Incrementing a linearly independent set

Dependencies:

  1. Vector Space
  2. Linear independence

Let $S = \{v_1, v_2, \ldots, v_n\}$ be a linearly independent subset of vector space $V$. Let $u$ be a vector which cannot be represented as a linear combination of vectors in $S$. Then $S \cup \{u\}$ is linearly independent.

Proof

\[ S \cup \{u\} \textrm{ is linearly dependent} \Rightarrow \exists (a_1, a_2, \ldots, a_n, b) \neq 0, bu + \sum_{i=1}^n a_iv_i = 0 \]

Case 1: $b \neq 0$

\[ bu + \sum_{i=1}^n a_iv_i = 0 \Rightarrow u = \sum_{i=1}^n (-b^{-1}a_i)v_i \]

Therefore, $u$ is a linear combination of vectors in $S$. This is a contradiction.

Case 2: $b = 0$

\[ bu + \sum_{i=1}^n a_iv_i = 0 \implies \sum_{i=1}^n a_iv_i = 0 \implies (a_1, a_2, \ldots, a_n) = 0 \tag{$\because$ $S$ is linearly independent} \]

This is a contradiction because we assumed that $(a_1, a_2, \ldots, a_n, b) \neq 0$.

Since assuming that $S \cup \{u\}$ is linearly dependent gives us a contradiction, $S \cup \{u\}$ is linearly independent.

Dependency for:

  1. Symmetric operator on V has a basis of orthonormal eigenvectors
  2. Linearly independent set can be expanded into a basis
  3. Maximally linearly independent iff basis
  4. A set of dim(V) linearly independent vectors is a basis

Info:

Transitive dependencies:

  1. Group
  2. Ring
  3. Field
  4. Vector Space
  5. Linear independence