Why do we need affine independence in the definition of a simplex?

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So we can think of forming an $m$-simplex in $mathbbR^n$ by taking $m+1$ affinely independent points in $mathbbR^n$ and then taking all convex combinations of them.



Here is a more formal definiton.



enter image description here



Now I can (sort of) visually see why we need the convexity condition. If simplices were invented to be triangles and tetrahedra in higher dimensions, we don't want our simplices to not be convex.



The best reason why I can come up with as to why we need our $m+1$ points to be affinely independent, is that since $m$ of those point will end up to be linearly independent (by definition of affine independence), when we take convex combinations (which are just special linear combinations) of those $m+1$ points, $m$ of those points being linearly independent will generate something that looks like an $m$-dimensional vector subspace of $mathbbR^n$ but isn't quite a vector space at all, I suppose that it would generate a $m$-dimensional topological manifold (with boundary).



Like for example consider the $2$-simplex $[(0, 0), (1, 0), (0, 1)]$ this gives a triangle in $mathbbR^2$ and linear independence of $(1, 0)$ and $(0, 1)$ ensures that we get something that's not just a line, but is two-dimensional when we take convex combinations of those points.



Am I correct in saying then that the affine independence condition is needed so that our notion of dimension for simplices corresponds with the topological manifold dimension if we view the simplices as a topological manifold (with boundary)?










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  • I think the reason for requiring affine independence is that you want the simplex to have full dimension, not live in a flat of lower dimension. The convexity isn't what's driving this part of the definition.
    – Ethan Bolker
    Sep 10 at 21:15











  • The short answer is Yes. The uniqueness of barycentric coordinates (given an ordering of the vertices), as in copper.hat's answer, is important; but even without that, the convex hull of a set of $m+1$ points in $mathbfR^n$ is $m$-dimensional if and only if the points are affinely independent.
    – Toby Bartels
    Sep 10 at 21:31










  • In the definition that you quoted, if you removed the "affine independent" requirement and allowed just any $m$ points in $mathbb R^n$, then, for example, every polygon in the plane $mathbb R^2$ would count as a simplex --- just take $p_0,dots,p_m$ to be the vertices of your polygon. Similarly, all polyhedra in higher dimensional spaces would count as simplices.
    – Andreas Blass
    Sep 11 at 1:52











  • @EthanBolker By dimension though I'm assuming that you mean the topological manifold dimension of the simplex, since we can't really talk about any other notion of dimension (I know we can define the dimension of the simplex in a certain way, but that definition leads to the result that the simplex dimension agrees with its dimension as a topological manifold)
    – Perturbative
    Sep 11 at 5:41










  • @Perturbative The simplex is an essentially linear object in real $n$ space so any reasonable definition of its dimension will be the dimension of the smallest Euclidean flat containing it. Affine independence implies that's the whole space Thinking of it as a manifold isn't usually useful since it has lots of corners. But if you must, it's full dimension that way too.
    – Ethan Bolker
    Sep 11 at 11:55














up vote
0
down vote

favorite












So we can think of forming an $m$-simplex in $mathbbR^n$ by taking $m+1$ affinely independent points in $mathbbR^n$ and then taking all convex combinations of them.



Here is a more formal definiton.



enter image description here



Now I can (sort of) visually see why we need the convexity condition. If simplices were invented to be triangles and tetrahedra in higher dimensions, we don't want our simplices to not be convex.



The best reason why I can come up with as to why we need our $m+1$ points to be affinely independent, is that since $m$ of those point will end up to be linearly independent (by definition of affine independence), when we take convex combinations (which are just special linear combinations) of those $m+1$ points, $m$ of those points being linearly independent will generate something that looks like an $m$-dimensional vector subspace of $mathbbR^n$ but isn't quite a vector space at all, I suppose that it would generate a $m$-dimensional topological manifold (with boundary).



Like for example consider the $2$-simplex $[(0, 0), (1, 0), (0, 1)]$ this gives a triangle in $mathbbR^2$ and linear independence of $(1, 0)$ and $(0, 1)$ ensures that we get something that's not just a line, but is two-dimensional when we take convex combinations of those points.



