Geometrical Interpretation of V in Span S

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Discussion Overview

The discussion centers around the geometric interpretation of the concept of a vector V lying in the span of a set of vectors S. Participants explore the implications of this relationship in various dimensions, particularly in R^2 and R^3, and consider the nature of linear combinations and their geometric representations.

Discussion Character

  • Exploratory
  • Technical explanation
  • Conceptual clarification
  • Debate/contested

Main Points Raised

  • Some participants suggest that if V lies in span S, it means V can be expressed as a linear combination of the vectors in S, which geometrically represents a point in the space defined by those vectors.
  • One participant illustrates this with the example of two linearly independent vectors in R^2, stating that their linear combinations can cover the entire 2-dimensional space.
  • Another participant emphasizes that in R^3, two vectors define a plane, and any vector in the span of these two vectors lies within that plane.
  • Some participants note that if three vectors are not all in the same plane, they can span the entirety of 3-dimensional space.
  • There is a question raised about the motivation behind understanding spans and their applications, particularly in relation to linear algebra and fields like computational neuroscience.

Areas of Agreement / Disagreement

Participants generally agree on the geometric interpretations of spans in relation to vectors in R^2 and R^3. However, there is ongoing inquiry into the implications and applications of these concepts, indicating that the discussion remains open and exploratory.

Contextual Notes

Some participants express uncertainty regarding the applications of linear algebra and the extent of their own knowledge, which may limit the depth of the discussion on motivations and practical uses.

Who May Find This Useful

This discussion may be useful for students studying linear algebra, particularly those interested in geometric interpretations of vector spaces and their applications in fields such as digital processing and computational neuroscience.

Nano-Passion
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What does it mean geometrically to say that V lies in span S, in other words that V is in a linear combination of S?
 
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Let me just try and answer this (because i am studying the same thing and was trying to interpret it geometrically). Let us consider two objects (rather vectors, mind well not the ones that have mag. and direction) u1 and v1\in S, such that they are linearly independent. Example (1,1),(0,1). Or simply consider u1=(0,1) and v1=(1,0), (\hat{i}, \hat{j})and using these two ordered pair you can form all the other ordered pairs and extend it to the whole V.
It is like saying, a(1,0)+b(0,1)=(x,y), i.e. their linear combination gives the whole region occupied by ordered pair. that is same as saying these vectors u1 and v1 cover or span the whole vector space V2(2-d vector space in this case). this same idea can be extended to n-dimensional vector space.
It is also possible that with a span S(u1, u2, u3) you span a plane of 3-d vector space depending upon the vectors u1, u2, u3 (this case comes when one of the three is dependent on the other two).
hope this helps.
 
Geometrically, let's restrict ourselves to R^3. And let us say we are talking about the span of two vectors ##\vec{v}## and ##\vec{w}##. If you remember from earlier math classes, for any two vectors there exists one and only one plane such that both vectors lie in the plane.

This plane that they both lie in can be considered as the sum of all the points that are a linear combination of S, a.k.a. the sum of all points that can be made by adding a scalar multiple of ##\vec{v}## to a scalar multiple of ##\vec{w}##.

Therefore, if you had a third vector ##\vec{x}## that was in span(##\vec{v}##,##\vec{w}##), then you are saying that ##\vec{x}## is in that plane defined by ##\vec{w}## and ##\vec{v}##.

Edit: I brushed over some things, like the fact that if ##\vec{v}## and ##\vec{w}## are scalar multiples of each other (or if one is the zero vector) then this doesn't quite work, but hopefully you get the idea.
 
Vorde said:
Geometrically, let's restrict ourselves to R^3. And let us say we are talking about the span of two vectors ##\vec{v}## and ##\vec{w}##. If you remember from earlier math classes, for any two vectors there exists one and only one plane such that both vectors lie in the plane.

This plane that they both lie in can be considered as the sum of all the points that are a linear combination of S, a.k.a. the sum of all points that can be made by adding a scalar multiple of ##\vec{v}## to a scalar multiple of ##\vec{w}##.

Therefore, if you had a third vector ##\vec{x}## that was in span(##\vec{v}##,##\vec{w}##), then you are saying that ##\vec{x}## is in that plane defined by ##\vec{w}## and ##\vec{v}##.

Edit: I brushed over some things, like the fact that if ##\vec{v}## and ##\vec{w}## are scalar multiples of each other (or if one is the zero vector) then this doesn't quite work, but hopefully you get the idea.


Thanks! So essentially V lies in Span S if it also lies in the plane of S.

You gave me an example of two vectors laying in the plane. But what about when there are three vectors in Span S that do not all lie in a common plane?
 
Geometrically, you can think of span S as the set of all points that you can reach from the origin, traveling only in directions parallel to the vectors in S.

If S contains two vectors that define a plane, you can get to every point in the plane.

If S contains more than two vectors all in the same plane, that makes no difference - you still can't get to any point that is NOT in the plane.

If S contains three vectors not all in the same plane, you can get to any point in 3-dimensional space.
 
AlephZero said:
Geometrically, you can think of span S as the set of all points that you can reach from the origin, traveling only in directions parallel to the vectors in S.

If S contains two vectors that define a plane, you can get to every point in the plane.

If S contains more than two vectors all in the same plane, that makes no difference - you still can't get to any point that is NOT in the plane.

If S contains three vectors not all in the same plane, you can get to any point in 3-dimensional space.

Thanks.

So literally the geometric interpretation is that V lies in S, in which S itself spans a 3-dimensional place. Now can I politely ask, what is the motivation behind this? What does it apply to?
 
Nano-Passion said:
Now can I politely ask, what is the motivation behind this? What does it apply to?

It's very hard to give an answer when we don't know how much you know already.

How much linear algebra have you studied? What applications of LA as a whole (not just this topic) do you know about?
 
AlephZero said:
It's very hard to give an answer when we don't know how much you know already.

How much linear algebra have you studied? What applications of LA as a whole (not just this topic) do you know about?

Just an introductory linear algebra class. I don't know much about applications of LA first hand, but I do know it is applied in many things that involves a large numbers of computations, things such as digital processing to be specific, or computational neuroscience to be general (I plan to pursue that field or mathematical neuroscience). Mathematically, LA has applications in fields such as topology.
 

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