# 数学代写|现代代数代写Modern Algebra代考|Modular determinant computation

#### Doug I. Jones

Lorem ipsum dolor sit amet, cons the all tetur adiscing elit

couryes™为您提供可以保分的包课服务

couryes-lab™ 为您的留学生涯保驾护航 在代写现代代数Modern Algebra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。我们的专家在代写现代代数Modern Algebra代写方面经验极为丰富，各种代写现代代数Modern Algebra相关的作业也就用不着说。

## 数学代写|现代代数代写Modern Algebra代考|Modular determinant computation

We will use our tools from Section 5.4 on an innocuous problem, namely computing the determinant $\operatorname{det} A \in \mathbb{Z}$ of an $n \times n$ matrix $A=\left(a_{i j}\right)_{1 \leq i, j \leq n} \in \mathbb{Z}^{n \times n}$.

We know from linear algebra (Section 25.5) that this problem can be solved by means of Gaussian elimination over $\mathbb{Q}$, which costs at most $2 n^3$ operations in $\mathbb{Q}$. Is this “polynomial time”? Of course $2 n^3$ is polynomial in the input size, but the number of word operations that the algorithm uses will also depend on the numerators and denominators of the intermediate results. How large can these grow? We consider the $k$ th stage during the elimination, and suppose for simplicity that $A$ is nonsingular and that no row or column permutations are necessary.

The table represents the matrix after $k-1$ pivoting stages, a “*” denotes an arbitrary rational number, and the upper diagonal entries are nonzero. The diagonal element $a_{k k}^{(k)} \neq 0$ is the new pivot element, and the entries of the $k$ th column below the pivot element must be made zero in the $k$ th stage by subtracting an appropriate multiple of the $k$ th row. The entries of the matrix for $k<i \leq n$ and $k \leq j \leq n$ change according to the formula
$$a_{i j}^{(k+1)}=a_{i j}^{(k)}-\frac{a_{i k}^{(k)}}{a_{k k}^{(k)}} a_{k j}^{(k)} .$$
The entries $a_{i j}^{(1)}=a_{i j}$ are the entries of the original matrix $A$. If $b_k$ is an upper bound for the absolute value of the numerators and denominators of all $a_{i j}^{(k)}$ for $1 \leq i, j \leq n$, so that in particular $\left|a_{i j}\right| \leq b_1$ for $1 \leq i, j \leq n$, then the formula (8) gives
$$b_k \leq 2 b_{k-1}^4 \leq 2^{1+4} b_{k-2}^{4^2} \leq \cdots \leq 2^{1+4+\cdots+4^{k-2}} b_1^{4^{k-1}}=2^{\left(4^{k-1}-1\right) / 3} b_1^{4^{k-1}}$$
which is an exponentially large upper bound in the input size $n^2 \lambda\left(b_1\right) \approx n^2 \log _{2^{64}} b_1$ (see Sections 2.1 and 6.1 concerning the length $\lambda$ ). At this point, we may wonder whether Gaussian elimination indeed uses polynomial time, if we count word operations. In fact, the length of the intermediate results and the number of word operations for Gaussian elimination over $\mathbb{Q}$ are polynomial in the input size, but the proof is nontrivial. We use an alternative approach to reach the same goal, a polynomial time algorithm for computing $\operatorname{det} A$. This illustrates modular computation in a simple case, and introduces some tools of more general interest.

## 数学代写|现代代数代写Modern Algebra代考|Hermite interpolation

Sections 5.6 through 5.11 are not essential for the rest of the text and may be skipped at first reading. In this section, we discuss an application of the Chinese Remainder Algorithm to Hermite interpolation. This is a generalization of polynomial interpolation where at each point not only the value of a function is prescribed, but also the values of some of the first few derivatives, or equivalently, an initial segment of the Taylor expansion.

