Engineering topics

Anderson, C. J.

Publications and source records attributed to Anderson, C. J..

3 records

NASA NTRS2019

The Experiment for Cryogenic Large-Aperture Intensity Mapping (EXCLAIM)

The EXperiment for Cryogenic Large-Aperture Intensity Mapping (EXCLAIM) is a cryogenic balloon-borne instrument which will survey galaxy and star formation history over cosmological time scales. Rather than identifying individual objects, EXCLAIM will be a pathfinder to demonstrate an intensity mapping approach, which measures the cumulative redshifted line emission. EXCLAIM will operate at 420-540 GHz with a spectral resolution R=512 to measure the integrated CO and [CII] in redshift windows spanning \exclaimz. CO and [CII] line emissions are key tracers of the gas phases in the interstellar medium involved in star-formation processes. EXCLAIM will shed light on questions such as why the star formation rate declines at z < 2, despite continued clustering of the dark matter. The instrument will employ an array of six superconducting integrated grating-analog spectrometers (Âµ-Spec) coupled to microwave kinetic inductance detectors (MKIDs). Here we present an overview of the EXCLAIM instrument design and status.

Instrumentation and Photography↗

NASA NTRS2019

Intensity Mapping in the Presence of Foregrounds and Correlated Continuum Emission

Intensity mapping has attracted significant interest as an approach to measuring the properties of the interstellar medium in typical galaxies at high redshift. Intensity mapping measures the statistics of surface brightness as a function of frequency, making it sensitive to not only all line emission of interest but also radiation from all other sources. Significant effort has gone into developing approaches that reject foreground contamination. Additionally, the target galaxies have multiple sources of emission that can complicate the interpretation of the line brightness.We describe the problem of jointly estimating correlated continuum emission and cleaning uncorrelated continuum emission, such as from the Milky Way. We apply these considerations to a cross-correlation of Planck data with BOSS quasars for a determination of [C II] for 2 < z < 3.2. Intensity mapping surveys with few bands have unique challenges for treating foregrounds and avoiding bias from correlated continuum emission. We show how a future intensity mapping survey with many bands can separate line from continuum emission in cross-correlation.

Switzer, E. R.↗

NASA NTRS2016

Erasing the Milky Way: New Cleaning Technique Applied to GBT Intensity Mapping Data

We present the first application of a new foreground removal pipeline to the current leading HI intensity mapping dataset, obtained by the Green Bank Telescope (GBT). We study the 15- and 1-h field data of the GBT observations previously presented in Masui et al. (2013) and Switzer et al. (2013), covering about 41 square degrees at 0.6 less than z is less than 1.0, for which cross-correlations may be measured with the galaxy distribution of the WiggleZ Dark Energy Survey. In the presented pipeline, we subtract the Galactic foreground continuum and the point source contamination using an independent component analysis technique (fastica), and develop a Fourier-based optimal estimator to compute the temperature power spectrum of the intensity maps and cross-correlation with the galaxy survey data. We show that fastica is a reliable tool to subtract diffuse and point-source emission through the non-Gaussian nature of their probability distributions. The temperature power spectra of the intensity maps is dominated by instrumental noise on small scales which fastica, as a conservative sub-traction technique of non-Gaussian signals, can not mitigate. However, we determine similar GBT-WiggleZ cross-correlation measurements to those obtained by the Singular Value Decomposition (SVD) method, and confirm that foreground subtraction with fastica is robust against 21cm signal loss, as seen by the converged amplitude of these cross-correlation measurements. We conclude that SVD and fastica are complementary methods to investigate the foregrounds and noise systematics present in intensity mapping datasets.

Wolz, L.↗