Propositional Logic

Definition 0.1: Proposition is a statement to which it is possible to assign a truth value.
A proposition is an umbrella term which can be used for any result.
A theorem is a key result which is particularly important.
A lemma is a result which is proved for the purpose of being used in the proof of a theorem.
A corollary is a result which follows from a theorem without much additional effort.

Sets and Numbers

Definition 0.3: A set is a collection of objects. The objects in the set are called elements of the set.
Definition 0.5: The natural numbers are represented by the points on the number line which can be obtained by starting at 0 and moving right by the unit length any number of times.

Basis for natural numbers

Definition 0.6: Let $b \gt 1$. The base-b expansion of a natural number n is the string $drd{r-1}…d_0$
- $n = dr \times b^r + d{r-1} \times b^{r-1} + … + d_0 \times b^0$ ;
- $0 \le d_i \lt b$ for each i; and
- if $n > 0$, then $d_r \ne 0$, the base-b expansion of zero is 0 in all cases b;
Definition 0.11: The integers are represented by the points on the number line which can be obtained by starting at 0 and movnig in either direction by the unit length any number of times.
Definition 0.12: Let $a, b \in Z$. We say b divides a if $a=qb$ for some integer q.
Proposition 0.15: Let $a,b,c \in Z$. If c divides b and b divides a, then c divides a.
Definition 0.17: An integer n is even if it is divisible by 2; otherwise, n is odd.
Theorem 0.18: Let $a,b \in Z$ with $b \ne 0$. There is exactly one way to write
$a = qb + r$
such that q and r are integers, and $0 \le r \lt b$(if $b \gt 0$), or $0 \le r \lt -b$(if $b \lt 0$).

Algorithm to find basis

Given $n \in N$:

Step 1: Let $d_0$ be the remainder when n is divided by b, and let $n_0=\frac{n-d_0}{b}$ be the quotient. Fix i = 0.
Step 2: Suppose $ni$ and $d_i$ have been defined. If $n_i = 0$, then proceed to Step 3. Otherwise, define $d{i+1}$ to be the remainder when $ni$ is divided by b, and define $n{i+1} = \frac{n_i-d_i+1}{b}$. Increment i, and repeat Step 2.
Step 3: The base-b expansion of n, is $did{i-1}…d_0$.

Rationals

Definition 0.24: The rational numbers are represented by the points at the number line which can be obtained by dividing any of the unit line segments between integers into an equal number of parts.

Real numbers

Definition 0.25: The real numebrs are the points on the number line. We write R for the set of all real numbers.

Irrational numbers

Definition 0.27: An irrational number is a real number that is not rational.

Complex numbers

Definition 0.31: The complex numbers are those obtained by the non-negative real numbers upon rotation by any angle about the point 0. We write C for the set of all complex numbers.

Complex number

Addition corresponds to translation.
Multiplication correspond to rotation.

Omit complex conjugate here.

Polynomials

Definition 0.32: Let S=N,Z,Q,R or C. A (univariate) polynomial over S in the indeterminate x is an expression of the form
$a_0+a_1x+…+a_nx^n$
Where $n \in N$ and each $a_k \in S$. The numbers $a_k$ are called the coefficients of the polynomial. If not all coefficients are zero, the largest value of k for which $a_k \ne 0$ is called the degree of the polynomial. By convention, the degree of the polynomial 0 is $-\infinity$
Definition 0.37: Let p(x) be a polynomial. A $root$ of p(x) is a complex number $\alpha$ such that $p(\alpha)=0$.
Omit the theorem of complex conjugate root.

