### 英国补考|宇宙学代写cosmology代考|PHYSICS 1002

statistics-lab™ 为您的留学生涯保驾护航 在代写宇宙学cosmology方面已经树立了自己的口碑, 保证靠谱, 高质且原创的统计Statistics代写服务。我们的专家在代写宇宙学cosmology代写方面经验极为丰富，各种代写宇宙学cosmology相关的作业也就用不着说。

• Statistical Inference 统计推断
• Statistical Computing 统计计算
• (Generalized) Linear Models 广义线性模型
• Statistical Machine Learning 统计机器学习
• Longitudinal Data Analysis 纵向数据分析
• Foundations of Data Science 数据科学基础

## 英国补考|宇宙学代写cosmology代考|Growth of Structure

The density fluctuations in the early universe eventually grew into all of the structures we see around us. On large scales, the gravitational clustering of matter can be described analytically, while, on small scales, the process becomes highly nonlinear and can only be captured by numerical simulations. The dark matter formed a web-like structure with high-density nodes connected by filaments. The baryonic gas collected in the regions of high dark matter density where it collapsed into stars which then congregated into galaxies.

The first stars – called population III stars ${ }^{1}$ – formed when the universe was about 100 million years old. Computer simulations suggest that these stars were very massive, about a few hundred times more massive than the Sun. They were also very luminous and, hence, burned up their fuel rapidly. Although the first stars were short-lived, their impact on the universe was significant. They emitted ultraviolet light which heated and ionized the surrounding gas. The dynamics of this process of reionization are still not completely known and are actively investigated thorough numerical simulations. The first stars also may have provided the seeds for the growth of supermassive black holes which are found at the centers of most galaxies. And, finally, they created the first heavy elements in their interiors which were dispersed throughout the cosmos when the stars exploded. Enriched with these heavy elements, the baryonic gas cooled more efficiently, allowing smaller and more long-lived stars to be formed.

The first galaxies started to appear nearly a billion years after the Big Bang. Over time, these galaxies formed clusters and superclusters, a process which is still ongoing today. In the future, however, the growth of structure will stop as dark energy starts to dominate the universe. The details of galaxy formation are intricate and still an active area of research. In this book, we will be more interested in galaxies as tracers of the underlying distribution of dark matter, which in turn is determined by the seed fluctuations in the early universe. This distribution isn’t random but has interesting spatial correlations which have been measured in large galaxy surveys.

## 英国补考|宇宙学代写cosmology代考|Cosmic Palaeontology

Cosmology is famously an observational rather than an experimental science. No experimentalists were present in the early universe, and the birth and subsequent evolution of the universe cannot be repeated. Instead, we can only measure the spatial correlations between cosmological structures at late times. A central challenge of modern cosmology is to construct a consistent “history” of the universe that explains these correlations. This cosmological history is a narrative, a story we tell to give a rational accounting of the patterns that we see in the cosmological correlations.

This parallels the way paleontologists infer the history of the Earth by studying the pattern of fossilized bones in the ground today. Like astronomical objects, these fossils are not randomly spread throughout space, but display interesting correlations which we try to explain by invoking past events. In much the same way, cosmologists study the pattern of cosmological structures observed today to infer the history of the early universe.

A remarkable feature of the observed correlations in the CMB is that they span scales that are larger than the distance travelled by light between the beginning of the hot Big Bang and the time when the CMB was created. This is in conflict with causality, unless the correlations were generated before the hot Big Bang. Indeed, there is now growing evidence that the hot Big Bang was not the beginning of time, but that the primordial density fluctuations were produced during an earlier period of accelerated expansion called inflation [14-16]. Small quantum fluctuations during inflation were amplified by the rapid expansion of the space and became the seeds for the large-scale structure of the universe $[17-21]$.

If inflation really occurred, it was a rather dramatic event in the history of the universe. In just a billionth of a trillionth of a trillionth of a second, the universe doubled in size about 80 times. A region of space the size of a mosquito got stretched to the size of an entire galaxy. The entire observable universe then originated from a microscopic, causally-connected region of space. The correlations observed in the afterglow of the Big Bang were inherited from the correlations of the quantum fluctuations during inflation. While this picture provides an elegant explanation for the initial conditions of the primordial universe, it must be emphasized that inflation is not yet a fact – at the same level that, for example, $\mathrm{BBN}$ is a fact. The theoretical framework for inflation, however, is sufficiently well developed to justify including it in an introductory textbook on standard cosmology. Moreover, many new observations of the primordial correlations are being carried out-or are in the planning stages – that will subject the inflationary paradigm to further tests.

## 有限元方法代写

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## MATLAB代写

MATLAB 是一种用于技术计算的高性能语言。它将计算、可视化和编程集成在一个易于使用的环境中，其中问题和解决方案以熟悉的数学符号表示。典型用途包括：数学和计算算法开发建模、仿真和原型制作数据分析、探索和可视化科学和工程图形应用程序开发，包括图形用户界面构建MATLAB 是一个交互式系统，其基本数据元素是一个不需要维度的数组。这使您可以解决许多技术计算问题，尤其是那些具有矩阵和向量公式的问题，而只需用 C 或 Fortran 等标量非交互式语言编写程序所需的时间的一小部分。MATLAB 名称代表矩阵实验室。MATLAB 最初的编写目的是提供对由 LINPACK 和 EISPACK 项目开发的矩阵软件的轻松访问，这两个项目共同代表了矩阵计算软件的最新技术。MATLAB 经过多年的发展，得到了许多用户的投入。在大学环境中，它是数学、工程和科学入门和高级课程的标准教学工具。在工业领域，MATLAB 是高效研究、开发和分析的首选工具。MATLAB 具有一系列称为工具箱的特定于应用程序的解决方案。对于大多数 MATLAB 用户来说非常重要，工具箱允许您学习应用专业技术。工具箱是 MATLAB 函数（M 文件）的综合集合，可扩展 MATLAB 环境以解决特定类别的问题。可用工具箱的领域包括信号处理、控制系统、神经网络、模糊逻辑、小波、仿真等。