Am I correct in saying then that the affine independence condition is needed so that our notion of dimension for simplices corresponds with the topological manifold dimension if we view the simplices as a topological manifold (with boundary)?










share|cite|improve this question























  • I think the reason for requiring affine independence is that you want the simplex to have full dimension, not live in a flat of lower dimension. The convexity isn't what's driving this part of the definition.
    – Ethan Bolker
    Sep 10 at 21:15











  • The short answer is Yes. The uniqueness of barycentric coordinates (given an ordering of the vertices), as in copper.hat's answer, is important; but even without that, the convex hull of a set of $m+1$ points in $mathbfR^n$ is $m$-dimensional if and only if the points are affinely independent.
    – Toby Bartels
    Sep 10 at 21:31










  • In the definition that you quoted, if you removed the "affine independent" requirement and allowed just any $m$ points in $mathbb R^n$, then, for example, every polygon in the plane $mathbb R^2$ would count as a simplex --- just take $p_0,dots,p_m$ to be the vertices of your polygon. Similarly, all polyhedra in higher dimensional spaces would count as simplices.
    – Andreas Blass
    Sep 11 at 1:52











  • @EthanBolker By dimension though I'm assuming that you mean the topological manifold dimension of the simplex, since we can't really talk about any other notion of dimension (I know we can define the dimension of the simplex in a certain way, but that definition leads to the result that the simplex dimension agrees with its dimension as a topological manifold)
    – Perturbative
    Sep 11 at 5:41










  • @Perturbative The simplex is an essentially linear object in real $n$ space so any reasonable definition of its dimension will be the dimension of the smallest Euclidean flat containing it. Affine independence implies that's the whole space Thinking of it as a manifold isn't usually useful since it has lots of corners. But if you must, it's full dimension that way too.
    – Ethan Bolker
    Sep 11 at 11:55












up vote
0
down vote

favorite









up vote
0
down vote

favorite











So we can think of forming an $m$-simplex in $mathbbR^n$ by taking $m+1$ affinely independent points in $mathbbR^n$ and then taking all convex combinations of them.



Here is a more formal definiton.



enter image description here



Now I can (sort of) visually see why we need the convexity condition. If simplices were invented to be triangles and tetrahedra in higher dimensions, we don't want our simplices to not be convex.



The best reason why I can come up with as to why we need our $m+1$ points to be affinely independent, is that since $m$ of those point will end up to be linearly independent (by definition of affine independence), when we take convex combinations (which are just special linear combinations) of those $m+1$ points, $m$ of those points being linearly independent will generate something that looks like an $m$-dimensional vector subspace of $mathbbR^n$ but isn't quite a vector space at all, I suppose that it would generate a $m$-dimensional topological manifold (with boundary).



Like for example consider the $2$-simplex $[(0, 0), (1, 0), (0, 1)]$ this gives a triangle in $mathbbR^2$ and linear independence of $(1, 0)$ and $(0, 1)$ ensures that we get something that's not just a line, but is two-dimensional when we take convex combinations of those points.



Am I correct in saying then that the affine independence condition is needed so that our notion of dimension for simplices corresponds with the topological manifold dimension if we view the simplices as a topological manifold (with boundary)?










share|cite|improve this question















So we can think of forming an $m$-simplex in $mathbbR^n$ by taking $m+1$ affinely independent points in $mathbbR^n$ and then taking all convex combinations of them.



Here is a more formal definiton.



enter image description here



Now I can (sort of) visually see why we need the convexity condition. If simplices were invented to be triangles and tetrahedra in higher dimensions, we don't want our simplices to not be convex.



The best reason why I can come up with as to why we need our $m+1$ points to be affinely independent, is that since $m$ of those point will end up to be linearly independent (by definition of affine independence), when we take convex combinations (which are just special linear combinations) of those $m+1$ points, $m$ of those points being linearly independent will generate something that looks like an $m$-dimensional vector subspace of $mathbbR^n$ but isn't quite a vector space at all, I suppose that it would generate a $m$-dimensional topological manifold (with boundary).



Like for example consider the $2$-simplex $[(0, 0), (1, 0), (0, 1)]$ this gives a triangle in $mathbbR^2$ and linear independence of $(1, 0)$ and $(0, 1)$ ensures that we get something that's not just a line, but is two-dimensional when we take convex combinations of those points.



