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NCSU北卡羅萊那州立大學| MA 405 Linear Algebra exam代写

MA 405Introduction to Linear AlgebraSection: 601

Course Description

This course offers a rigorous treatment of linear algebra, including systems of linear equations, matrices, determinants, abstract vector spaces, bases, linear independence, spanning sets, linear transformations, eigenvalues and eigenvectors, similarity, inner product spaces, orthogonality and orthogonal bases, factorization of matrices. Compared with MA 305 Introductory Linear Algebra, more emphasis is placed on theory and proofs. MA 225 is recommended as a prerequisite. Credit is not allowed for both MA 305 and MA 405

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NCSU北卡羅萊那州立大學| MA 405 Linear Algebra exam代写

2210Q 应用线性代数Applied Linear Algebra题目解答

问题 1.

A matrix $A \in M_{2}(\mathbf{C})$ is invertible if and only if $\operatorname{det} A \neq 0$. If this is the case, then
$$
A^{-1}=\frac{1}{\operatorname{det} A}\left(\operatorname{Tr}(A) \cdot I_{2}-A\right)
$$

证明 .

Suppose that $A$ is invertible. Then taking the determinant in the equality $A \cdot A^{-1}=I_{2}$ we obtain
$$
\operatorname{det} A \cdot \operatorname{det} A^{-1}=\operatorname{det} I_{2}=1
$$
thus $\operatorname{det} A \neq 0$.
Conversely, suppose that $\operatorname{det} A \neq 0$ and define
$$
B=\frac{1}{\operatorname{det} A}\left(\operatorname{Tr}(A) \cdot I_{2}-A\right)
$$
Then using the Cayley-Hamilton theorem we obtain
$$
A B=\frac{1}{\operatorname{det} A}\left(\operatorname{Tr}(A) \cdot A-A^{2}\right)=\frac{1}{\operatorname{det} A} \cdot \operatorname{det} A I_{2}=I_{2}
$$
and similarly $B A=I_{2}$. Thus $A$ is invertible and $A^{-1}=B$.

问题 2.

Let $A, B \in M_{2}(\mathbf{C})$ be two matrices such that $A B=I_{2}$. Then $A$ is invertible and $B=A^{-1}$. In particular, we have $B A=I_{2}$.

证明 .

Since $A B=I_{2}$, we have $\operatorname{det} A \cdot \operatorname{det} B=\operatorname{det}(A B)=1$, thus $\operatorname{det} A \neq 0$. The previous theorem shows that $A$ is invertible. Multiplying the equality $A B=I_{2}$ by $A^{-1}$ on the left, we obtain $B=A^{-1}$. Finally, $B A=A^{-1} A=I_{2}$.

问题 3.

证明 .

By the previous theorem, we can find two nonzero vectors $X_{1}=\left[\begin{array}{l}x_{11} \ x_{21}\end{array}\right]$ and $X_{2}=\left[\begin{array}{l}x_{12} \ x_{22}\end{array}\right]$ such that $A X_{i}=\lambda_{i} X_{i}$.

Consider the matrix $P=\left[\begin{array}{ll}x_{11} & x_{12} \ x_{21} & x_{22}\end{array}\right]$ whose columns are $X_{1}, X_{2}$. A simple computation shows that the columns of $A P$ are $\lambda_{1} X_{1}$ and $\lambda_{2} X_{2}$, which are the columns of $P\left[\begin{array}{cc}\lambda_{1} & 0 \ 0 & \lambda_{2}\end{array}\right]$, thus $A P=P\left[\begin{array}{cc}\lambda_{1} & 0 \ 0 & \lambda_{2}\end{array}\right]$. It remains to see that if $\lambda_{1} \neq \lambda_{2}$, then $P$ is invertible (we haven’t used so far the hypothesis $\lambda_{1} \neq \lambda_{2}$ ).

