A Millimeter-Wave Galactic Plane Survey With The BICEP Polarimeter

In addition to its potential to probe the Inflationary cosmological paradigm, millimeter-wave polarimetry is a powerful tool for studying the Milky Way galaxy's composition and magnetic field structure. Towards this end, presented here are Stokes I, Q, and U maps of the Galactic plane from the millimeter-wave polarimeter BICEP covering the Galactic longitude range 260 - 340 degrees in three atmospheric transmission windows centered on 100, 150, and 220 GHz. The maps sample an optical depth 1 < AV < 30, and are consistent with previous characterizations of the Galactic millimeter-wave frequency spectrum and the large-scale magnetic field structure permeating the interstellar medium. Polarized emission is detected over the entire region within two degrees of the Galactic plane and indicates that the large-scale magnetic field is oriented parallel to the plane of the Galaxy. An observed trend of decreasing polarization fraction with increasing total intensity rules out the simplest model of a constant Galactic magnetic field throughout the Galaxy. Including WMAP data in the analysis, the degree-scale frequency spectrum of Galactic polarization fraction is plotted between 23 and 220 GHz for the first time. A generally increasing trend of polarization fraction with electromagnetic frequency is found, which varies from 0.5%-1.5%at frequencies below 50 GHz to 2.5%-3.5%above 90 GHz. The BICEP and WMAP data are fit to a two-component (synchrotron and dust) model showing that the higher frequency BICEP data are necessary to tightly constrain the amplitude and spectral index of Galactic dust. Furthermore, the dust amplitude predicted by this two-component fit is consistent with model predictions of dust emission in the BICEP bands

A Millimeter-wave Galactic Plane Survey with the BICEP Polarimeter

In order to study inflationary cosmology and the Milky Way Galaxy's composition and magnetic field structure, Stokes I, Q, and U maps of the Galactic plane covering the Galactic longitude range 260° < ℓ < 340° in three atmospheric transmission windows centered on 100, 150, and 220 GHz are presented. The maps sample an optical depth 1 ≾ AV ≾ 30, and are consistent with previous characterizations of the Galactic millimeter-wave frequency spectrum and the large-scale magnetic field structure permeating the interstellar medium. The polarization angles in all three bands are generally perpendicular to those measured by starlight polarimetry as expected and show changes in the structure of the Galactic magnetic field on the scale of 60°. The frequency spectrum of degree-scale Galactic emission is plotted between 23 and 220 GHz (including WMAP data) and is fit to a two-component (synchrotron and dust) model showing that the higher frequency BICEP data are necessary to tightly constrain the amplitude and spectral index of Galactic dust. Polarized emission is detected over the entire region within two degrees of the Galactic plane, indicating the large-scale magnetic field is oriented parallel to the plane of the Galaxy. A trend of decreasing polarization fraction with increasing total intensity is observed, ruling out the simplest model of a constant Galactic magnetic field orientation along the line of sight in the Galactic plane. A generally increasing trend of polarization fraction with electromagnetic frequency is found, varying from 0.5%-1.5% at frequencies below 50 GHz to 2.5%-3.5% above 90 GHz. The effort to extend the capabilities of BICEP by installing 220 GHz band hardware is described along with analysis of the new band

Systematic approach to nonlinear filtering associated with aggregation operators. Part 1. SISO-filters

There are various methods to help restore an image from noisy distortions. Each technique has its advantages and disadvantages. Selecting the appropriate method plays a major role in getting the desired image. Noise removal or noise reduction can be done on an image by linear or nonlinear filtering. The more popular linear technique is based on average (on mean) linear operators. Denoising via linear filters normally does not perform satisfactorily since both noise and edges contain high frequencies. Therefore, any practical denoising model has to be nonlinear. In this work, we introduce and analyze a new class of nonlinear SISO-filters that have their roots in aggregation operator theory. We show that a large body of non-linear filters proposed to date constitute a proper subset of aggregation filters. (C) 2017 The Authors. Published by Elsevier Ltd.This work was supported by grants the RFBR No. 17-07-00886 and by Ural State Forest Engineering's Center of Excellence in "Quantum and Classical Information Technologies for Remote Sensing Systems"

Review of Unbiased FIR Filters, Smoothers, and Predictors for Polynomial Signals

Extracting an estimate of a slowly varying signal corrupted by noise is a common task. Examples can be found in industrial, scientific and biomedical instrumentation. Depending on the nature of the application the signal estimate is allowed to be a delayed estimate of the original signal or, in the other extreme, no delay is tolerated. These cases are commonly referred to as filtering, prediction, and smoothing depending on the amount of advance or lag between the input data set and the output data set. In this review paper we provide a comprehensive set of design and analysis tools for designing unbiased FIR filters, predictors, and smoothers for slowly varying signals, i.e. signals that can be modeled by low order polynomials. Explicit expressions of parameters needed in practical implementations are given. Real life examples are provided including cases where the method is extended to signals that are piecewise slowly varying. A critical view on recursive implementations of the algorithms is provided

High Precision Photometry for K2 Campaign 1

The two reaction wheel K2 mission promises and has delivered new discoveries in the stellar and exoplanet fields. However, due to the loss of accurate pointing, it also brings new challenges for the data reduction processes. In this paper, we describe a new reduction pipeline for extracting high precision photometry from the K2 dataset, and present public light curves for the K2 Campaign 1 target pixel dataset. Key to our reduction is the derivation of global astrometric solutions from the target stamps, from which accurate centroids are passed on for high precision photometry extraction. We extract target light curves for sources from a combined UCAC4 and EPIC catalogue -- this includes not only primary targets of the K2 campaign 1, but also any other stars that happen to fall on the pixel stamps. We provide the raw light curves, and the products of various detrending processes aimed at removing different types of systematics. Our astrometric solutions achieve a median residual of ~ 0.13". For bright stars, our best 6.5 hour precision for raw light curves is ~20 parts per million (ppm). For our detrended light curves, the best 6.5 hour precisions achieved is ~15 ppm. We show that our detrended light curves have fewer systematic effects (or trends, or red-noise) than light curves produced by other groups from the same observations. Example light curves of transiting planets and a Cepheid variable candidate, are also presented. We make all light curves public, including the raw and de-trended photometry, at http://k2.hatsurveys.org.Comment: submitted to MNRA

LSDCat: Detection and cataloguing of emission-line sources in integral-field spectroscopy datacubes

We present a robust, efficient, and user-friendly algorithm for detecting faint emission-line sources in large integral-field spectroscopic datacubes together with the public release of the software package LSDCat (Line Source Detection and Cataloguing). LSDCat uses a 3-dimensional matched filter approach, combined with thresholding in signal-to-noise, to build a catalogue of individual line detections. In a second pass, the detected lines are grouped into distinct objects, and positions, spatial extents, and fluxes of the detected lines are determined. LSDCat requires only a small number of input parameters, and we provide guidelines for choosing appropriate values. The software is coded in Python and capable to process very large datacubes in a short time. We verify the implementation with a source insertion and recovery experiment utilising a real datacube taken with the MUSE instrument at the ESO Very Large Telescope.Comment: 14 pages. Accepted for publication in Astronomy & Astrophysics. The LSDCat software is available at https://bitbucket.org/Knusper2000/lsdcat, v2 corrected typos and language editin