MHB Proving Linear Dependence and Span in n-dimensional Space

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SUMMARY

This discussion focuses on proving linear dependence and span in n-dimensional space, specifically addressing the properties of linear combinations of vectors. The participants confirm that if a set of vectors \( v_1, \ldots, v_k \) is linearly dependent, then there exists an index \( i \) such that \( \text{Lin}(v_1, \ldots, v_k) = \text{Lin}(v_1, \ldots, v_{i-1}, v_{i+1}, \ldots, v_k) \). They also clarify that the equality of linear spans holds true even when the order of vectors is altered, emphasizing the commutative property of vector addition. The discussion concludes with a consensus on the definitions and implications of linear dependence and span.

PREREQUISITES
  • Understanding of linear algebra concepts, particularly linear dependence and span.
  • Familiarity with vector spaces and linear combinations.
  • Knowledge of notation used in set theory and linear algebra.
  • Basic proficiency in mathematical proofs and logical reasoning.
NEXT STEPS
  • Study the definition and properties of linear combinations in vector spaces.
  • Explore the implications of linear dependence in higher-dimensional spaces.
  • Learn about the relationship between bases and spans in vector spaces.
  • Investigate the commutative property of vector addition and its applications in proofs.
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Students and professionals in mathematics, particularly those studying linear algebra, vector spaces, and mathematical proofs. This discussion is beneficial for anyone looking to deepen their understanding of linear dependence and span in n-dimensional space.

mathmari
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Hey! :o

Let $1\leq n,k\in \mathbb{N}$ and let $v_1, \ldots , v_k\in \mathbb{R}^k$. Show that:
  1. Let $w\in \text{Lin}(v_1, \ldots , v_k)$. Then it holds that $\text{Lin}(v_1, \ldots , v_k)=\text{Lin}(v_1, \ldots , v_k,w)$.
  2. Let $v_1, \ldots , v_k$ be linearly dependent. Thn there is a $1\leq i\leq k$ and $\lambda_1, \ldots , \lambda_k$ such that $v_i=\lambda_1v_1+\ldots +\lambda_{i-1}v_{i-1}+\lambda_{i+1}v_{i+1}+\ldots +\lambda_nk_n$.
  3. Let $i_1, \ldots i_k\in \mathbb{N}$, such that $\{1, \ldots , k\}=\{i_1, \ldots , i_k\}$. Then it holds that $\text{Lin}(v_1, \ldots , v_k)=\text{Lin}(v_{i_1}, \ldots , v_{i_k})$.
  4. Let $v_1, \ldots , v_k$ be linearly dependent. Then there is a $1\leq i\leq k$ such that $\text{Lin}(v_1, \ldots , v_k)=\text{Lin}(v_1, \ldots , v_{i-1}, v_{i+1}, \ldots, v_k)$.

I have already shown the first two points. Could you please give me a hint fot the point $3$ ? (Wondering) As for point $4$ : Do we use here the point $2$ ? Suppose $v_i=\lambda_1v_1 +\ldots \lambda_{i-1}v_{i-1}+\lambda_{i+1}v_{i+1}+\ldots +\lambda_kv_k$. Then it holds that $\text{Lin}(v_1, \ldots , v_k)\subseteq \text{Lin}(v_1, \ldots , v_{i-1}, v_{i+1}, \ldots, v_k)$, or not?
No it is left to show that $\text{Lin}(v_1, \ldots , v_{i-1}, v_{i+1}, \ldots, v_k)\subset \text{Lin}(v_1, \ldots , v_k)$, or not?

Or is there an other for this proof?

(Wondering)
 
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For (3), what does "\{1, …, k\}= \{i_1, …, i_k\}" mean? With standard set notation that would just mean that v_1= v_{i_1}, …, v_k= v_{i_k} but then the problem is trivial. Or is the point that the order doesn't matter? Then the problem is almost trivial- just using the fact that vector addition is commutative.
 
mathmari said:
Hey! :o

Let $1\leq n,k\in \mathbb{N}$ and let $v_1, \ldots , v_k\in \mathbb{R}^k$. Show that:
4. Let $v_1, \ldots , v_k$ be linearly dependent. Then there is a $1\leq i\leq k$ such that $\text{Lin}(v_1, \ldots , v_k)=\text{Lin}(v_1, \ldots , v_{i-1}, v_{i+1}, \ldots, v_k)$.

