radio frequency interference.
The MWA operates at low radio frequencies, 80-300 MHz, with a processed
bandwidth of 30.72 MHz for both linear polarisations, and consists of 128
aperture arrays (known as tiles) distributed over a ~3 km diameter area. Novel
hybrid hardware/software correlation and a real-time imaging and calibration
systems comprise the MWA signal processing backend. In this paper the as-built
MWA is described both at a system and sub-system level, the expected
performance of the array is presented, and the science goals of the instrument
are summarised.Comment: Submitted to PASA. 11 figures, 2 table
From Data to Causes I: Building A General Cross-Lagged Panel Model (GCLM)
This is the first paper in a series of two that synthesizes, compares, and extends methods for causal inference with longitudinal panel data in a structural equation modeling (SEM) framework. Starting with a cross-lagged approach, this paper builds a general cross-lagged panel model (GCLM) with parameters to account for stable factors while increasing the range of dynamic processes that can be modeled. We illustrate the GCLM by examining the relationship between national income and subjective well-being (SWB), showing how to examine hypotheses about short-run (via Granger-Sims tests) versus long-run effects (via impulse responses). When controlling for stable factors, we find no short-run or long-run effects among these variables, showing national SWB to be relatively stable, whereas income is less so. Our second paper addresses the differences between the GCLM and other methods. Online Supplementary Materials offer an Excel file automating GCLM input for Mplus (with an example also for Lavaan in R) and analyses using additional data sets and all program input/output. We also offer an introductory GCLM presentation at https://youtu.be/tHnnaRNPbXs. We conclude with a discussion of issues surrounding causal inference
From Data to Causes II: Comparing Approaches to Panel Data Analysis
This article compares a general cross-lagged model (GCLM) to other panel data methods based on their coherence with a causal logic and pragmatic concerns regarding modeled dynamics and hypothesis testing. We examine three “static” models that do not incorporate temporal dynamics: random- and fixed-effects models that estimate contemporaneous relationships; and latent curve models. We then describe “dynamic” models that incorporate temporal dynamics in the form of lagged effects: cross-lagged models estimated in a structural equation model (SEM) or multilevel model (MLM) framework; Arellano-Bond dynamic panel data methods; and autoregressive latent trajectory models. We describe the implications of overlooking temporal dynamics in static models and show how even popular cross-lagged models fail to control for stable factors over time. We also show that Arellano-Bond and autoregressive latent trajectory models have various shortcomings. By contrasting these approaches, we clarify the benefits and drawbacks of common methods for modeling panel data, including the GCLM approach we propose. We conclude with a discussion of issues regarding causal inference, including difficulties in separating different types of time-invariant and time-varying effects over time
Effect of hydrodynamic interactions on the distribution of adhering Brownian particles
Brownian dynamics simulations were used to study the adhesion of hard spheres on a solid surface by taking the hydrodynamic interactions into account. Special attention was paid to analyze the configuration of the assembly of adsorbed particles. These results were compared to configurations generated by the extensively studied random sequential adsorption (RSA) model. In our case the adsorption probability for a particle is almost uniform over the entire available surfae. This surprising result shows that RSA provides a good approximation to generate adsorbed particle configurations
Radio Interferometric Calibration Using The SAGE Algorithm
The aim of the new generation of radio synthesis arrays such as LOFAR and SKA
is to achieve much higher sensitivity, resolution and frequency coverage than
what is available now, especially at low frequencies. To accomplish this goal,
the accuracy of the calibration techniques used is of considerable importance.
