Woodward, Christopher |
L | 02403 | 640 | 350 | 02 | MW5 | 0320 P - 0440 | SEC: 206 |
BUS |

- This course is a proof-based continuation of Math 250, covering Abstract vector spaces and linear transformations, inner product spaces, diagonalization, and canonical forms.

*Prerequisites: *

- CALC4, Math 250 and Math 300

Text: *Linear Algebra* (4th ed.), by Friedberg, Insel and Spence,

Prentice Hall, 2003 ISBN 0-13-008451-4.

- Lectures MW5 (3:20-4:40PM) in
**SEC: 206** - Office Hours: Wednesday 2-3pm, Hill 726
- Contact Information: e-mail ctw@math.rutgers.edu

The course is strongly based on Math 250. However, we'll work axiomatically, starting from the abstract notions of vector space and of linear transformation. Much of the homework and many of the exam and quiz problems will require you to write precise proofs, building on your proof-writing experience in Math 300. From this more abstract viewpoint, we'll be developing linear algebra far beyond Math 250, with new insight and new applications.

Class attendance is very important. A lot of what we do in class will involve collective participation. We will cover the topics indicated in the syllabus below, but the dates that we cover some of the topics might be adjusted during the semester, depending on class discussion, etc. Such adjustments, along with the almost-weekly homework assignments, will be announced in class and also posted on this webpage, so be sure to check this webpage regularly. Absences from a single class due to minor illnesses should be self-reported using the university system; for longer absences, students should email me with the situation. I reserve the right to lower the course grade up to one full letter grade for poor attendance.

Make-ups for exams are generally not given; if a student has an extremely good reason (e.g. documented medical emergency) I may re-arrange the grading scheme to accomodate.

Problem sets are due on most Wednesdays. There are no problems due on the two midterm-exam Wednesdays.

Note that we will cover significant material from all the chapters in the book, Chapters 1-7, but we will cover Chapter 7 before Chapter 6. This is because the material in Chapter 7 is a natural continuation of the material in Chapter 5 on the theory of eigenvalues, eigenvectors and diagonalizability. Chapter 6 also concerns eigenvalues, eigenvectors and diagonalizability, but this time, based on a generalization of the theory of dot products.

Quizzes will be given at the ends of a few class sessions. The dates of these quizzes, and the topics covered, will be announced in advance.

Grading policy: First midterm exam: 100 points; Second midterm exam: 100 points; Homework and quizzes: 100 points; Final exam: 200 points (Total: 500 points).

#### Tentative Course Syllabus

Week | Lecture dates | Sections | topics |
---|---|---|---|

1 | 9/6 (W) | Chapter 1 | Abstract vector spaces & subspaces |

2 | 9/11, 9/13 | Chapter 1 | Span of subsets, linear independence |

3 | 9/18, 9/20 | Chapter 1 | Bases and dimension |

4 | 9/25, 9/27 | Chapter 2 | Linear transformations |

5 | 10/2, 10/4 | Chapter 2 | Change of basis, dual spaces |

6 | 10/9, 10/11 | Ch. 1-2 | Review and Exam 1 (10/11) |

7 | 10/16, 10/18 | Chapter 3 | Rank and Systems of Linear Equations |

8 | 10/23, 10/25 | Chapter 4 | Determinants and their properties |

9 | 10/30, 11/1 | Chapter 5 | Eigenvalues/eigenvectors |

10 | 11/6, 11/8 | Chapter 5 | Cayley-Hamilton |

11 | 11/13, 11/15 | Chapter 7 | Jordan Canonical Form |

12 | 11/20 | Chapter 7 | Rational Canonical Form |

13 | 11/27, 11/29 | Ch.3,4,5,7 | Review and Exam 2 (11/29) |

14 | 12/4, 12/6 | Chapter 6 | Inner Product spaces |

15 | 12/11, 12/13 | Chapter 6 | Unitary and Orthogonal operators (last class) |

17 | 12/22 (Friday) | 12-3 PM | Final Exam |

#### Exam Dates

The exam dates are listed in the schedule above. Any conflict (such as with a religious holiday) should be reported to me at the beginning of the semester, so that the exam may be re-scheduled.

