Linear Algebra Problem: Finding the Matrix A for a 3-Dimensional Subspace

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SUMMARY

The discussion centers on finding a matrix A that represents a 3-dimensional subspace W defined by the span of vectors u, v, and w in a vector space V with basis α = {e1, e2, e3}. The vectors are defined as u = e1 − e2 + e3, v = e1 + e3, and w = e1 + e2 + e3. Through row reduction, it is determined that the vectors are not linearly independent, leading to the conclusion that removing one vector results in a linearly independent set. The next steps involve determining the number of free parameters in the solution space W, which relates to the number of equations for the matrix A.

PREREQUISITES
  • Understanding of vector spaces and bases, specifically in 3 dimensions.
  • Familiarity with linear independence and span of vectors.
  • Knowledge of row reduction techniques for matrices.
  • Concept of reduced row echelon form (RREF) in linear algebra.
NEXT STEPS
  • Study the process of determining linear independence among vectors in a vector space.
  • Learn about constructing matrices from vector spans and their implications in linear algebra.
  • Investigate the relationship between the number of free parameters and the dimensions of solution spaces.
  • Explore the concept of reduced row echelon form (RREF) and its applications in solving systems of equations.
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Students and professionals in mathematics, particularly those focusing on linear algebra, as well as educators seeking to deepen their understanding of vector spaces and matrix representations.

c00ter
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1. The question is asking:

Let V be a 3-dimensional vector space with a chosen basis α = {e1,e2,e3}. Consider the subspace W = span(u,v,w). Represent W as span(α, [v]α, [w]α), and then write
W as a solution space {X : AX = 0} for some matrix A.

2. u = e1e2 + e3
v = e1 + e3
and w = e1 + e2 + e3




3. so i got w= span([1 -1 1],[1 0 1],[1 1 1])
and through row reduction I found that the vectors in the span are not linearly independent so removing one will make it linearly independent. I removed the last one so we have
w= span([1 -1 1],[1 0 1]) which is linearly indep.

From here I am not sure how to proceed. I was told that at this point I need to "find the number of parameters needed for the solution space (i.e. W) of a hypothetical system of equations" which will give me the number of equations( I am unsure of how the #of free parameters relates to the number of equations). And I think since the space is 3-dimensional this implies I will have 3 unknowns. Knowing # of equations = # of rows and #of unknowns = # of columns for the matrix A. Then find the possible RREF's of such a matrix and see which one has the correct # of free parameters and equations then use this to find the matrix A.

Any help would be greatly appreciated.
 
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c00ter said:
1. The question is asking:

Let V be a 3-dimensional vector space with a chosen basis α = {e1,e2,e3}. Consider the subspace W = span(u,v,w). Represent W as span(α, [v]α, [w]α), and then write
W as a solution space {X : AX = 0} for some matrix A.

2. u = e1e2 + e3
v = e1 + e3
and w = e1 + e2 + e3




3. so i got w= span([1 -1 1],[1 0 1],[1 1 1])

You're saying [1 1 1] = span([1 -1 1],[1 0 1],[1 1 1]). w and W aren't the same thing.

and through row reduction I found that the vectors in the span are not linearly independent so removing one will make it linearly independent. I removed the last one so we have
w= span([1 -1 1],[1 0 1]) which is linearly indep.

From here I am not sure how to proceed. I was told that at this point I need to "find the number of parameters needed for the solution space (i.e. W) of a hypothetical system of equations" which will give me the number of equations( I am unsure of how the #of free parameters relates to the number of equations). And I think since the space is 3-dimensional this implies I will have 3 unknowns. Knowing # of equations = # of rows and #of unknowns = # of columns for the matrix A. Then find the possible RREF's of such a matrix and see which one has the correct # of free parameters and equations then use this to find the matrix A.

Any help would be greatly appreciated.
When you say a vector ##\vec{x}## is in W, what exactly does that mean?
 

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