The cosmic microwave background radiation defines a preferred cosmic rest frame, and inflationary cosmological theories predict that the microwave background temperature fluctuations should be statistically isotropic in this rest frame. For observers moving with respect to the rest frame, the temperature fluctuations will no longer be isotropic, due to the preferred direction of motion. The most prominent effect is a dipole temperature variation, which has long been observed with an amplitude of a part in a thousand of the mean temperature. An observer's velocity with respect to the rest frame will also induce changes in the angular correlation function and creation of non-zero off-diagonal correlations between multipole moments. We calculate both of these effects, which are part-in-a-thousand corrections to the rest frame power spectrum and correlation function. Both should be detectable in future full-sky microwave maps from the Planck satellite. These signals will constrain cosmological models in which the cosmic dipole arises partly from large-scale isocurvature perturbations, as suggested by recent observations.
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…
We present a new model of the microwave sky in polarization that can be used to simulate data from CMB polarization experiments. We exploit the most recent results from the Planck satellite to provide an accurate description of the diffuse polarized foreground synchrotron and thermal dust emission. Our model can include the two mentioned foregrounds, and also a constructed template of Anomalous Microwave Emission (AME). Several options for the frequency dependence of the foregrounds can be easily selected, to reflect our uncertainties and to test the impact of different assumptions. Small angu…
We re-analyse the cosmic microwave background (CMB) Cold Spot (CS) anomaly with particular focus on understanding the bias a mask (contaminated by Galactic and point sources) may introduce. We measure the coldest spot, found by applying the Spherical Mexican Hat Wavelet transform on 100 000 cut-sky (masked) and full-sky CMB simulated maps. The CS itself is barely affected by the mask; we estimate a 94 per cent probability that the CS is the full-sky temperature minimum. However, approximately 48 per cent (masked fraction of the mask) of full-sky minima are obscured by the mask. Since the obser…
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 statistic…
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…
Explaining Neural Networks on the Sky: Machine Learning Interpretability for Cosmic Microwave Background Maps
Instituto de Física Teórica UAM-CSIC（马德里自治大学-西班牙国家科研中心理论物理研究所）；Universidad Autónoma de Madrid（马德里自治大学）；Leiden Observatory, Leiden University（莱顿大学莱顿天文台）
In CMB science, the simplest idea to remove a contaminated sky region is to multiply the sky map with a mask that is 0 for the contaminated region and 1 elsewhere, which is also called a top-hat masking. Although it is easy to use, such top-hat masking is known to suffer from various leakage problems. Therefore, we want to extend the top-hat masking to a series of semi-analytic functions called the P-filters. Most importantly, the P-filters can seamlessly realize the core idea of masking in CMB science, and, meanwhile, guarantee continuity up to the first derivative everywhere. The P-filters c…
Large-Angle Correlations in the Cosmic Microwave Background
Copi et al（2009）最近提出，CMB温度场缺乏大的角相关性，这为标准的、统计各向同性的、暴胀的λ CDM宇宙学提供了强有力的证据。我们比较各种估计的温度关联函数，显示他们如何依赖于统计各向同性的假设，以及他们如何执行WMAP 5年ILC地图，并没有天空切割。我们表明，低多极谐波，确定温度关联函数的大规模功能，可以准确地重建，独立于任何假设有关的统计各向同性，从数据以外的天空削减。由重建结果计算的温度关联函数与由全天空计算的温度关联函数符合得很好。贝叶斯分析的大规模的相关性表明，数据不能排除标准的LambdaCDM模型。我们讨论了我们的结论和Copi等人之间的差异。
We introduce a publicly available full-sky beam convolution code library intended to inform the design of future cosmic microwave background (CMB) instruments and help current experiments probe potential systematic effects. The code can be used to assess the impact of optical systematics on all stages of data reduction for a realistic experiment, including analyses beyond power spectrum estimation, by generating signal timelines that may serve as input to full analysis pipelines. The design and mathematical framework of the Python code is discussed along with a few simple benchmarking results.…
Microwave telescopes require an ever-increasing control of experimental systematics in their quest to measure the Cosmic Microwave Background (CMB) to exquisite levels of precision. One important systematic for ground and balloon-borne experiments is ground pickup, where beam sidelobes detect the thermal emission of the much warmer ground while the main beam is scanning the sky. This generates scan-synchronous noise in experiment timestreams, which is difficult to filter out without also deleting some of the signal from the sky. Therefore, efficient modelling of pickup can help guide the desig…
All-sky modeling of Galactic emission at radio and microwave frequencies
The University of Manchester（曼彻斯特大学）；Instituto de Astrofísica de Canarias（加那利天体物理研究所）；Universidad de La Laguna（拉古纳大学）；University of Oslo（奥斯陆大学）；University of Cambridge（剑桥大学）；University of Oxford（牛津大学）
In this research, we present an alternative methodology to search for ring-like structures in the sky with unusually large temperature gradients, namely Hawking points (HP), in the Cosmic Microwave Background (CMB), which are possible observational effects associated with Conformal Cyclic Cosmology (CCC). To assess the performance of our method, we constructed an artificial data set of HP, according to CCC, and we were able to retrieve $95 \%$ of ring-like anomalies from it. Furthermore, we scanned the \textit{Planck} CMB sky map and compared it to simulations according to $ΛCDM$, where we app…
We present 108 full-sky gravitational lensing simulation data sets generated by performing multiple-lens plane ray-tracing through high-resolution cosmological $N$-body simulations. The data sets include full-sky convergence and shear maps from redshifts $z=0.05$ to $5.3$ at intervals of $150 \, h^{-1}{\rm Mpc}$ comoving radial distance (corresponding to a redshift interval of $Δz \simeq 0.05$ at the nearby universe), enabling the construction of a mock shear catalog for an arbitrary source distribution up to $z=5.3$. The dark matter halos are identified from the same $N$-body simulations with…
Temperature and polarization variations across the microwave sky include the fingerprints of quantum fluctuations in the early universe. They may soon reveal physics at unprecedented energy scales.
Component separation is the process with which emission sources in astrophysical maps are generally extracted by taking multi-frequency information into account. It is crucial to develop more reliable methods for component separation for future CMB experiments. We aim to develop a new method based on fully convolutional neural networks called the Cosmic microwave background Extraction Neural Network (CENN) in order to extract the CMB signal in total intensity. The frequencies used are the Planck channels 143, 217 and 353 GHz. We validate the network at all sky, and at three latitude intervals:…
We present the DustFilaments code, a full sky model for the millimeter Galactic emission of thermal dust. Our model, composed of millions of filaments that are imperfectly aligned with the magnetic field, is able to reproduce the main features of the dust angular power spectra at 353 GHz as measured by the Planck mission. Our model is made up of a population of filaments with sizes following a Pareto distribution $\propto L_a^{-2.445}$, with an axis ratio between short and long semi-axes $ε\sim 0.16$ and an angle of magnetic field misalignment with a dispersion RMS($θ_{LH}$)$=10$ degree. On la…
Detection of new point-sources in WMAP Cosmic Microwave Background (CMB) maps at high Galactic latitude. A new technique to extract point sources from CMB maps
We study different variants of the Gibbs sampler algorithm from the perspective of their applicability to the estimation of power spectra of the cosmic microwave background (CMB) anisotropies. These include approaches studied earlier in the CMB literature as well as new ones which are proposed in this work. We demonstrate all these variants on full and cut sky simulations and compare their performance, assessing both their computational and statistical efficiency. For this we employ a consistent comparison metric, an effective sample size (ESS) per second, commonly used in this context in the …