Suppose that det $P=0$, thus $x_{11} x_{22}=x_{21} x_{12}$. This easily implies that the columns of $P$ are proportional, say the second column $X_{2}$ is $\alpha$ times the first column, $X_{1}$. Thus $X_{2}=\alpha X_{1}$. Then
$$
\lambda_{2} X_{2}=A X_{2}=\alpha A X_{1}=\alpha \lambda_{1} X_{1}=\lambda_{1} X_{2},
$$
forcing $\left(\lambda_{1}-\lambda_{2}\right) X_{2}=0$. This is impossible as both $\lambda_{1}-\lambda_{2}$ and $X_{2}$ are nonzero. The problem is solved.

问题 4.

Solve in $M_{2}(\mathbf{C})$ the following equations
(a) $A^{2}=O_{2}$.
(b) $A^{2}=I_{2}$.
(c) $A^{2}=A$.

证明 .

(a) Let $A$ be a solution of the problem. Then $\operatorname{det} A=0$ and the CayleyHamilton relation reduces to $\operatorname{Tr}(A) A=0$. Taking the trace yields $\operatorname{Tr}(A)^{2}=0$, thus $\operatorname{Tr}(A)=0$. Conversely, if $\operatorname{det} A=0$ and $\operatorname{Tr}(A)=0$, then the CayleyHamilton theorem shows that $A^{2}=O_{2}$. Thus the solutions of the problem are the matrices
$A=\left[\begin{array}{cc}a & b \ c & -a\end{array}\right], \quad$ with $\quad a, b, c \in \mathbf{C} \quad$ and $\quad a^{2}+b c=0 .$
(b) We must have det $A=\pm 1$ and, by the Cayley-Hamilton theorem, $I_{2}-$ $\operatorname{Tr}(A) A+\operatorname{det} A I_{2}=O_{2}$. If det $A=1$, then $\operatorname{Tr}(A) A=2 I_{2}$ and taking the trace yields $\operatorname{Tr}(A)^{2}=4$, thus $\operatorname{Tr}(A)=\pm 2$. This yields two solutions, $A=\pm I_{2}$. Suppose that $\operatorname{det} A=-1$. Then $\operatorname{Tr}(A) A=O_{2}$ and taking the trace gives $\operatorname{Tr}(A)=0$. Conversely, any matrix $A$ with $\operatorname{Tr}(A)=0$ and $\operatorname{det} A=-1$ is a solution of the problem (again by Cayley-Hamilton). Thus the solutions of the equation are
$\pm I_{2} \quad$ and $\quad A=\left[\begin{array}{cc}a & b \ c & -a\end{array}\right], \quad a, b, c \in \mathbf{C}, \quad a^{2}+b c=1 .$
(c) If $\operatorname{det} A \neq 0$, then multiplying by $A^{-1}$ yields $A=I_{2}$. So suppose that $\operatorname{det} A=$ 0 . The Cayley-Hamilton theorem yields $A-\operatorname{Tr}(A) A=O_{2}$. If $\operatorname{Tr}(A) \neq 1$, this forces $A=O_{2}$, which is a solution of the problem. Thus if $A \neq O_{2}, I_{2}$, then det $A=0$ and $\operatorname{Tr}(A)=1$. Conversely, all such matrices are solutions of the problem (again by Cayley-Hamilton). Thus the solutions of the problem are
$O_{2}, \quad I_{2} \quad$ and $\quad A=\left[\begin{array}{cc}a & b \ c & 1-a\end{array}\right], \quad a, b, c \in \mathbf{C}, \quad a^{2}+b c=a .$

线性代数和矩阵导论MA 405. Introduction to Linear Algebra and Matrices


Instructor: V. Summers | SAS 4121 | vwsummer@ncsu.edu |
Moodle page: http://moodle.wolfware.ncsu.edu
Lectures will be held MWF 9:35 am – 10:25 am in SAS 2235.
Communication: Office hours will be held Mondays 10:30 – 12:30 in SAS 4121.
Moodle forums will be used for most communications in this course. You are encouraged to discuss concepts and
homework in the forums with your fellow students; the discussions will be monitored by Mr. Summers.
Course text
There is no assigned textbook for this course. The class notes and video lectures are available in Moodle. The
following texts are good resources:

  1. Linear Algebra Done Right, by Sheldon Axler, Springer International Publishing : Imprint: Springer, 2015
    ISBN: 9783319110806 – available through NCSU libraries.
  2. Linear Algebra – A Free text for a standard US undergraduate course, by Jim Hefferon – link to open source
    book available in Moodle
    The Math Multimedia Center is a tutorial center for undergraduate students that need help in their mathematics courses (100- through 300-level), and is staffed by math graduate students familiar with the material taught
    in these courses.
    Location: SAS Hall 2103/2105
    Hours: Monday – Friday 8:00 am – 5:00 pm
    You can also get help with your courses (not only math) at the NCSU Undergraduate Tutorial Center.
    Catalog Description
    Prerequisite: MA 241 (Co-requisite MA 242)
    This course offers a rigorous treatment of linear algebra, including systems of linear equations, matrices, determinants, abstract vector spaces, bases, linear independence, spanning sets, linear transformations, eigenvalues
    and eigenvectors, similarity, inner product spaces, orthogonality and orthogonal bases, factorization of matrices.
    Compared with MA 305 Introductory Linear Algebra, more emphasis is placed on theory and proofs. MA 225 is
    recommended as a prerequisite. Credit is not allowed for both MA 305 and MA 405.
    Course overview
    Linear Algebra provides one of the cornerstones for much of modern Mathematics, and has important applications
    in Physics, Chemistry, Engineering, Economics, Game Theory, Cryptography, Differential Equations, Genetics,
    Coding Theory and Sociology, and just about any other field of study involving mathematics you can imagine. The
    main purpose of this course is to introduce the basic concepts from linear algebra, explain the underlying theory,
    the computational techniques, and study how these concepts and results can be productively used in other areas
    of mathematics and physical sciences. Among the topics covered in this course will be: solving systems of linear
    equations using Gauss elimination, row echelon form, determinants, vector spaces, linear independence, bases,
    dimension, linear maps, orthogonality, eigenvalues, and reduction of matrices to diagonal forms. If time permits,
    we will discuss applications of linear algebra to differential equations and/or Fibonacci sequences. The subject
    involves a mixture of both the practical and the theoretical, and will provide in particular a good introduction to
    mathematical proofs. The student should be prepared to invest considerable amount of time in understanding the
    class material and doing homework. Credit is not allowed for both MA 305 and MA 405.
    Learning Objectives
    Upon successful completion of this course, students will be able to:
  3. Use Mathematical Notation and Terminology. The students will demonstrate mastery in using the
    mathematical notation and terminology of linear algebra. Students will read, interpret, and use the vocabulary, symbolism and basic definitions.
  4. Understand and Describe the Fundamental Concepts of Linear Algebra. Students will identify and
    apply the theorems about abstract vector spaces and linear transformations; will gain a clear understanding
    of the basic concepts of linear algebra, such as linear independence of vectors, spanning sets, basis, dimension,
    NCSU Department of Mathematics Spring 2019
    linear maps, isomorphism, similarity, eigenvalues and eigenvectors.
  5. Identify and Utilize Linear Algebra Tools. The students will be able to apply course material along
    with techniques and procedures covered in this course to solve problems. Students will master techniques
    for solving linear systems by various matrix methods, compute the determinant and the inverse of a square
    matrix, work with matrix representations of linear maps, compute various factorizations of matrices, apply
    the Gram-Schmidt process, calculate and analyze the characteristic equation of a matrix to determine its
    eigenvalues and eigenvectors. Moreover, students will apply properties and theorems about vector spaces
    to specific mathematical structures that satisfy the vector space axioms, will analyze the differences and
    similarities between spanning sets, bases, and orthogonal bases and will use the knowledge gained in this
    course to determine appropriate methods of proof for specific problems.
  6. Develop Cognitive Skills. Students will demonstrate the ability to reason with abstract linear algebra
    concepts, to read and comprehend mathematical arguments utilizing direct and indirect proof, case analysis,
    and mathematical induction. Students will develop familiarity with axiomatic approach in mathematics
    through the study of vector spaces and linear transformations. They will acquire a level of proficiency in
    manipulating linear algebra concepts, in analyzing and evaluating their applicability in their future studies,
    including graduate work, in academic areas requiring linear algebra as a prerequisite for work in occupational
    fields requiring a background in linear algebra.

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