### Special Accommodations

Students with disabilities requesting accommodations must follow the procedures outlined at https://ods.rutgers.edu/students/applying-for-services

### Academic Integrity

All Rutgers students are expected to be familiar with and abide by the academic integrity policy. Violations of the policy are taken very seriously. In particular, your work should be your own; you are responsible for properly crediting all help with the solution.

#### Problem Set 1

(Problems in pdf. Solutions in pdf.)

(1) Find the space of polynomials \(f(x) = \{ ax^2 + bx + c \}\) satisfying \(f(-1) = -1, f'(-1) = -1\).

(2) Show that the set of functions \(f: S \to \mathbb{R}\) from a set \(S\) to the real numbers \(\mathbb{R}\) with addition given by \((f + g)(x) = f(x) + g(x)\) and scalar multiplication given by \((cf)(x) = c(f(x))\) satisfies axiom (VS4) in the axioms for a vector space.

(3) Show that the set of polynomials in a single real variable with addition given by \((f + g)(x) = f(x) + g(x)\) and scalar multiplication \((cf)(x) = f(cx)\) is not a vector space.

(4) Show that if \(V\) is a vector space and \(v \in V\) and \(c \in F\) are such that \(cv = 0\) then either \(c = 0\) or \(v = 0\). [Hint: argue by cases or by contradiction.]

(5) Prove that \( \{ (1,1,0), (1,0,1), (0,1,1) \}\) is linearly independent over \(\mathbb{R}\) but linearly dependent over \(\mathbb{Z}_2\).

#### Problem Set 2

(Problems in pdf. Solutions in pdf.)

(1) Prove that a nonempty subset \(W\) of a vector space \(V\) is a subspace iff \(\operatorname{span}(W) = W\).

(2) Prove that the polynomials \(1, x, x^2\) are linearly independent in the space of functions from \(\mathbb{R}\) to \(\mathbb{R}\).

(3) Find a basis for the space of real polynomials \(\{ f(x) = ax^3 + bx^2 + cx + d \ | \ f(1) = 0 \}\).

(4) Find a basis for the vector space of real polynomials of arbitrary degree, and prove that your answer is a basis. [Warning: linear independence is a bit tricky.] Show that this space is infinite dimensional.

(5) Show that if \(W\) is a subspace of a finite-dimensional vector space \(V\) and \(\dim(W) = \dim(V)\) then \(V = W\).

(6) Find a basis for the space of real skew-symmetric matrices of size \(n\). What is the dimension of the space?

#### Problem Set 3

(Problems in pdf. Solutions in pdf.)

(1) Show that the space of convergent sequences of real numbers is an infinite-dimensional subspace of the space of all sequences of real numbers. [Hint: exhibit an linearly independent subset of infinite size.]

(2) Show that if \(T: V \rightarrow W\) and \(S: W \rightarrow U\) are linear transformations then the composition \(S \circ T: V \rightarrow U\) is also a linear transformation.

(3) Suppose that \(T:\mathbb{R}^2 \rightarrow \mathbb{R}^2\) is a linear transformation. If \(T(1,0) = (2,3)\) and \(T(0,1) = (3,4)\), find \(T(2,1)\). Justify your answer.

(4) Show that the function \(T:\mathbb{R}^2 \rightarrow \mathbb{R}^2\) defined by \(T(x,y) = (|x|,|y|)\) is not a linear transformation.

(5) Let \(T: P_2(R) \rightarrow P_2(R)\) (here \(P_2(\mathbb{R})\) is the space of polynomials in a real variable of degree at most 2) be the linear transformation defined by \((T(f))(x) = x f'(x)\). Show that \(T\) is a linear transformation and find its nullspace and range.

#### Problem Set 4

(Problems in pdf. Solutions in pdf.)

