Algebra — Basic

An Introduction to Abstract Algebra: Groups, Rings, and Fields (Undergraduate Level)

Overview

The basic level introduces the foundations of abstract algebra (modern algebra). We generalize number structures and study algebraic structures such as groups, rings, and fields.

Learning Objectives

  • Understand the definition and basic properties of groups
  • Develop intuition for group theory through concrete examples
  • Understand the concepts of rings and fields
  • Learn the structure of polynomial rings
  • Learn the basics of field extensions

Table of Contents (18 chapters)

Introduction

  1. Chapter 1 Abstract Algebra

    Overview of groups, rings, and fields

Group Theory

  1. Chapter 2 Monoid

    Associative binary operation with identity

  2. Chapter 3 Groups

    Definition of groups, subgroups, permutation groups

  3. Chapter 4 Abelian Groups

    Groups with the commutative law

  4. Chapter 5 Cyclic Groups

    Groups generated by a single element

  5. Chapter 6 Cosets and Normal Subgroups

    Cosets, normal subgroups, and the kernel correspondence

  6. Chapter 7 Quotient Groups

    Partitioning groups by normal subgroups and the isomorphism theorems

  7. Chapter 8 Lagrange's Theorem

    The order of a subgroup divides the order of the group

Rings, Modules, and Fields

  1. Chapter 9 Rings, Modules, and Fields

    Definition of rings, integral domains, fields, ideals, field of fractions, and modules

Polynomials

  1. Chapter 10 Polynomials

    Definition, operations, roots, special polynomials, interpolation, applications

  2. Chapter 11 Binomial Theorem

    Binomial expansion and binomial coefficients

  3. Chapter 12 Partial Fraction Decomposition

    Decomposing rational functions into sums of simpler fractions

  4. Chapter 13 Discriminant

    Discriminants of quadratic, cubic, and general-degree polynomials

  5. Chapter 14 Resultant

    Sylvester matrix, product-of-roots formula, and the discriminant relation

  6. Chapter 15 Synthetic Division and Horner's Method

    Efficient polynomial evaluation algorithms

  7. Chapter 16 Descartes' Rule of Signs

    Upper bound for the number of real roots of a polynomial

History

  1. Chapter 17 History of Polynomials

    Four millennia from ancient Egypt to modern Galois theory

Practice

  1. Chapter 18 Exercises

    Comprehensive practice problems for the basic level

Prerequisites

  • Introductory Algebra material (complex numbers, higher-degree equations)
  • Basic concepts of sets and mappings
  • Foundations of logical proof

Algebraic Structure of "Sum" and "Product"

Here we survey the two operations at the heart of algebra — "sum" and "product" — examining their common properties and mutual relationship.

Properties of "Sum"

The common properties of operations called "sum" are associativity and commutativity.

Basic Properties of Sum

  • Associativity: \((X + Y) + Z = X + (Y + Z)\)
  • Commutativity: \(X + Y = Y + X\)
  • Identity element: there exists \(0\) with \(X + 0 = X\)
  • Inverse element: there exists \(-X\) with \(X + (-X) = 0\)

Important difference from product: a sum is only defined between objects of the same type.

  • vector + vector = vector ✓
  • vector + scalar = ? ✗ (not defined)
  • By contrast, a product can mix types: scalar × vector = vector

Examples of various "sums":

  • Addition of numbers: \(3 + 5 = 8\), \((-2) + 7 = 5\)
  • Sum of vectors: $\begin{pmatrix} 1 \\ 2 \end{pmatrix} + \begin{pmatrix} 3 \\ -1 \end{pmatrix} = \begin{pmatrix} 4 \\ 1 \end{pmatrix}$
  • Sum of matrices: $\begin{pmatrix} 1 & 2 \\ 3 & 4 \end{pmatrix} + \begin{pmatrix} 5 & 6 \\ 7 & 8 \end{pmatrix} = \begin{pmatrix} 6 & 8 \\ 10 & 12 \end{pmatrix}$
  • Sum of functions: \((f+g)(x) = f(x) + g(x)\)
  • Direct sum of sets: \(A \oplus B\) (direct sum of algebraic structures)
  • Exclusive OR: XOR (addition in \(\mathbb{Z}/2\mathbb{Z}\))

Properties of "Product"

What operations called "product" share is bilinearity.

What is Bilinearity?

A map \(f: V \times V \to W\) is bilinear if it is linear in each argument:

  • \(f(aX + bY, Z) = a \cdot f(X, Z) + b \cdot f(Y, Z)\)
  • \(f(Z, aX + bY) = a \cdot f(Z, X) + b \cdot f(Z, Y)\)

Comparison of major "products":

Operation Bilinear Associative Commutative Notes
Ordinary product \(xy\)
Matrix product \(AB\)
Inner product \(\langle X, Y \rangle\) returns a scalar
Cross product \(X \times Y\) anti-commutative
Lie bracket \([X, Y]\) anti-commutative + Jacobi identity
Tensor product \(X \otimes Y\) dimensions multiply
Wedge product \(\omega \wedge \eta\) product of differential forms

Associativity and commutativity may fail depending on the operation, but bilinearity is common to every "product". This can be regarded as the essential condition for being called a product.

Note: a group operation does not have bilinearity (it is not necessarily defined on a linear space). Bilinearity is a property specific to "products" on linear spaces.