Subspace Determination using (x,y,z) = a(1,0,1) + b(0,1,0) + c(0,1,1) in R^3

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In summary: Do I need something more like A + B, where A≠B and A,B \in U? If so, then do I write, A + B \in U since U is closed, and thus U + U = U? If the problem had stated, U + U + U = U, would I need A + B + C, where A≠B≠C and A,B,C \in...?
  • #1
TranscendArcu
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Homework Statement



2012_02_05_10_03_20_AM.png


The Attempt at a Solution


Let [itex](x,y,z)[/itex] be arbitrary. We write, [itex](x,y,z) = a(1,0,1) + b(0,1,0) + c(0,1,1) [/itex] for [itex]a,b,c \in R [/itex]. From this,

[itex](x,y,z) = (a,0,a) + (0,b,0) + (0,c,c) = (a,b+c,a+c)[/itex]. However, [itex](a,b+c,a+c)[/itex] can generate all of [itex]R^3[/itex] for appropriately chosen [itex]a,b,c[/itex]. Thus, the subspace in question is all of [itex]R^3[/itex].

Am I doing this right?
 
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  • #2
Hi TranscendArcu! :wink:

Yes, that's fine. :smile:

(another way would be to say that (0,0,1) is the difference of the last two, and (1,0,0) is the difference of that and the first one;

yet another way would be to show that the determinant is non-zero :wink:)
 
  • #3
TranscendArcu said:

Homework Statement



2012_02_05_10_03_20_AM.png


The Attempt at a Solution


Let [itex](x,y,z)[/itex] be arbitrary. We write, [itex](x,y,z) = a(1,0,1) + b(0,1,0) + c(0,1,1) [/itex] for [itex]a,b,c \in R [/itex]. From this,

[itex](x,y,z) = (a,0,a) + (0,b,0) + (0,c,c) = (a,b+c,a+c)[/itex]. However, [itex](a,b+c,a+c)[/itex] can generate all of [itex]R^3[/itex] for appropriately chosen [itex]a,b,c[/itex]. Thus, the subspace in question is all of [itex]R^3[/itex].

Am I doing this right?

another approach is to show that {(1,0,1),(0,1,0),(0,1,1)} is a linearly independent set which would mean that span({(1,0,1),(0,1,0),(0,1,1)}) is a 3-dimensional subspace of R3, hence must be all of R3.

an arbitrary linear combination is, as you noted:

(a,b+c,a+c). if (a,b+c,a+c) = (0,0,0), then:

a = 0
b+c = 0
a+c = 0

a = 0 means that a+c = 0+c, so c = 0, as well. thus b+c = b+0, so b = 0. so if:

(a,b+c,a+c) = a(1,0,1) + b(0,1,0) + c(0,1,1) = (0,0,0), a = b = c = 0, proving linear independence.

it's a good idea to keep all the methods suggested here in mind, because sometimes one way is easier than the others, in terms of ease of calculation.
 
  • #4
Deveno said:
another approach is to show that {(1,0,1),(0,1,0),(0,1,1)} is a linearly independent set which would mean that span({(1,0,1),(0,1,0),(0,1,1)}) is a 3-dimensional subspace of R3, hence must be all of R3.
Does that mean that if V,W, such that W is a subspace of V, are vector spaces, and dimV=dimW, and {A1,...,An} is a basis for W, then span{A1,...,An} = W and V?
 
  • #5
This is another problem I'd like to have my work checked on:

2012_02_05_11_23_55_AM.png


If U is a subspace, then certainly it must have a basis consisting of vectors in V. Let [itex]E = \left\{ V_1,...,V_n \right\}[/itex] be a basis for U. Thus, Span(E) = U. Thus,

[itex]U + U = span(E) + span(E) = a_1 V_1 + ... + a_n V_n + a_1 V_1 + ... + a_n V_n = (2a_1)V_1 + ... + (2a_n) V_n[/itex], which is still span(E) = U. (Let the [itex]a_1,...,a_n \in R[/itex])

QED?
 