(1) Find the coordinates of the given vector with respect to the given basis.

(a) \(V = \mathbb{R}^2, B = \{ (1,0), (0,1) \}, v = (1,2)\).

(b) \(V = \mathbb{R}^2, B = \{ (1,1), (1,-1) \}, v = (1,2)\).

(c) \(V = P_2, B = \{ 1, x, x^2 \}, v(x) = (x + 1)^2 \).

(d)

\(V\) the span of \(\sin(x),\cos(x)\) in the space of functions of a real variable \(x\),

\(B = \{ \sin(x), \cos(x) \}\), \(v(x) = \sin(x + 1)\).

(2) Find the matrix of the given linear transformation with respect to the given bases.

(a) \(T: \mathbb{R}^2 \to \mathbb{R}^2, (x,y) \mapsto (-y,x), B = B' = \{ (1,0), (0,1) \}\).

(b) \(T: P_2 \to P_2, B = B' = \{ 1,x,x^2 \}, (Tf)(x) = f(x+1) \).

(c) \(T: V \to V\) where \(V\) is the span of \(\sin(x),\cos(x)\) in the space of functions of a real variable \(x\), \(B = B' = \{ \sin(x), \cos(x) \}\), \((Tf)(x) = f(x + \pi/2) \).

(d) \(T: P_1 \to P_2\), \(B = \{ 1, x \}\), \(B' = \{ 1, x, x^2 \}\), \((Tf)(x) = \int_{0}^x f(t) dt \).

(3) Show that if \(S: V \to W\) and \(T: W \to U\) are linear transformations then

(a) If \(S,T\) are one-to-one then \(T \circ S\) is one-to-one.

(b) Is \(T \circ S\) is one-to-one then \(S\) is one-to-one.

#### Problem Set 5

(Problem in pdf.)

(1) Let \(T: V \to W\) be a linear transformation and \(B \subset V\) a basis. Prove that \(T\) is an isomorphism if and only if \(T(B) := \{ T(b), b \in B \}\) is a basis for \(W\).

(2) In each case find the \(3 \times 3\) elementary matrix \(E\) so that multiplying on the left by \(E\) has the desired effect.

(a) Switching rows \(2\) and \(3\).

(b) Multiplying row \(3\) by \(5\).

(c) Subtracting \(4\) times row \(3\) from row \(1\).

(3) Write the matrix \( \left[ \begin{array}{lll} 0 & 1 & 0 \\

0 & 0 & 2 \\

3 & 0 & 0 \end{array} \right] \)

as the product of elementary matrices.

(4) Find the inverse of the matrix in \(3\) and write it as a product of elementary matrices.

(5) Suppose that \(T: V \to W\) is an isomorphism of vector spaces.

(a) If \(Z \subseteq V\) is a subspace, show that \(\dim(T(Z)) = \dim(Z)\). Here \(T(Z) := \{ T(z) | z \in Z \}\).

(b) Suppose that \(S: U \to V\) is another linear transformation. Show that \(rank(T \circ S)= rank(S)\).

(c) Suppose \(A\) and \(B\) are matrices related by an elementary row operation. Do \(A\) and \(B\) have the same rank, that is, are their columns spaces the same dimension? Why or why not?

#### Practice Exam for First Midterm

(Problems in pdf)

(1) Find all polynomials \(f(x)\) of degree at most \(3\) satisfying \(f'(x) = f(x+1) - f(x)\).

(2) True or false: the functions \(1^x, 2^x, 3^x\) are linearly independent as functions of a real variable \(x\). Prove your answer.

(3) Show that the set of eventually-constant sequences (like \(3,2,1,1,1,1,\ldots \)) is a subspace of the vector space of sequences of real numbers. Find its dimension, and, if possible, a basis.

(4) Let \(V = W = \operatorname{span} B\) where \(B = \{ \sin(x),\cos(x) \}\). Let \(T: V \to W, (Tf)(x) = f(x + \pi/4)\). Find the matrix \(A\) of \(T\) with respect to \(B\). (1 point extra credit: what is \(A^8\) and why?)

