Subscribe to the gold package and get unlimited access to Shamra Academy
Register a new userMillimeterDL: Deep Learning Simulations of the Microwave Sky
62
0
0.0
(
0
)
Ask ChatGPT about the research
No Arabic abstract
We present 500 high-resolution, full-sky millimeter-wave Deep Learning (DL) simulations that include lensed CMB maps and correlated foreground components. We find that these MillimeterDL simulations can reproduce a wide range of non-Gaussian summary statistics matching the input training simulations, while only being optimized to match the power spectra. The procedure we develop in this work enables the capability to mass produce independent full-sky realizations from a single expensive full-sky simulation, when ordinarily the latter would not provide enough training data. We also circumvent a common limitation of high-resolution DL simulations that they be confined to small sky areas, often due to memory or GPU issues; we do this by developing a stitching procedure that can faithfully recover the high-order statistics of a full-sky map without discontinuities or repeated features. In addition, since our network takes as input a full-sky lensing convergence map, it can in principle take a full-sky lensing convergence map from any large-scale structure (LSS) simulation and generate the corresponding lensed CMB and correlated foreground components at millimeter wavelengths; this is especially useful in the current era of combining results from both CMB and LSS surveys, which require a common set of simulations.
rate research
Read More
We create realistic, full-sky, half-arcminute resolution simulations of the microwave sky matched to the most recent astrophysical observations. The primary purpose of these simulations is to test the data reduction pipeline for the Atacama Cosmology Telescope (ACT) experiment; however, we have widened the frequency coverage beyond the ACT bands to make these simulations applicable to other microwave background experiments. Some of the novel features of these simulations are that the radio and infrared galaxy populations are correlated with the galaxy cluster populations, the CMB is lensed by the dark matter structure in the simulation via a ray-tracing code, the contribution to the thermal and kinetic Sunyaev-Zeldovich (SZ) signals from galaxy clusters, groups, and the IGM has been included, and the gas prescription to model the SZ signals matches the most recent X-ray observations. Regarding the contamination of cluster SZ flux by radio galaxies, we find for 148 GHz (90 GHz) only 3% (4%) of halos have their SZ decrements contaminated at a level of 20% or more. We find the contamination levels higher for infrared galaxies. However, at 90 GHz, less than 20% of clusters with M_{200} > 2.5 x 10^{14} Msun and z<1.2 have their SZ decrements filled in at a level of 20% or more. At 148 GHz, less than 20% of clusters with M_{200} > 2.5 x 10^{14} Msun and z<0.8 have their SZ decrements filled in at a level of 50% or larger. Our models also suggest that a population of very high flux infrared galaxies, which are likely lensed sources, contribute most to the SZ contamination of very massive clusters at 90 and 148 GHz. These simulations are publicly available and should serve as a useful tool for microwave surveys to cross-check SZ cluster detection, power spectrum, and cross-correlation analyses.
We describe and compare two types of microwave sky simulations which are good for small angular scales. The first type uses expansions in spherical harmonics, and the second one is based on plane waves and the Fast Fourier Transform. The angular power spectrum is extracted from maps corresponding to both types of simulations, and the resulting spectra are appropriately compared. In this way, the features and usefulness of Fourier simulations are pointed out. For $ell geq 100$, all the simulations lead to similar accuracies; however, the CPU cost of Fourier simulations is $sim 10$ times smaller than that for spherical harmonic simulations. For $ell leq 100$, the simulations based on spherical harmonics seem to be preferable.
In order to extract cosmological information from observations of the millimeter and submillimeter sky, foreground components must first be removed to produce an estimate of the cosmic microwave background (CMB). We developed a machine-learning approach for doing so for full-sky temperature maps of the millimeter and submillimeter sky. We constructed a Bayesian spherical convolutional neural network architecture to produce a model that captures both spectral and morphological aspects of the foregrounds. Additionally, the model outputs a per-pixel error estimate that incorporates both statistical and model uncertainties. The model was then trained using simulations that incorporated knowledge of these foreground components that was available at the time of the launch of the Planck satellite. On simulated maps, the CMB is recovered with a mean absolute difference of $<4mu$K over the full sky after masking map pixels with a predicted standard error of $>50mu$K; the angular power spectrum is also accurately recovered. Once validated with the simulations, this model was applied to Planck temperature observations from its 70GHz through 857GHz channels to produce a foreground-cleaned CMB map at a Healpix map resolution of NSIDE=512. Furthermore, we demonstrate the utility of the technique for evaluating how well different simulations match observations, particularly in regard to the modeling of thermal dust.
We present a numerical code to simulate maps of Galactic emission in intensity and polarization at microwave frequencies, aiding in the design of Cosmic Microwave Background experiments. This Python code builds on existing efforts to simulate the sky by providing an easy-to-use interface and is based on publicly available data from the WMAP and Planck satellite missions. We simulate synchrotron, thermal dust, free-free, and anomalous microwave emission over the whole sky, in addition to the Cosmic Microwave Background, and include a set of alternative prescriptions for the frequency dependence of each component that are consistent with current data. We also present a prescription for adding small-scale realizations of these components at resolutions greater than current all-sky measurements. The code is available at https://github.com/bthorne93/PySM_public.
The ESA Planck satellite, launched on May 14th, 2009, is the third generation space mission dedicated to the measurement of the Cosmic Microwave Background (CMB), the first light in the Universe. Planck observes the full sky in nine frequency bands from 30 to 857 GHz and is designed to measure the CMB anisotropies with an unprecedented combination of sensitivity, angular resolution and control of systematic effects. In this presentation we summarise the Planck instruments performance and discuss the main scientific results obtained after one year of operations in the fields of galactic and extragalactic astrophysics.
Log in to be able to interact and post comments
comments
Fetching comments
Sign in to be able to follow your search criteria