Am I correct in saying then that the affine independence condition is needed so that our notion of dimension for simplices corresponds with the topological manifold dimension if we view the simplices as a topological manifold (with boundary)?







linear-algebra general-topology algebraic-topology affine-geometry






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edited Sep 10 at 19:31

























asked Sep 10 at 19:21









Perturbative

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  • I think the reason for requiring affine independence is that you want the simplex to have full dimension, not live in a flat of lower dimension. The convexity isn't what's driving this part of the definition.
    – Ethan Bolker
    Sep 10 at 21:15











  • The short answer is Yes. The uniqueness of barycentric coordinates (given an ordering of the vertices), as in copper.hat's answer, is important; but even without that, the convex hull of a set of $m+1$ points in $mathbfR^n$ is $m$-dimensional if and only if the points are affinely independent.
    – Toby Bartels
    Sep 10 at 21:31










  • In the definition that you quoted, if you removed the "affine independent" requirement and allowed just any $m$ points in $mathbb R^n$, then, for example, every polygon in the plane $mathbb R^2$ would count as a simplex --- just take $p_0,dots,p_m$ to be the vertices of your polygon. Similarly, all polyhedra in higher dimensional spaces would count as simplices.
    – Andreas Blass
    Sep 11 at 1:52











  • @EthanBolker By dimension though I'm assuming that you mean the topological manifold dimension of the simplex, since we can't really talk about any other notion of dimension (I know we can define the dimension of the simplex in a certain way, but that definition leads to the result that the simplex dimension agrees with its dimension as a topological manifold)
    – Perturbative
    Sep 11 at 5:41










  • @Perturbative The simplex is an essentially linear object in real $n$ space so any reasonable definition of its dimension will be the dimension of the smallest Euclidean flat containing it. Affine independence implies that's the whole space Thinking of it as a manifold isn't usually useful since it has lots of corners. But if you must, it's full dimension that way too.
    – Ethan Bolker
    Sep 11 at 11:55
















  • I think the reason for requiring affine independence is that you want the simplex to have full dimension, not live in a flat of lower dimension. The convexity isn't what's driving this part of the definition.
    – Ethan Bolker
    Sep 10 at 21:15











  • The short answer is Yes. The uniqueness of barycentric coordinates (given an ordering of the vertices), as in copper.hat's answer, is important; but even without that, the convex hull of a set of $m+1$ points in $mathbfR^n$ is $m$-dimensional if and only if the points are affinely independent.
    – Toby Bartels
    Sep 10 at 21:31










  • In the definition that you quoted, if you removed the "affine independent" requirement and allowed just any $m$ points in $mathbb R^n$, then, for example, every polygon in the plane $mathbb R^2$ would count as a simplex --- just take $p_0,dots,p_m$ to be the vertices of your polygon. Similarly, all polyhedra in higher dimensional spaces would count as simplices.
    – Andreas Blass
    Sep 11 at 1:52











  • @EthanBolker By dimension though I'm assuming that you mean the topological manifold dimension of the simplex, since we can't really talk about any other notion of dimension (I know we can define the dimension of the simplex in a certain way, but that definition leads to the result that the simplex dimension agrees with its dimension as a topological manifold)
    – Perturbative
    Sep 11 at 5:41










  • @Perturbative The simplex is an essentially linear object in real $n$ space so any reasonable definition of its dimension will be the dimension of the smallest Euclidean flat containing it. Affine independence implies that's the whole space Thinking of it as a manifold isn't usually useful since it has lots of corners. But if you must, it's full dimension that way too.
    – Ethan Bolker
    Sep 11 at 11:55















I think the reason for requiring affine independence is that you want the simplex to have full dimension, not live in a flat of lower dimension. The convexity isn't what's driving this part of the definition.
– Ethan Bolker
Sep 10 at 21:15





I think the reason for requiring affine independence is that you want the simplex to have full dimension, not live in a flat of lower dimension. The convexity isn't what's driving this part of the definition.
– Ethan Bolker
Sep 10 at 21:15













The short answer is Yes. The uniqueness of barycentric coordinates (given an ordering of the vertices), as in copper.hat's answer, is important; but even without that, the convex hull of a set of $m+1$ points in $mathbfR^n$ is $m$-dimensional if and only if the points are affinely independent.
– Toby Bartels
Sep 10 at 21:31