  • #6
TranscendArcu said:
Does that mean that if V,W, such that W is a subspace of V, are vector spaces, and dimV=dimW, and {A1,...,An} is a basis for W, then span{A1,...,An} = W and V?

Yes of course. :smile:
TranscendArcu said:
If U is a subspace, then certainly it must have a basis consisting of vectors in V. Let [itex]E = \left\{ V_1,...,V_n \right\}[/itex] be a basis for U. Thus, Span(E) = U. Thus,

[itex]U + U = span(E) + span(E) = a_1 V_1 + ... + a_n V_n + a_1 V_1 + ... + a_n V_n = (2a_1)V_1 + ... + (2a_n) V_n[/itex], which is still span(E) = U. (Let the [itex]a_1,...,a_n \in R[/itex])

QED?

This is very complicated :yuck:

Just prove it from the basic definitions of + and vector subspace. :redface:
 
  • #7
tiny-tim said:
This is very complicated :yuck:

Just prove it from the basic definitions of + and vector subspace. :redface:

Should I just say: let A be an arbitrary vector in U. Then [itex]A +A \in U[/itex] since U is a subspace and closed. Thus, U + U = U.
 
  • #8
TranscendArcu said:
Should I just say: let A be an arbitrary vector in U. Then [itex]A +A \in U[/itex] since U is a subspace and closed. Thus, U + U = U.

But {A+A} doesn't give you every element of U + U, does it? :redface:
 
  • #9
TranscendArcu said:
Should I just say: let A be an arbitrary vector in U. Then [itex]A +A \in U[/itex] since U is a subspace and closed. Thus, U + U = U.

U + U = {u+w: u in U, w in U}.

what i would be tempted to do is show that U and U+U contain each other.

showing U is contained in U+U should be easy (hint: what vector is U guaranteed to have?).

what you have above is only half the story.
 
  • #10
tiny-tim said:
But {A+A} doesn't give you every element of U + U, does it? :redface:

Do I need something more like A + B, where A≠B and [itex]A,B \in U[/itex]? If so, then do I write, [itex]A + B \in U[/itex] since U is closed, and thus U + U = U? If the problem had stated, U + U + U = U, would I need A + B + C, where A≠B≠C and [itex]A,B,C \in U[/itex]?
 
  • #11
Deveno said:
U + U = {u+w: u in U, w in U}.

what i would be tempted to do is show that U and U+U contain each other.

showing U is contained in U+U should be easy (hint: what vector is U guaranteed to have?).

what you have above is only half the story.
So, if [itex]A \in U[/itex] then [itex]A \in U + U[/itex] since [itex]\vec0 \in U[/itex] and [itex]A + \vec0 = A[/itex]?
 
  • #12
yes, and yes (to your post # 10) :smile:

(but you shouldn't say A≠B, since or course they may be the same! :wink:)
 
  • #13
Okay, I'll make those adjustments in my work. Thanks! Here's another problem that I'm working:

2012_02_05_12_21_45_PM.png
Let [itex](a_1,0,0),(a_2,0,0) \in S, x,y \in R[/itex]. Then [itex]x(a_1,0,0) + y(a_2,0,0) = (a_1 x,0,0) + (a_2 y,0,0) = (a_1 x +a_2 y,0,0) \in S[/itex]. Thus, S is a subspace. Let [itex](0,b_1,b_2),(0,q_1,q_2) \in T[/itex]. Then [itex]x(0,b_1,b_2)+ y(0,q_1,q_2) = (0,x b_1,x b_2) + (0,y q_1,y q_2) = (0,x b_1 + y q_1,x b_2 + y q_2) \in T[/itex]. Thus T is a subspace.

I said that S+T will be vectors of the form [itex]\left\{(a,b,b) | a,b \in R \right\}[/itex]. Thus, a basis for S+T will be [itex]\left\{(1,0,0),(0,1,1) \right\}[/itex]. Is that right?
 