As for point $4$ : Do we use here the point $2$ ? Suppose $v_i=\lambda_1v_1 +\ldots \lambda_{i-1}v_{i-1}+\lambda_{i+1}v_{i+1}+\ldots +\lambda_kv_k$. Then it holds that $\text{Lin}(v_1, \ldots , v_k)\subseteq \text{Lin}(v_1, \ldots , v_{i-1}, v_{i+1}, \ldots, v_k)$, or not?

Hey mathmari!

Normally we start from the definition.
From wiki:
The vectors in a subset $S=\{\vec v_1,\vec v_2,\dots,\vec v_k\}$ of a vector space $V$ are said to be ''linearly dependent'', if there exist scalars $a_1,a_2,\dots,a_k$, not all zero, such that
$$a_1\vec v_1+a_2\vec v_2+\cdots+a_k\vec v_k= \vec 0,$$
where $\vec 0$ denotes the zero vector.


Let $a_i$ be one of those scalars that is not zero.
Then:
$$a_1\vec v_1+a_2\vec v_2+\cdots+a_k\vec v_k= \vec 0
\implies \vec v_i = -\frac{1}{a_i}\left(a_1 \vec v_1+\cdots + a_{i-1}\vec v_{i-1}+ a_{i+1}\vec v_{i+1}+\cdots+a_k\vec v_k\right)
$$
So $\vec v_i \in \operatorname{Lin}(v_1, \ldots , v_{i-1}, v_{i+1}, \ldots, v_k)$, isn't it? (Wondering)
mathmari said:
No it is left to show that $\text{Lin}(v_1, \ldots , v_{i-1}, v_{i+1}, \ldots, v_k)\subset \text{Lin}(v_1, \ldots , v_k)$, or not?

Yes, and that follows from the definition of a linear span, doesn't it?
What is the definition of a linear span? (Wondering)
 
Klaas van Aarsen said:
Let $a_i$ be one of those scalars that is not zero.
Then:
$$a_1\vec v_1+a_2\vec v_2+\cdots+a_k\vec v_k= \vec 0
\implies \vec v_i = -\frac{1}{a_i}\left(a_1 \vec v_1+\cdots + a_{i-1}\vec v_{i-1}+ a_{i+1}\vec v_{i+1}+\cdots+a_k\vec v_k\right)
$$
So $\vec v_i \in \operatorname{Lin}(v_1, \ldots , v_{i-1}, v_{i+1}, \ldots, v_k)$, isn't it? (Wondering)

So this direction follows from point 2., doesn't t? (Wondering)
Klaas van Aarsen said:
Yes, and that follows from the definition of a linear span, doesn't it?
What is the definition of a linear span? (Wondering)

Let $x\in \text{Lin}(v_1, \ldots , v_{i-1}, v_{i+1}, \ldots, v_k)$. Then $x$ is a linear combination of the elements $v_1, \ldots , v_{i-1}, v_{i+1}, \ldots, v_k$, i.e. \begin{equation*}x=\lambda_1v_1+ \ldots + \lambda_{i-1}v_{i-1}+\lambda_{i+1} v_{i+1}+ \ldots+ \lambda_kv_k\end{equation*} Then we can write this element also as follows \begin{equation*}x=\lambda_1v_1+ \ldots + \lambda_{i-1}v_{i-1}+0\cdot v_i+\lambda_{i+1} v_{i+1}+ \ldots+ \lambda_kv_k\end{equation*} and now it is a linear combination of the elements $v_1, \ldots , v_{i-1}, v_i,v_{i+1}, \ldots, v_k$ and this means that $x\in \text{Lin}(v_1, \ldots , v_k)$.

So we get that $\text{Lin}(v_1, \ldots , v_{i-1}, v_{i+1}, \ldots, v_k)\subseteq \text{Lin}(v_1, \ldots , v_k)$. Is everything correct? (Wondering)

- - - Updated - - -

HallsofIvy said:
For (3), what does "\{1, …, k\}= \{i_1, …, i_k\}" mean? With standard set notation that would just mean that v_1= v_{i_1}, …, v_k= v_{i_k} but then the problem is trivial. Or is the point that the order doesn't matter? Then the problem is almost trivial- just using the fact that vector addition is commutative.

I am also a bit confused about the meaning. I think that your second assumption is meant, since the first were too easy. (Thinking)

So do we have to show that at the linear combination we can change the order of the vectors? (Wondering)
 
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