Simulating Calibration and Beam Systematics for a Future CMB Space Mission with the TOAST Package

ForSE+：基于生成对抗网络以随机方式模拟3角分分辨率的非高斯CMB前景

ForSE+: Simulating non-Gaussian CMB foregrounds at 3 arcminutes in a stochastic way based on a generative adversarial network

本研究提出基于GAN的Python包ForSE+，作为ForSE的扩展，可随机生成3角分分辨率的非银河系热尘埃前景小尺度图，其统计特性符合观测结果，将助力CMB相关信号测量研究。

Simulating instrumental systematics of Cosmic Microwave Background experiments with s4cmb

The observation of cosmic microwave background (CMB) anisotropies is one of the key probes of physical cosmology. The weak nature of this signal has driven the construction of increasingly complex and sensitive experiments observing the sky at multiple frequencies with thousands of polarization sensitive detectors. Given the high sensitivity of such experiments, instrumental systematic effects can become the limiting factor towards the full scientific exploitation of their data. In this paper we present s4cmb (Systematics for CMB), a Python package designed to simulate raw data streams in time…

利用三维快速傅里叶变换模拟部分天空宇宙微波背景图

Simulating Partial Sky Cosmic Microwave Background Maps with 3D Fast Fourier Transforms

本文提出一种利用三维快速傅里叶变换在盒子中模拟CMB图并采样到部分天球的方法，证明其比全天球谐变换模拟更高效，适用于CMB S4等中等天区实验，并可扩展至偏振模拟。

ForSE: a GAN based algorithm for extending CMB foreground models to sub-degree angular scales

We present ForSE (Foreground Scale Extender), a novel Python package which aims at overcoming the current limitations in the simulation of diffuse Galactic radiation, in the context of Cosmic Microwave Background experiments (CMB). ForSE exploits the ability of generative adversarial neural networks (GANs) to learn and reproduce complex features present in a set of images, with the goal of simulating realistic and non-Gaussian foreground radiation at sub-degree angular scales. This is of great importance in order to estimate the foreground contamination to lensing reconstruction, de-lensing an…

大尺度宇宙微波背景数据的准确高效似然建模

Accurate and efficient likelihood modeling for large-scale CMB data

本文提出了一种基于Hamimeche-Lewis形式的新型方法，用于大尺度CMB数据的准确高效似然建模，通过边缘化自谱以减少偏差，并在多场设置中验证了其在准确性与计算效率上的优势。

Optimal analysis of the CMB trispectrum

We develop a general framework for data analysis and phenomenology of the CMB four-point function or trispectrum. To lowest order in the derivative expansion, the inflationary action admits three quartic operators consistent with symmetry: $\dotσ^4$, $\dotσ^2 (\partialσ^2)$, and $(\partialσ)^4$. In single field inflation, only the first of these operators can be the leading non-Gaussian signal. A Fisher matrix analysis shows that there is one near-degeneracy among the three CMB trispectra, so we parameterize the trispectrum with two coefficients $g_{NL}^{\dotσ^4}$ and $g_{NL}^{(\partialσ)^4}$,…