  • #14
TranscendArcu said:
Okay, I'll make those adjustments in my work. Thanks! Here's another problem that I'm working:

2012_02_05_12_21_45_PM.png
Let [itex](a_1,0,0),(a_2,0,0) \in S, x,y \in R[/itex]. Then [itex]x(a_1,0,0) + y(a_2,0,0) = (a_1 x,0,0) + (a_2 y,0,0) = (a_1 x +a_2 y,0,0) \in S[/itex]. Thus, S is a subspace. Let [itex](0,b_1,b_2),(0,q_1,q_2) \in T[/itex]. Then [itex]x(0,b_1,b_2)+ y(0,q_1,q_2) = (0,x b_1,x b_2) + (0,y q_1,y q_2) = (0,x b_1 + y q_1,x b_2 + y q_2) \in T[/itex]. Thus T is a subspace.

I said that S+T will be vectors of the form [itex]\left\{(a,b,b) | a,b \in R \right\}[/itex]. Thus, a basis for S+T will be [itex]\left\{(1,0,0),(0,1,1) \right\}[/itex]. Is that right?

it appears that in T, the second and third coordinates are always the same. your proof does not take that into account, and so is incorrect.

can you prove that your proposed basis for S+T actually is one? it's not a difficult task, but i see no demonstration of linear independence OR spanning (to be fair, this is not the most challenging example of a sum subspace, but it's a good habit to get into, because you WILL encounter subspaces S+T that aren't "as nice" in the future).

there is another problem (albeit a minor one). you say:

"let (a1,0,0), (a2,0,0) be in S". when you do something like that, it's a good idea to verify that you actually have some things in S. traditionally, this is often done by showing that (0,0,0) lies in S (if it doesn't, your "subspace" doesn't satisfy the vector space axioms).
 
  • #15
Okay let me try this again.

Let [itex](0,b,b),(0,q,q) \in T[/itex]. We confirm that T has elements in it by observing that (0,0,0) is an element of T. This is true when b=0. Then [itex]x(0,b,b)+ y(0,q,q) = (0,x b,x b) + (0,y q,y q) = (0,x b + y q,x b + y q) \in T[/itex]. Thus T is a subspace.

To prove that [itex]\left\{(1,0,0),(0,1,1) \right\}[/itex] is a basis, we will show first that it is linearly independent. Thus,

[itex](0,0,0) = a(1,0,0) + b(0,1,1)[/itex]. Thus, 0 = 1a, 0=1b, necessitating that a=b=0. Let (x,y,y) be arbitrary in S+T. [itex](x,y,y) = a(1,0,0) + b(0,1,1)[/itex]. Thus, x = 1a = a, y=1b=b. Thus, showing that the basis spans.
 
  • #16
TranscendArcu said:
Okay let me try this again.

Let [itex](0,b,b),(0,q,q) \in T[/itex]. We confirm that T has elements in it by observing that (0,0,0) is an element of T. This is true when b=0. Then [itex]x(0,b,b)+ y(0,q,q) = (0,x b,x b) + (0,y q,y q) = (0,x b + y q,x b + y q) \in T[/itex]. Thus T is a subspace.

To prove that [itex]\left\{(1,0,0),(0,1,1) \right\}[/itex] is a basis, we will show first that it is linearly independent. Thus,

[itex](0,0,0) = a(1,0,0) + b(0,1,1)[/itex]. Thus, 0 = 1a, 0=1b, necessitating that a=b=0. Let (x,y,y) be arbitrary in S+T. [itex](x,y,y) = a(1,0,0) + b(0,1,1)[/itex]. Thus, x = 1a = a, y=1b=b. Thus, showing that the basis spans.

exactly so.

now, in this exercise, those things are obvious, and in an informal discussion, wouldn't need any proof at all. with homework...it depends on how picky your instructor is.

but later on, sometimes the "obvious" things aren't so obvious anymore. that's when having "good habits" can at least get you started in the right direction.
 