The short answer is Yes. The uniqueness of barycentric coordinates (given an ordering of the vertices), as in copper.hat's answer, is important; but even without that, the convex hull of a set of $m+1$ points in $mathbfR^n$ is $m$-dimensional if and only if the points are affinely independent.
– Toby Bartels
Sep 10 at 21:31












In the definition that you quoted, if you removed the "affine independent" requirement and allowed just any $m$ points in $mathbb R^n$, then, for example, every polygon in the plane $mathbb R^2$ would count as a simplex --- just take $p_0,dots,p_m$ to be the vertices of your polygon. Similarly, all polyhedra in higher dimensional spaces would count as simplices.
– Andreas Blass
Sep 11 at 1:52





In the definition that you quoted, if you removed the "affine independent" requirement and allowed just any $m$ points in $mathbb R^n$, then, for example, every polygon in the plane $mathbb R^2$ would count as a simplex --- just take $p_0,dots,p_m$ to be the vertices of your polygon. Similarly, all polyhedra in higher dimensional spaces would count as simplices.
– Andreas Blass
Sep 11 at 1:52













@EthanBolker By dimension though I'm assuming that you mean the topological manifold dimension of the simplex, since we can't really talk about any other notion of dimension (I know we can define the dimension of the simplex in a certain way, but that definition leads to the result that the simplex dimension agrees with its dimension as a topological manifold)
– Perturbative
Sep 11 at 5:41




@EthanBolker By dimension though I'm assuming that you mean the topological manifold dimension of the simplex, since we can't really talk about any other notion of dimension (I know we can define the dimension of the simplex in a certain way, but that definition leads to the result that the simplex dimension agrees with its dimension as a topological manifold)
– Perturbative
Sep 11 at 5:41












@Perturbative The simplex is an essentially linear object in real $n$ space so any reasonable definition of its dimension will be the dimension of the smallest Euclidean flat containing it. Affine independence implies that's the whole space Thinking of it as a manifold isn't usually useful since it has lots of corners. But if you must, it's full dimension that way too.
– Ethan Bolker
Sep 11 at 11:55




@Perturbative The simplex is an essentially linear object in real $n$ space so any reasonable definition of its dimension will be the dimension of the smallest Euclidean flat containing it. Affine independence implies that's the whole space Thinking of it as a manifold isn't usually useful since it has lots of corners. But if you must, it's full dimension that way too.
– Ethan Bolker
Sep 11 at 11:55










1 Answer
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The point of affine independence is, as with linear independence, to ensure that the
representation of points in the affine hull is unique.



Some rambling follows in case it may be useful.



The affine hull of a set $P$ is the smallest affine set containing $P$. Alternatively,
$operatornameaff P = sum_k lambda = 1, p_k in P $, where the sums are finite.



(In the following, I implicitly assume that $sum_k lambda_k = 1$.)



If $x =sum_k lambda_k p_kin operatornameaff P$, the $lambda_k$ are called the barycentric coordinates. They are not necessarily unique, for example, with $P=-1,0,1$ we can write $0 = 1 cdot 0 = 1over 2 cdot (-1) + 1over 2 cdot 1$.



As with linear spaces, it is convenient if the coordinates are unique, if $P$ is affinely independent, then the (barycentric) coordinates are unique.



Note that $x in operatornameco P $ if there are barycentric non negative coordinates such that $x = sum_k lambda_k p_k$. If $P$ is affinely independent, then we can state that $x in operatornameco P $ iff the barycentric coordinates are non negative.



Note that in $mathbbR^n$ there are at most $n+1$ linearly independent points (cf. Carathéodory's theorem)






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    The point of affine independence is, as with linear independence, to ensure that the
    representation of points in the affine hull is unique.



    Some rambling follows in case it may be useful.



    The affine hull of a set $P$ is the smallest affine set containing $P$. Alternatively,
    $operatornameaff P = sum_k lambda = 1, p_k in P $, where the sums are finite.



    (In the following, I implicitly assume that $sum_k lambda_k = 1$.)



    If $x =sum_k lambda_k p_kin operatornameaff P$, the $lambda_k$ are called the barycentric coordinates. They are not necessarily unique, for example, with $P=-1,0,1$ we can write $0 = 1 cdot 0 = 1over 2 cdot (-1) + 1over 2 cdot 1$.



    As with linear spaces, it is convenient if the coordinates are unique, if $P$ is affinely independent, then the (barycentric) coordinates are unique.



