COMS 3203: Discrete Mathematics (Fall 2021)

Antonio Khalil Moretti

"What one fool can understand, another can." -- R.P. Feynman

Last updated December 9th, 2021.


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Course Description

Combinatorics is an ancient subject that concerns the algebra of enumeration or counting. The study of discrete structures and the ability to utilize combinatorial methods is central to numerous other fields including probability, analysis, number theory and abstract algebra. A primary motivation for studying discrete mathematics is the central role it plays in computer science - in data structures, algorithms and the theory of programming languages. This course will provide a general introduction to the facinating field of discrete mathematics and combinatorics.

Students will learn methods for counting as well as techniques to analyze recursions, sequences and computer algorithms. The methods taught in this course are often subtle - it took thousands of years to understand some of the ideas to be discussed. Most notably, this course will attempt to develop a different skill set than memorizing formulas or applying learned techniques. However, the ability to strengthen problem solving skills and think rigorously will aid in your understanding of computer science. While the topics and problem sets may be challenging, we will explore them in a collaborative and supportive environment.

Learning Objectives

Students will:

Learning Resources

There is no required textbook for the course, however the following texts give alternative presentations of similar content. In order to expose students to other points of contact with discrete mathematics, a fair amount of extra material (not in the textbook) may be introduced in class. You are encouraged to do the recommended readings. Each textbook offers a student-friendly exposition of the fundamentals required to excel in the course.

Grading

Detailed syllabus

The semester's tentative schedule is detailed below.

Date Summary Video Recordings Reference Reading Lecture Notes Recitations Assignments
Lecture 1
(Tues Sept 14)   
Introduction, propositions, theorems and proofs
Fundamental Theorem of Arithmetic
proof by contradiction and contrapositive
proved sqrt two and sqrt prime are irrational
1.1, 1.2 Rosen 1.1-1.7
Cummings 5.1-5.5
Grimaldi 2.1-2.5
Lecture 1
Lecture 2
(Tues Sept 16)
Logic, truth tables, quantifiers, sets
revisit proof by contradiction and contrapositive
Euclids proof for the infinitude of primes
divisors, sum of geometric series, the Cantor set

2.1, 2.2
Cummings 7.1-7.5
Grimaldi 3.1-3.3
Lecture 2
Lecture 3
(Tues Sept 21)
Open and closed sets, binary and ternary representations
geometric progressions and properties of the Cantor set
a new definition of functions, field axioms
3.1, 3.2, 3.3, 3.4 Rosen 2.3-2.5
D'Angelo and West Ch 1
Lecture 3
Lecture 4
(Thurs Sept 23)
Injections, surjections, bijections, function composition
cardinality, constructing a bijection from N to Z
the Stern-Brocot tree, properties and the rational numbers Q
binary matrix representation of the Stern-Brocot tree
4.1, 4.2 Rosen 2.3-2.5
Graham & Knuth 4.5
D'Angelo Ch 4
Lecture 4Recitation 1
Logic, quantifiers, proofs, sets, series
Problems from Rosen:
1.1: 28, 31, 1.3: 4, 22, 1.4: 50
1.7: 3, 17, 1.8: 30, 2.2: 4, 2.4: 31
Lecture 5
(Tues Sept 28)
Stern's diatomic series and array for a bijection from N+ to Q+
rational approximations, the Archimedian property
proving the density of rational numbers
Cantor's diagonalization argument for uncountability of R
5.1, 5.2 Rosen 2.3-2.5
Graham and Knuth 4.5
D'Angelo & West 4
Lecture 5Recitation 2
Injections, surjections, bijections, countability
Problems from Rosen:
2.3: 3, 7, 10, 21, 26, 44a
2.4: 35, 36 and 2.5: 3, 28
Homework 1
Solution
Lecture 6
(Thurs Sept 30th)
Stating and proving the principle of induction
examples of proof by ordinary induction
covering any 2nx2n chessboard missing a square with L-shaped trominoes
6.1, 6.2 Rosen Ch 5
Cummings Ch 4
D'Angelo & West 3
Lecture 6
Lecture 7
(Tues Oct 5th)
The principle of strong induction
examples of proof by strong induction
7 Rosen Ch 5
Cummings Ch 4
D'Angelo & West 3
Lecture 7
Lecture 8
(Thurs Oct 7th)
Proving the Fundamental Theorem of Arithmetic
Euclids Lemma, Gauss's Lemma, Bezouts Identity
The Well Ordering Principle
The Euclidean and Extended Euclidean Algorithms
8.1, 8.2 Rosen Ch 4Lecture 8Recitation 3
Ordinary and Strong Induction
Problems from Rosen:
5.1: 4, 5, 7, 28, 32, 36
5.2: 12
Practice Exam 1
Solution
Lecture 9
(Tues Oct 12th)
Review for Exam 1
9 Rosen 1, 2, 4, 5
Lecture 10
(Thurs Oct 14th)
Exam 1
Exam 1
Solution
Lecture 11
(Tues Oct 19th)