  • #17
This is another problem I'd like checked:
2012_02_05_7_33_43_PM.png


Suppose T is injective. Since [itex]A_1,...,A_n[/itex] is a basis, it is linearly independent. That is, [itex]0A_1+...+0A_n = \vec0[/itex]. Thus, [itex]0T(A_1)+...+0T(A_n) = T( \vec0 _w)[/itex]. If T is injective, then [itex]KerT = \left\{ 0 \right\} [/itex], which states that the only vector to map to [itex]\vec0 _w[/itex] is [itex]\vec0 _v[/itex]. Since the only way to create [itex]\vec0 _w[/itex] from the basis of V is with all zero coefficients, we see that [itex]T(A_1),...,T(A_n)[/itex] is linearly independent.

Suppose that [itex]T(A_1),...,T(A_n)[/itex] are linearly independent. Then [itex]0T(A_1)+...+0T(A_n) = T( \vec0 _w )[/itex]. This implies [itex]T(0A_1 + ... 0A_n) = T(\vec0 _v)=\vec0 _w[/itex]. Since any change to the coefficients will result in a nonzero element of V going under T, we see that all coefficients must necessarily be zero in order for [itex]T(\vec 0 _v) =\vec0 _w[/itex]. Thus, the only thing that creates [itex]\vec0 _w[/itex] is [itex]\vec0 _v[/itex], which implies [itex]kerT = \left\{ 0 \right\} [/itex] and T is injective.
 
  • #18
TranscendArcu said:
This is another problem I'd like checked:
2012_02_05_7_33_43_PM.png


Suppose T is injective. Since [itex]A_1,...,A_n[/itex] is a basis, it is linearly independent. That is, [itex]0A_1+...+0A_n = \vec0[/itex]. Thus, [itex]0T(A_1)+...+0T(A_n) = T( \vec0 _w)[/itex]. If T is injective, then [itex]KerT = \left\{ 0 \right\} [/itex], which states that the only vector to map to [itex]\vec0 _w[/itex] is [itex]\vec0 _v[/itex]. Since the only way to create [itex]\vec0 _w[/itex] from the basis of V is with all zero coefficients, we see that [itex]T(A_1),...,T(A_n)[/itex] is linearly independent.

Suppose that [itex]T(A_1),...,T(A_n)[/itex] are linearly independent. Then [itex]0T(A_1)+...+0T(A_n) = T( \vec0 _w )[/itex]. This implies [itex]T(0A_1 + ... 0A_n) = T(\vec0 _v)=\vec0 _w[/itex]. Since any change to the coefficients will result in a nonzero element of V going under T, we see that all coefficients must necessarily be zero in order for [itex]T(\vec 0 _v) =\vec0 _w[/itex]. Thus, the only thing that creates [itex]\vec0 _w[/itex] is [itex]\vec0 _v[/itex], which implies [itex]kerT = \left\{ 0 \right\} [/itex] and T is injective.

i don't mean to be rude (forgive me if i appear that way, my social skills have deteriorated after decades in isolation), but it occurs to me, you might run afoul of the moderators here by "extending" a thread with multiple questions. I've seen some of them request other posters to start new threads for new topics.

just sayin'

**********

your definition of linear independence doesn't look right. ANY linear combination of a set with 0's as every coefficient will sum to the 0-vector, whether the set is linearly independent or not.

if {a1,...,an} is linearly independent, this means that

c1a1+...+cnan= 0, forces every ci to be 0.
 
  • #19
Deveno said:
i don't mean to be rude (forgive me if i appear that way, my social skills have deteriorated after decades in isolation), but it occurs to me, you might run afoul of the moderators here by "extending" a thread with multiple questions. I've seen some of them request other posters to start new threads for new topics.

just sayin'

**********
Oh dang. I thought it would be better to keep all of my questions consolidated in one place (both for myself and for others). I can start creating new topics for my questions if that's best. I hope that we can at least address this last question in this thread, though.

your definition of linear independence doesn't look right. ANY linear combination of a set with 0's as every coefficient will sum to the 0-vector, whether the set is linearly independent or not.

if {a1,...,an} is linearly independent, this means that

c1a1+...+cnan= 0, forces every ci to be 0.
Okay. But I don't immediately see how this effects the work I have above. In particular, I thought I addressed the need for all the coefficients to be zero with phrases like "Since the only way to create [itex]\vec0 _w[/itex] from the basis of V is with all zero coefficients" and "Since any change to the coefficients will result in a nonzero element of V going under T, we see that all coefficients must necessarily be zero in order for [itex]T(\vec 0 _v) =\vec0 _w[/itex]."
 