If $R$ is an arbitrary (commutative) ring, $f \in R[x]$ has degree at most $n$, and $u \in R$, then the Taylor expansion of $\boldsymbol{f}$ around $\boldsymbol{u}$ is
$$f=f_n \cdot(x-u)^n+\cdots+f_1 \cdot(x-u)+f_0,$$
where $f_n, \ldots, f_0 \in R$ are the Taylor coefficients. If $u=0$, then this is just our usual way of writing polynomials. The Taylor coefficients are uniquely determined, and we have $f_n x^n+\cdots+f_1 x+f_0=f(x+u)$, which is the polynomial $f$ with $x$ substituted by $x+u$. (Formally, this defines $f_n, \ldots, f_0 \in R[u]$, when we consider $u$ as an indeterminate over $R$, and then (12) holds for this indeterminate and also for each value from $R$ substituted for it.) For $R=\mathbb{Z}, \mathbb{Q}, \mathbb{R}$, or $\mathbb{C}$, the $i$ th Taylor coefficient of $f$ is equal to $f^{(i)}(u) / i$ !, where $f^{(i)}$ is the $i$ th derivative of $f$ with respect to $x$, and (12) takes the more familiar form
$$f=\frac{f^{(n)}(u)}{n !} \cdot(x-u)^n+\cdots+\frac{f^{\prime \prime}(u)}{2} \cdot(x-u)^2+f^{\prime}(u) \cdot(x-u)+f(u) .$$
Thus for $f \in \mathbb{Z}[x]$ and $u \in \mathbb{Z}, f^{(i)}(u) / i$ ! is always an integer. For $e \leq n,(12)$ implies that
$$f \equiv f_{e-1} \cdot(x-u)^{e-1}+\cdots+f_1 \cdot(x-u)+f_0 \bmod (x-u)^e .$$

# 现代代数代考

## 数学代写|现代代数代写Modern Algebra代考|Modular determinant computation

$$a_{i j}^{(k+1)}=a_{i j}^{(k)}-\frac{a_{i k}^{(k)}}{a_{k k}^{(k)}} a_{k j}^{(k)} .$$

$$b_k \leq 2 b_{k-1}^4 \leq 2^{1+4} b_{k-2}^{4^2} \leq \cdots \leq 2^{1+4+\cdots+4^{k-2}} b_1^{4^{k-1}}=2^{\left(4^{k-1}-1\right) / 3} b_1^{4^{k-1}}$$

## 数学代写|现代代数代写Modern Algebra代考|Hermite interpolation

$$f=f_n \cdot(x-u)^n+\cdots+f_1 \cdot(x-u)+f_0,$$

$$f=\frac{f^{(n)}(u)}{n !} \cdot(x-u)^n+\cdots+\frac{f^{\prime \prime}(u)}{2} \cdot(x-u)^2+f^{\prime}(u) \cdot(x-u)+f(u) .$$

$$f \equiv f_{e-1} \cdot(x-u)^{e-1}+\cdots+f_1 \cdot(x-u)+f_0 \bmod (x-u)^e .$$

## 有限元方法代写

tatistics-lab作为专业的留学生服务机构，多年来已为美国、英国、加拿大、澳洲等留学热门地的学生提供专业的学术服务，包括但不限于Essay代写，Assignment代写，Dissertation代写，Report代写，小组作业代写，Proposal代写，Paper代写，Presentation代写，计算机作业代写，论文修改和润色，网课代做，exam代考等等。写作范围涵盖高中，本科，研究生等海外留学全阶段，辐射金融，经济学，会计学，审计学，管理学等全球99%专业科目。写作团队既有专业英语母语作者，也有海外名校硕博留学生，每位写作老师都拥有过硬的语言能力，专业的学科背景和学术写作经验。我们承诺100%原创，100%专业，100%准时，100%满意。

## 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。

Days
Hours
Minutes
Seconds

# 15% OFF

## On All Tickets

Don’t hesitate and buy tickets today – All tickets are at a special price until 15.08.2021. Hope to see you there :)