5.6. Barycenters
This page is under construction.
Conceiving affine and vector
spaces as ℝ-duality systems, reduces the issue of formalizing
affine and linear geometries, to the following questions:
- Describing ℝ with its algebraic structures, and its axioms (including second-order ones);
- We shall accept all duality morphisms.
Works of functional analysis involving more primitive structures to restrict the
class of morphisms, are beyond the scope of this exposition.
- Specify the axioms (criteria to accept duality systems as spaces): E
and E' will be made algebras by stability axioms
E ∈ Sub ℝE' and E' ∈ Sub ℝE,
from different algebraic structures on ℝ which we have to describe.
That will be all for us.
More about basis
Properties of trajectories have
generalizations to other arities, as follows. Consider a concrete category having for
every n∈ℕ a space with a basis of n elements. They form together a language
L that is a clone of operations which means, generalizing
the concept of monoid, that all operations defined by L-terms also belong to
L....
Vector spaces
Linear geometry can be conceived as equivalent
to affine geometry with an additional constant symbol 0
called origin or zero (no additional axiom
could be relevant since affine groups have only one orbit):
- A vector space is an affine
space E with a chosen point 0E called "origin"
- A linear map between vector spaces E and F
is an affine map f such that f(0E) = 0F.
- A subspace of a vector space E is an affine subspace of E containing
0E (so by definition, each subspace is an affine subspace but not conversely)
- Subspaces can be used in the role of directions, as any direction contains a unique subspace.
This does not formalize linear geometry, as we did not formalize affine geometry here assumed.
Optimal formalizations of linear geometry do not even go this way, but logically come first,
as affine geometry can be more usefully formalized using it.
Indeed, affine subspaces F of vector spaces E are still affine spaces:
affine structures of F are definable from linear structures of E
with the choice of F, in the sense that the group GF⊂GLE
of automorphisms of E which preserve F, is morphed by restriction into Aff F.
Now for this to form an equivalent presentation of the affine geometry of F, this morphism from GF
to Aff F must be bijective:
- 0E∉F (gives surjectivity : the choice of 0E
is not structuring for F).
- Then F must be an hyperplane (to give injectivity).
Basis of affine spaces
Now let us start a proper formalization of affine and linear geometries in terms of basis.
A fundamental feature of affine geometry is that for any n∈ℕ,
n-dimensional spaces have basis of n+1 elements, and any point belongs to some basis.
Then a possible presentation of linear geometry (but not the most formally convenient),
The barycenter of points x and y with
coefficients (1-a) and a is the image of a by
the unique affine map from ℝ
to M which sends 0 to x and 1 to y.
Middles of segments are defined from barycenters.
k-dimensional subspaces are generated by a
set of k+1 points but not generated by any set of k
points or less.
A subset F of an affine space E
is a subspace of E, if and only if ∀a,b∈F,
a≠b ⇒ a∨b ⊂ F.
An equivalent condition for F ⊂ E to be an hyperplane is ∃a∈E\F, E = F∨a, which implies
∀a∈E\F, E = F∨a.
Generally ∀F ∈S(E), ∀a∈E\F,
Dim(F∨a) = Dim(F)+1.
Vector spaces in duality
A pair of dual vector spaces, is a particular case of duality system.
It is a pair of sets (E,E'), where the elements of E
are called vectors, those of E' are called covectors
(or linear forms) together with an operation of scalar
product from E×E' to ℝ : for each u∈E and x∈E', we have u⋅x∈ℝ,
and that is subject to the following axioms:
We have a zero element in E, whose scalar product with any
element of E' is zero; and a zero element of E', whose scalar
product by any element of E is zero. We shall abusively denote the
zeros of all sets by the same symbol 0, letting their precise
identity be given by the operations where they are used, as this
won't cause any ambiguity:
- ∀x∈E', 0⋅x = 0
- ∀u∈E', u⋅0 = 0
We define an operation of addition in E as the addition of
the scalar products with any element of E' ; and the same in E'.
Formally:
- ∀u,v∈E, ∀x∈E', (u+v)⋅x = u⋅x + v⋅x
- ∀x,y∈E', ∀u∈E, u⋅(x+y) = u⋅x + u⋅y
In other words : for all u,v∈E, the function from E' to R defined
by (x ↦ u⋅x + v⋅x) "belongs to" (or : is represented through the
scalar product by) an element of E that is denoted u+v.
We define an operation of multiplication of elements of E by any
real number, as multiplying by the same number, the scalar product
with any element of E'. And the same in E'. Formally :
- ∀a∈ℝ, ∀u∈E, ∀x∈E', (au)⋅x = a(u⋅x) = u⋅(ax)
Remark : the zero element of E can as well be obtained from any
element u of E by the multiplication by 0∈ℝ: 0 = 0u. But declaring
the constant 0∈E further says that E is nonempty.
The above definitions of the operations in E can also be
equivalently expressed in the following two ways
- E represents (though the scalar product) a vector subspace of
the space of functions from E' to ℝ. (stable by addition and
multiplication by a scalar).
- E is a vector space, and the elements of E' represent linear
functions from E to ℝ.
(the below will be reworked later)
A subspace is a subalgebra
(i.e. stable) for addition and multiplication by a number.
Note that (as for any duality
system) from any pair (E,E') with an operation from E×E' to ℝ
we can produce a pair of spaces in duality by replacing E by the
vector space generated by its image in ℝE', and the same
for E'. This can be done in any order without affecting the result
and indeed gives a pair of dual vector spaces by doing this
replacement just once on each side, because this replacement for E
does not affect the linear relations in E' (relations in E' that are
true in ℝE remain true when replacing E by the vector
space generated by its image in ℝE'), thanks to the
algebraic relations between addition and multiplication
(commutativity, associativity, distributivity).
If (E,E') is a pair of dual spaces and E is finite-dimensional then
E' is the space of all linear forms on E and has the same dimension.
There are counter-examples in the infinite-dimensional case. For
example take E = E' = the set of continuous maps from [-1,1] to ℝ,
and the operation of integral of the product of these functions.
Then the Dirac mass in 0 (or in any other point of [0,1], which maps
any f in E to f(0), is outside E'. It may still be understood as a
limit of a sequence of elements of E'.
(This page will be later expanded to further details)
Note : instead of ℝ we may as well take ℂ or generally any field.
Eventually some other commutative ring may be used but this can make
some of the below constructions fail)
Orthogonality
Preimages of 0 (or any number) by non-constant affine forms, are the closed hyperplanes.
Let us see
how the previously mentioned pathological D is dismissed, not only when
viewed from a set theory without AC (but only DC), but by the duality structure itself which
can somehow express the idea of rejecting AC regardless the rest of universe.
Up: 5. Geometry
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