  • #20
TranscendArcu said:
Oh dang. I thought it would be better to keep all of my questions consolidated in one place (both for myself and for others). I can start creating new topics for my questions if that's best. I hope that we can at least address this last question in this thread, though.

Okay. But I don't immediately see how this effects the work I have above. In particular, I thought I addressed the need for all the coefficients to be zero with phrases like "Since the only way to create [itex]\vec0 _w[/itex] from the basis of V is with all zero coefficients" and "Since any change to the coefficients will result in a nonzero element of V going under T, we see that all coefficients must necessarily be zero in order for [itex]T(\vec 0 _v) =\vec0 _w[/itex]."


what you are GIVEN is that:

{a1,...,an} is a linearly independent set (because it's a basis) what you have to PROVE is that {T(a1),...,T(an)} is ALSO a linearly independent set, from the fact that T is injective.

now you're good with stating that T injective → ker(T) = {0}

so if c1T(a1)+...+cnT(an) = 0, then

(because T is LINEAR)

T(c1a1+..+cnan) = 0

hence, c1a1+..+cnan is in _______ .

but because T is injective, this means that...? (you want something about what we're taking T OF).

now, what does this tell you about the "c's"? why?

then conclude that:_________ .

in the other direction: 0T(a1) +...+ 0T(an) is ALWAYS going to be 0.

you want to show that a linear combination that sums to 0 has to be the 0-combination, not that a 0-combination is 0 (which is always true).

adding something like "since the only way to get 0 is with all 0 coefficients" is putting the horse after the cart. when proving something, start with what you know to be true, and derive what you want to prove.

*******

i would prove the injectivity of T like this:

since {T(a1),...,T(an)} is _____ _______, if

T(c1a1+...+cnan) = _____,

then (by the linearity of T):

(something goes here).

so that _____ = _____ (the only thing you have to use is the linear independence of a certain set, so this should appear in your proof somewhere).

your goal is to show that ker(T) = 0. so you're going to have to take T of something, just to display a typical element of ker(T). then you need to use your conditions given to show that the only thing that something can be, is the 0-vector of V.
 

1. What is subspace determination using (x,y,z) = a(1,0,1) + b(0,1,0) + c(0,1,1) in R^3?

Subspace determination using (x,y,z) = a(1,0,1) + b(0,1,0) + c(0,1,1) in R^3 is a method used to find the span of a set of vectors in three-dimensional space. It involves solving for the values of a, b, and c that satisfy the equation in order to determine the subspace spanned by the vectors.

2. How is this method different from other methods of finding subspaces?

This method is different from other methods of finding subspaces because it is specifically used for finding the span of a set of vectors in three-dimensional space. Other methods may involve solving for the null space or column space of a matrix, which can be used to find subspaces in any dimension.

3. What is the importance of determining subspaces in mathematics and science?

Determining subspaces is important in mathematics and science because it allows us to understand the structure and properties of vector spaces. Subspaces play a crucial role in linear algebra, which is used in many fields such as physics, engineering, and computer science.

4. Can this method be used for any set of vectors in R^3?

Yes, this method can be used for any set of vectors in R^3. However, it is important to note that the vectors must be linearly independent in order for the span to be a subspace. If the vectors are linearly dependent, the span will not be a subspace but rather a line or a plane.

5. Are there any limitations to using this method for subspace determination?

One limitation of using this method is that it only works for vector spaces in three-dimensional space. For higher dimensions, other methods such as finding the null space or column space of a matrix may be more efficient. Additionally, this method can only be used for finding subspaces spanned by a finite set of vectors, not for infinite sets.

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