Sets

Axiom 2.1.22 (Sets extensionality)
Let X and Y be sets. Then X = Y if and only if $\forall a, (a \in X \leftrightarrow a \in Y)$, or equivalently, if $X \sub Y$, and $Y \sub X$.
Definition 2.1.36
Let X be a set. The power set of X, written $\mathcal{P}(X)$, is the set of all subsets of X.
Definition 2.2.8
Let X and Y be sets. We say X and Y are disjoint if $X \cap Y$ is empty.
Definition 2.2.18
An (indexed) family of sets is a specification of a set $X_i$ for each element i of some indexing set I. We write ${X_i | i \in I}$ for the indexed family of sets.
Definition 2.2.20
The (indexed) intersection of an indexed family ${Xi | i \in I}$ is defined by
$\bigcap{i \in I} Xi = {a | \forall i \in I, a \in X_i}$
The (indexed) union of ${X_i | i \in I}$ is defined by
$\bigcup{i \in I} X_i = {a | \exists i \in I, a \in X_i}$
Definition 2.2.26
Let X and Y be sets. The relative complement of Y in X, denoted $X \setminus Y$, is defined by
$X \setminus Y = {x \in X | x \notin Y}$
The operation is also known as the set difference operation. Some authors write Y - X instead of $Y \setminus X$.
Theorem 2.2.31 (De Morgan’s Laws for sets)
Given sets A, X, Y and a family ${Xi | i \in I}$, we have
(a) $A \setminus (X \cup Y) = (A \setminus X) \cap (A \setminus Y)$
(b) $A \setminus (X \cap Y) = (A \setminus X) \cup (A \setminus Y)$
(c) $A \setminus \bigcup{i \in I} Xi = \bigcap{i \in I}(A \setminus Xi)$
(d) $A \setminus \bigcap{i \in I} Xi = \bigcup{i \in I}(A \setminus X_i)$
Definition 2.2.33
Let X and Y be sets. The (pairwise) cartesian product of X and Y is the set $X \times Y$ defined by
$X \times Y = {(a, b) | a \in X \wedge b \in Y}$
The elements $(a,b) \in X \times Y$ are called ordered pairs, whose defining property is that, for all $a, x \in X$ and all $b, y \in Y$, we have $(a, b) = (x, y)$ if and only if a = x and b = y.
Definition 2.2.38
Let $n \in \mathbb{N}$ and let $X1, X_2, …, X_n$ be sets. The $(n-fold)cartesian product$ of $X_1, X_2, …, X_n$ is the set $\prod{k=1}^{n} Xk$ defined by
$\prod{k=1}^{n} = {(a1, a_2, …, a_n) | a_k \in X_k, 1 \le k \le n}$
The elements $(a_1, a_2, …, a_n) \in \prod{k=1}^{n} Xk$ are called $ordered k-tuples$, whose defining property is that, for all $1 \le k \le n$ and all $a_k, b_k \in X_k$, we have $(a_1, a_2, … ,a_n) = (b_1, b_2, …, b_n)$ if and only if $a_k = b_k$ for all $1 \le k \le n$.
Given a set X, write $X^n$ to denote the set $\prod{k=1}^{n}X$. We might on occasion also write
$X1 \times X_2 \times … \times X_n = \prod{k=1}^{n}X_k$
Definition 9.2.1
Let $A \subseteq \mathbb{R}$. A real number m is an upper bound for A if $a \le m$ for all $a \in A$. A supremum of A is a least upper bound of A; that is, a real number m such that:
(i) m is an upper bound of A——that is, $a \le m$ for all $a \in A$; and
(ii) m is least amongst all upper bounds for A——that is, for all $x \in \mathbb{R}$, if $a \le x$ for all $a \in A$, then $x \le m$.
Theorem 9.2.5(Uniqueness of suprema)
Let A be a subset of $\mathbb{R}$. If $m_1$ and $m_2$ are suprema of A, then $m_1 = m_2$.
Axiom 9.2.7 (Completemess axiom)
Let $A \subseteq \mathbb{R}$ be inhabited. If A has an upper bound, then A has a supremum.