Moreover, since these telescopes produce huge amounts of data, speed of
convergence of calibration is a major bottleneck. The errors in calibration are
due to system noise (sky and instrumental) as well as the estimation errors
introduced by the calibration technique itself, which we call solver noise. We
define solver noise as the distance between the optimal solution (the true
value of the unknowns, uncorrupted by the system noise) and the solution
obtained by calibration. We present the Space Alternating Generalized
Expectation Maximization (SAGE) calibration technique, which is a modification
of the Expectation Maximization algorithm, and compare its performance with the
traditional Least Squares calibration based on the level of solver noise
introduced by each technique. For this purpose, we develop statistical methods
that use the calibrated solutions to estimate the level of solver noise. The
SAGE calibration algorithm yields very promising results both in terms of
accuracy and speed of convergence. The comparison approaches we adopt introduce
a new framework for assessing the performance of different calibration schemes.Comment: 12 pages, 10 figures, Accepted for publication in MNRA
Polarization leakage in epoch of reionization windows – I. Low Frequency Array observations of the 3C196 field
Detection of the 21-cm signal coming from the epoch of reionization (EoR) is challenging especially because, even after removing the foregrounds, the residual Stokes I maps contain leakage from polarized emission that can mimic the signal. Here, we discuss the instrumental polarization of LOFAR and present realistic simulations of the leakages between Stokes parameters. From the LOFAR observations of polarized emission in the 3C196 field, we have quantified the level of polarization leakage caused by the nominal model beam of LOFAR, and compared it with the EoR signal using power spectrum analysis. We found that at 134– 166 MHz, within the central 4◦ of the field the (Q,U)→I leakage power is lower than the EoR signal at k<0.3 Mpc−¹. The leakage was found to be localized around a Faraday depth of 0, and the rms of the leakage as a fraction of the rms of the polarized emission was shown to vary between 0.2–0.3%, both of which could be utilized in the removal of leakage. Moreover, we could define an ‘EoR window’ in terms of the polarization leakage in the cylindrical power spectrum above the PSF-induced wedge and below k∥∼0.5 Mpc−¹, and the window extended up to k∥∼1 Mpc−¹ at all k⊥ when 70% of the leakage had been removed. These LOFAR results show that even a modest polarimetric calibration over a field of view of ≲4∘ in the future arrays like SKA will ensure that the polarization leakage remains well below the expected EoR signal at the scales of 0.02–1 Mpc−¹
The Gaussian graphical model in cross-sectional and time-series data
We discuss the Gaussian graphical model (GGM; an undirected network of
partial correlation coefficients) and detail its utility as an exploratory data
analysis tool. The GGM shows which variables predict one-another, allows for
sparse modeling of covariance structures, and may highlight potential causal
relationships between observed variables. We describe the utility in 3 kinds of
psychological datasets: datasets in which consecutive cases are assumed
independent (e.g., cross-sectional data), temporally ordered datasets (e.g., n
= 1 time series), and a mixture of the 2 (e.g., n > 1 time series). In
time-series analysis, the GGM can be used to model the residual structure of a
vector-autoregression analysis (VAR), also termed graphical VAR. Two network
models can then be obtained: a temporal network and a contemporaneous network.
When analyzing data from multiple subjects, a GGM can also be formed on the
covariance structure of stationary means---the between-subjects network. We
discuss the interpretation of these models and propose estimation methods to
obtain these networks, which we implement in the R packages graphicalVAR and
mlVAR. The methods are showcased in two empirical examples, and simulation
studies on these methods are included in the supplementary materials.Comment: Accepted pending revision in Multivariate Behavioral Researc
First LOFAR observations at very low frequencies of cluster-scale non-thermal emission: the case of Abell 2256
Abell 2256 is one of the best known examples of a galaxy cluster hosting
large-scale diffuse radio emission that is unrelated to individual galaxies. It
contains both a giant radio halo and a relic, as well as a number of head-tail
sources and smaller diffuse steep-spectrum radio sources. The origin of radio
halos and relics is still being debated, but over the last years it has become
clear that the presence of these radio sources is closely related to galaxy
cluster merger events. Here we present the results from the first LOFAR Low
band antenna (LBA) observations of Abell 2256 between 18 and 67 MHz. To our
knowledge, the image presented in this paper at 63 MHz is the deepest ever
obtained at frequencies below 100 MHz in general. Both the radio halo and the
giant relic are detected in the image at 63 MHz, and the diffuse radio emission
remains visible at frequencies as low as 20 MHz. The observations confirm the
presence of a previously claimed ultra-steep spectrum source to the west of the
cluster center with a spectral index of -2.3 \pm 0.4 between 63 and 153 MHz.
The steep spectrum suggests that this source is an old part of a head-tail
radio source in the cluster. For the radio relic we find an integrated spectral
index of -0.81 \pm 0.03, after removing the flux contribution from the other
sources. This is relatively flat which could indicate that the efficiency of
particle acceleration at the shock substantially changed in the last \sim 0.1
Gyr due to an increase of the shock Mach number. In an alternative scenario,
particles are re-accelerated by some mechanism in the downstream region of the
shock, resulting in the relatively flat integrated radio spectrum. In the radio
halo region we find indications of low-frequency spectral steepening which may
suggest that relativistic particles are accelerated in a rather inhomogeneous
turbulent region.Comment: 13 pages, 13 figures, accepted for publication in A\&A on April 12,
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