Relations, equivalence relations, congruence classes
directed graphs, Hasse diagrams, residues
11.1 , 11.2 Rosen Ch 9, 4.4 - 4.6Lecture 11
Lecture 12
(Thurs Oct 21st)

Properties of relations, congruence classes, groups
modular inverses, a roadmap to solving linear congruences
12.1 , 12.2 Rosen Ch 9, 4.4 - 4.6Lecture 12Recitation 4
Relations, Equivalence Relations, Congruence Classes
Homework 2
Solution
Lecture 13
(Tues Oct 26th)
Solving linear congruences, systems of linear congruences
Chinese Remainder Theorem
Fermat's Little Theorem, two proofs (direct and via counting necklaces)
13 Rosen 4.4 - 4.6Lecture 13
Lecture 14
(Thurs Oct 28th)
Fermat Primality Test, pseudoprime numbers
Euler's Totient function, examples
Euler's generalization of Fermat's Theorem and proof sketch
Landau notation, the RSA Algorithm
14 Rosen Ch 3, 4.4 - 4.6Lecture 14
Lecture 15
(Thurs Nov 4th)
RSA Algorithm example, Binomial Theorem, polynomial derivatives
Pascal's Triangle, Luca's Theorem and Pascal (mod p)
Wilson's Theorem and proof
15.1 , 15.2 Rosen Ch 3, 4.4 - 4.6Lecture 15
Lecture 16
(Tues Nov 9th)
Review for Exam 2 16.1 , 16.2 Rosen Ch 3, 4.4 - 4.6Recitation 5
Modular Arithmetic, CRT
Fermat's Theorem and Binomial Theorem examples
Practice Exam 2
Solution
Exam 2
(Thurs Nov 11th)
Exam 2 Exam 2
Solution
Lecture 17
(Tues Nov 16th)
Tower of Hanoi, recurrence relations
the characteristic equation and polynomial
solving linear homogeneous recurrence relations
17 Rosen Ch 8.1-8.2Lecture 17
Lecture 18
(Thurs Nov 18th)
linear homogeneous recurrence relation examples
Gaussian elimination, non-homogeneous recurrence relations
divide and conquor recurrence relations
18 Rosen Ch 8Lecture 18 Homework 3
Solution
Lecture 19
(Tues Nov 23rd)
Divide and conquor recurrence relations
binary search, recursion trees, complexity
master theorem and proof sketch
using generating functions to solve recurrence relations
Inclusion-Exclusion principle, probability axioms
19.1 , 19.2 Rosen Ch 8, 7.1-7.2Lecture 19Recitation 6
Recurrence Relations
Problems from Rosen:
8.1: 8a, 8.2: 3d, 3g, 28
Thanksgiving
(Thurs Nov 25th)
Lecture 20
(Tues Nov 30th)
Probability Axioms
conditional, pairwise and mutual independence
Bernoulli trials and the Binomial distribution
random variables and probability mass functions
conditional, joint and marginal probabilities
sums of independent RVs, the central limit theorem
Gaussian integral and normal distribution, Bayes theorem
expectations, uniform, geometric and poisson distributions
20 Rosen Ch 7Lecture 20 Homework 4
Lecture 21
(Thurs Dec 2nd)
Expectation and variance examples
negative binomial, poisson, geometric and hypergeometric distributions
calculating moments of negative binomial and poisson random variables
21 Rosen Ch 7Lecture 21
Lecture 22
(Tues Dec 7th)
Review for Exam 3 22 Rosen Ch 7 Practice Exam 3
Solution
Lecture 23
(Thurs Dec 9th)
Exam 3 Rosen Ch 7 Exam 3
Solution