Definition 9.2.8
If $f: X \to \mathbb{R}$ is a funciton and X is an arbitrary set, we define
$sup f(x) := sup{f(x) : x \in X}$
whenever the sup on RHS exists.
Definition 9.2.9
Let $n \in \mathbb(N), n \ge 1$, we define the n-dimensional Euclidian space $\mathbb{R}^n$ as follows:
$\prod_{i = 1}^{n}\mathbb{R} = \mathbb{R}^n := {(x_1, x_2, x_n) : x_i \in \mathbb{R}, \forall i \in {1, …, n}}$
Definition 9.2.10
Let $\vec{x}, \vec{y} \in \mathbb{R}^n$ and $\lambda \in \mathbb{R}$, we define
(sum) $\vec{x} + \vec{y} = (x_1 + y_1, … ,x_n + y_n)$
(multiplication by scalar) $\lambda \vec{x} = (\lambda x_1, …, \lambda x_n)$
obs: The definition above does not say anything about multiplying vectors by another vector.
Definition 9.2.11
Let $\vec{x}, \vec{y} \in \mathbb{R}^n$. The scalar or dot product of $\vec{x}$ and $\vec{y}$ is the real number defined as
$\vec{x} \dot \vec{y} = <\vec{x}, \vec{y}> := \sum_{i=1}^{n}x_i y_i = x_1y_1 + … + x_ny_n$
Proposition 9.2.12
For any $\vec{x} \in \mathbb{R}^n$, we have: $||\vec{x}||^2 = \vec{x} \dot \vec{x}$
Theorem 9.2.13
Let $\vec{x}, \vec{y} \in \mathbb{R}^n$. Then $\vec{x} \dot \vec{y} = ||\vec{x}||||\vec{y}||cos\theta$
The latter theorem says that vector x is orthogonal to vector y if and only if their scalar product is zero.
Theorem 9.1.16 (Cauchy-Schwarz inequality)
Let $n \in \mathbb{N}$ and let $x_i, y_i \in \mathbb{R}$ for each $i \in [n]$. Then
$|\vec{x} \dot \vec{y}| \le ||\vec{x}||||\vec{y}||$
with equality if and only if $a \vec{x} = b\vec{y}$ for some $a, b \in \mathbb{R}$ which are not both zero.
Theorem 9.2.17 (Triangle inequality)
Let $\vec{x}, \vec{y} \in \mathbb{R}^n$. Then $|| \vec{x} + \vec{y} || \le ||\vec{x}|| + ||\vec{y}||$
Equality holds if and only if $a\vec{x} = b\vec{y}$ for some $a, b \in \mathbb{R}$ which are noth zero and $a, b \ge 0$
Theorem 9.2.18 (Parallelogram law)
Given $\vec{x}, \vec{y} \in \mathbb{R}^n$, we have
$||\vec{x} + \vec{y}||^2 + ||\vec{x} - \vec{y}||^2 = 2||\vec{x}||^2 + 2||\vec{y}||^2$
Moreover, if $\vec{x}$ is orthogonal to $\vec{y}$, then (Pitagoras theorem)
$||x - y||^2 = ||x||^2 + ||y||^2$
Definition 9.1.20
Let $n \ge 1$. The (arithmetic) mean of real numbers $x1, …, x_n$ is
$\frac{1}{n}\sum{i=1}^{n}x_i = \frac{x_1 + x_2 + … + x_n}{n}$
Definition 9.1.21
Let $n \ge 1$. The geometric mean of non-negative real numbers $x1, …, x_n$ is
$\sqrt[n]{\prod{i=1}^{n}x_i} = \sqrt[n]{x_1 \dot x_2 \dot … \dot x_n}$
Theorem 9.1.22 (Inequality of arithmetic and geometric means)
Let $n \in \mathbb{N}$ and $x_1, x_2, …, x_n \ge 0$. Then
$\sqrt[n]{x_1 \dot \dot \dot x_n} \le \frac{x_1 + … + x_n}{n}$
with equality if and only if $x_1 = … = x_n$
Theorem 9.1.31 (Inequality of geometric and harmonic means)
let $n \in \mathbb{N}$ and $x_1, x_2, …, x_n \gt 0$. Then
$\frac{n}{\frac{1}{x_1} + frac{1}{x_2} + … + frac{1}{x_n}} \le \sqrt[n]{x_1x_2 \dot \dot \dot x_n}$
Theorem 9.1.34 (Inequality of quadratic and arithmetic means)
Let $n \gt 0$ and $x_1, x_2, …, x_n \ge 0$. Then
$\frac{x_1 + … + x_n}{n} \le \sqrt{\frac{x_1^2 + x_2^2 + … + x_n^2}{n}}$
with equality if and only if $x_1 = … = x_n$.