    Note that $x in operatornameco P $ if there are barycentric non negative coordinates such that $x = sum_k lambda_k p_k$. If $P$ is affinely independent, then we can state that $x in operatornameco P $ iff the barycentric coordinates are non negative.



    Note that in $mathbbR^n$ there are at most $n+1$ linearly independent points (cf. Carathéodory's theorem)






    share|cite|improve this answer
























      up vote
      1
      down vote













      The point of affine independence is, as with linear independence, to ensure that the
      representation of points in the affine hull is unique.



      Some rambling follows in case it may be useful.



      The affine hull of a set $P$ is the smallest affine set containing $P$. Alternatively,
      $operatornameaff P = sum_k lambda = 1, p_k in P $, where the sums are finite.



      (In the following, I implicitly assume that $sum_k lambda_k = 1$.)



      If $x =sum_k lambda_k p_kin operatornameaff P$, the $lambda_k$ are called the barycentric coordinates. They are not necessarily unique, for example, with $P=-1,0,1$ we can write $0 = 1 cdot 0 = 1over 2 cdot (-1) + 1over 2 cdot 1$.



      As with linear spaces, it is convenient if the coordinates are unique, if $P$ is affinely independent, then the (barycentric) coordinates are unique.



      Note that $x in operatornameco P $ if there are barycentric non negative coordinates such that $x = sum_k lambda_k p_k$. If $P$ is affinely independent, then we can state that $x in operatornameco P $ iff the barycentric coordinates are non negative.



      Note that in $mathbbR^n$ there are at most $n+1$ linearly independent points (cf. Carathéodory's theorem)






      share|cite|improve this answer






















        up vote
        1
        down vote










        up vote
        1
        down vote









        The point of affine independence is, as with linear independence, to ensure that the
        representation of points in the affine hull is unique.



        Some rambling follows in case it may be useful.



        The affine hull of a set $P$ is the smallest affine set containing $P$. Alternatively,
        $operatornameaff P = sum_k lambda = 1, p_k in P $, where the sums are finite.



        (In the following, I implicitly assume that $sum_k lambda_k = 1$.)



        If $x =sum_k lambda_k p_kin operatornameaff P$, the $lambda_k$ are called the barycentric coordinates. They are not necessarily unique, for example, with $P=-1,0,1$ we can write $0 = 1 cdot 0 = 1over 2 cdot (-1) + 1over 2 cdot 1$.



        As with linear spaces, it is convenient if the coordinates are unique, if $P$ is affinely independent, then the (barycentric) coordinates are unique.



        Note that $x in operatornameco P $ if there are barycentric non negative coordinates such that $x = sum_k lambda_k p_k$. If $P$ is affinely independent, then we can state that $x in operatornameco P $ iff the barycentric coordinates are non negative.



        Note that in $mathbbR^n$ there are at most $n+1$ linearly independent points (cf. Carathéodory's theorem)






        share|cite|improve this answer












        The point of affine independence is, as with linear independence, to ensure that the
        representation of points in the affine hull is unique.



        Some rambling follows in case it may be useful.



        The affine hull of a set $P$ is the smallest affine set containing $P$. Alternatively,
        $operatornameaff P = sum_k lambda = 1, p_k in P $, where the sums are finite.



        (In the following, I implicitly assume that $sum_k lambda_k = 1$.)



        If $x =sum_k lambda_k p_kin operatornameaff P$, the $lambda_k$ are called the barycentric coordinates. They are not necessarily unique, for example, with $P=-1,0,1$ we can write $0 = 1 cdot 0 = 1over 2 cdot (-1) + 1over 2 cdot 1$.



        As with linear spaces, it is convenient if the coordinates are unique, if $P$ is affinely independent, then the (barycentric) coordinates are unique.



        Note that $x in operatornameco P $ if there are barycentric non negative coordinates such that $x = sum_k lambda_k p_k$. If $P$ is affinely independent, then we can state that $x in operatornameco P $ iff the barycentric coordinates are non negative.



        Note that in $mathbbR^n$ there are at most $n+1$ linearly independent points (cf. Carathéodory's theorem)







        share|cite|improve this answer












        share|cite|improve this answer



        share|cite|improve this answer










        answered Sep 10 at 21:13









        copper.hat

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