Shilov's Linear Algebra Subspace Question

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Discussion Overview

The discussion revolves around a concept from Shilov's linear algebra regarding linear independence of vectors in a subspace L and a larger space K, specifically addressing the relationship between these subspaces and the implications for their dimensions. Participants explore the definitions and proofs presented in the text, seeking clarification on the independence of certain vector sets and the dimensionality of the spaces involved.

Discussion Character

  • Technical explanation
  • Conceptual clarification
  • Debate/contested
  • Mathematical reasoning

Main Points Raised

  • Some participants question why a linear combination of vectors from subspace L and vectors from K over L is considered independent, referencing Shilov's proof.
  • It is noted that the set of vectors {f1,...,fl} is a basis for L, while the set {g1,...,gk} does not necessarily form a basis for any subspace.
  • Participants discuss the condition that if k = n - l, then the combined set {f1,...,fl,g1,...,gk} can form a basis for K.
  • There is confusion about whether the vectors g1,...,gk are elements of L, with some asserting they are not, while others seek clarification on their relationship to L.
  • One participant provides an example using R^2 and R^3 to illustrate the independence of certain vectors over L, which helps clarify the concept for others.
  • Another participant suggests that the concepts discussed may become clearer when exploring quotient spaces in future studies.

Areas of Agreement / Disagreement

Participants express varying levels of understanding regarding the independence of the vector sets and the definitions involved. While some agree on the proof's validity, others remain uncertain about specific aspects, indicating that the discussion is not fully resolved.

Contextual Notes

There are limitations in understanding the implications of linear combinations and the definitions of the subspaces involved. The discussion highlights the need for clarity on the relationships between the vectors and their respective spaces.

Chacabucogod
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Hi,

I'm reading Shilov's linear algebra and in part 2.44 he talks about linear independent vectors in a subspace L which is a subset of space K( he refers to it as K over L). I don't understand why he says that a linear combination of vectors of the subspace L and vectors of the subspace K over L is independent. Is it the same subspace or am I wrong? Shilov also says that the dimension of the subspace K over L n-l. Why?

LINK to the page:

http://books.google.com.mx/books?id=5U6loPxlvQkC&pg=PA44&lpg=PA44&dq=2.44+shilov+linear+algebra&source=bl&ots=bcYpdoyvx7&sig=3daYGhPuQKVDbO2nc1TGrXb75tA&hl=es&sa=X&ei=P1MaU9nrOYPj2AWKjYHQCw&ved=0CEkQ6AEwAw#v=onepage&q=2.44%20shilov%20linear%20algebra&f=false
 
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Chacabucogod said:
Hi,

I'm reading Shilov's linear algebra and in part 2.44 he talks about linear independent vectors in a subspace L which is a subset of space K( he refers to it as K over L). I don't understand why he says that a linear combination of vectors of the subspace L and vectors of the subspace K over L is independent.

He proves it in the text. He takes a linear independent set ##\{f_1,...,f_l\}\subseteq L## and a set ##\{g_1,...,g_k\}\subseteq K## such that they are linear indepent over L. Then Shilov explicitely shows that

\alpha_1 f_1+...+\alpha_lf_l +\beta_1 g_1 +... + \beta_k g_k = 0

implies that ##\alpha_1 = ... = \alpha_l = \beta_1 = ...=\beta_k = 0## which implies linear independence in K.

Shilov also says that the dimension of the subspace K over L n-l. Why?

He explicitely proves this in the book. What about the proof is unclear?
 
So both f and g are bases of the subspace?
 
Chacabucogod said:
So both f and g are bases of the subspace?

The set ##\{f_1,...,f_l\}## is a linear independent set of ##L##. And ##L## is assumed to have dimension ##l##, so ##\{f_1,...,f_l\}## is indeed a basis.

The ##\{g_1,...,g_k\}## do not (in general) form a basis of anything.

However, we do know that if ##k = n-l## (where ##K## has been assumed to have dimension ##n##), then ##\{f_1,...,f_l,g_1,...,g_k\}## is a basis of ##K##.
 
I still don't get it :(. The set of g's are just random vectors, or what? Because he says that vectors g_1...g_k are part of L.
 
Chacabucogod said:
I still don't get it :(. The set of g's are just random vectors, or what? Because he says that vectors g_1...g_k are part of L.

He never says that the ##g_1,...,g_k## are elements of ##L##.

The ##g_1,...,g_k## are just random elements of ##K##. And you only know that they are linearly independent over ##L##.
 
Ok... What does he mean then with:

α1g1+...+αkgk belongs to L
 
Chacabucogod said:
Ok... What does he mean then with:

α1g1+...+αkgk belongs to L

He means that if ##\alpha_1 g_1 + ... + \alpha_kg_k\in L##, then ##\alpha_1 = ...=\alpha_k = 0##.

So the only linear combination of the ##\{g_1,...,g_k\}## belonging to ##L## is the zero vector. And it's not because some linear combination belongs to ##L##, that the ##g_j## separately belong to ##L##.
 
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Do you have an example? Because I still can't grasp the idea. Thank you
 
  • #10
Chacabucogod said:
Do you have an example? Because I still can't grasp the idea. Thank you

Take ##K = \mathbb{R}^2## and ##L## the ##x##-axis, thus ##L = \mathrm{span}\{(1,0)\}##.

Then ##(1,1)## and ##(1,-1)## are not independent over ##L## because

1\cdot (1,1) + 1\cdot (1,-1) = (2,0)\in L

but the coefficients are not all ##0##.

Consider however ##K=\mathbb{R}^3## and ##L = \mathrm\{(1,0,0)\}## the ##x##-axis again. Then ##(0,1,0)## and ##(0,0,1)## are independent over ##L##. Indeed, take any linear combination

x:=\alpha(0,1,0) + \beta(0,0,1) = (0,\alpha,\beta)

if this were in ##L##, then there would exist some scalar ##c## such that ##x = c(1,0,0)##. But then

(c,0,0) = (0,\alpha,\beta)

which is clearly only possible if ##c=\alpha=\beta=0##.
 
  • #11
Ok now I get it. Thanks a lot for taking the time to answer my questions and having the patience.
 
  • #12
I think that these things will make more sense to you once you get to quotient spaces. Right now, I think the concept is pulled a bit out of the air.
 

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