(5) Let \(V = P_2\) and \(W = P_4\) and let \(T: V \to W\) be the function \((T f)(x) = f''(x) + x^2f(x)\). Prove that \(T\) is a linear transformation. What are the null space and range of \(T\)?

Additional Problems:

(6) Let \(A\) be the \( 3 \times 3\) matrix whose \(ij\)-th entry is \(i + j\) and let \(T\) be multiplication by \(A\). Find the range and nullspace of \(T\).

(7) Let \(V = W = \operatorname{span} B, B = \{ 1^x, 2^x, 3^x \}\) where \(x\) is a real variable Find the matrix of the linear transformation \(T(f) = f'\) with respect to \(B\).

(8) Show that \(V = \mathbb{R}^2\) with addition defined by \((x_1,y_1) + (x_2,y_2) = (x_1 + x_2,y_1y_2)\) and scalar multiplication \(c(x,y) = (cx,y)\) is not a vector space.

(9) Show that if \(W_1\) and \(W_2\) are subspace of a vector space \(V\) then

\(\dim(W_1 + W_2) \leq \dim(W_1) + \dim(W_2)\).

(10) Show that if \(T: V \to W\) is a one-to-one linear transformation and \(\{ v_1,\ldots, v_k \} \) is a linearly independent subset of \(V\) then \( \{ T(v_1),\ldots, T(v_k) \}\) is a linearly independent subset of \(W\).

(11) Let \(T: V \to V\) be a linear transformation. Show that \(rank(T^2) \leq rank(T)\) and \(nullity(T^2) \ge nullity(T)\).

(12) True/false: explain your answer in each case. (a) Any vector space has a finite basis. (b) A set \(\{ v_1,\ldots, v_k \}\) is linearly dependent iff the last vector \(v_k\) is a linear combination of the others. (c) The empty set is a subspace of any vector space. (d) Any spanning set for a vector space contains a basis. (e) A linear transformation maps the zero vector to the zero vector. (f) If a linear transformation from \(V\) to \(V\) is onto, then so is its square. (g) If the matrix for a linear transformation has a zero column, then the linear tranformation is not one-to-one. (h) Any basis for \(P_n\) (the space of polynomials of degree at most \(n\)) has \(n\) elements. (i) The dimension of the space of \(2 \times 2\) real symmetric matrices is \(2\).

#### Recommended Practice Problems (the problem sets from last year)

Sept. 13 | 1.2 #17; 1.3 #19,23; 1.4 #11,13; 1.5 #9,15 |

Sept. 20 | 1.6 # 20,21,26,29; 1.7 #5,6 |

Sept. 27 | 2.1 #3,11,28; 2.2 #4; 2.3 #12; 2.4 #15,17 |

October 4 | 2.5 #3(d),7(a,b),13; 2.6 #5,10; Show that F[x]* ≅ F[[x]]. |

October 18 | 3.1 #6,12; 3.2 #5(b,d,h),17; 3.3 #8,10; 3.4 #8,15 If an nxn matrix A has each row sum 0, some Ax=b has no solution. |

October 25 | 4.1 #10(a,c); 4.2 #23; 4.3 #12,22(c),25(c); 4.4 #6; 4.5 #11,12 |

Nov. 1 | 5.1 #3(b),20,21; 5.2 #4,9(a),12; Show that the cross product induces an isomorphism between R³ and Λ²(R³). |

Nov. 8 | 5.2 #18(a),21; 5.3 #2(d,f); 5.4 #6(a),13,19,25 |

Nov. 15 | 7.1 #3(b),9(a),13; 7.2 #3,14,19(a); 7.3 #13,14; Find all 4x4 Jordan canonical forms of T satisfying T²=T³. |

Dec. 13 | 6.1; #6,11,12,17; 6.2 #2a,6,11; 6.8 #4(a,c,d),11 |