Algebraic Geometry
Contents
6.1. Algebraic Geometry#
This section covers essential notions and facts from algebraic geometry needed for these notes. For a systematic introduction to the subject, see [44, 45, 47]. Algebraic geometry is the study of geometries that come from algebra. The geometrical objects being studied are the solution sets of systems of multivariate polynomial equations. A data set being studied can be thought of as a collection of sample points from a geometrical object (e.g. a union of subspaces). The objective is to infer the said geometrical object from the given data set and decompose the object into simpler objects which help in better understanding of the data set.
6.1.1. Polynomial Rings#
Let
be -dimensional vector space where is either or (a field of characteristic 0).For
, let be the set of all polynomials of variables . is a commutative ring [3].A monomial is a product of variables. Its degree is the number of variables in the product.
A monomial of degree
is of the form with and .There are a total of
different degree- monomials.We now construct an embedding of vectors in
to .The Veronese map of degree
, denoted as , is defined aswhere
are degree-n monomials chosen in the degree lexicographic order.For example, the Veronese map of degree 2 from
to is defined asA term is a scalar multiplying a monomial.
A polynomial
is said to be homogeneous if all its terms have the same degree.Homogeneous polynomials are also known as forms.
A linear form is a homogeneous polynomial of degree 1.
A quadratic form is a homogeneous polynomial of degree 2.
A degree-n form
can be written aswhere
are the coefficients associated with the monomials .A projective space corresponding to a vector space
is the set of lines passing through its origin (the one dimensional subspaces).Each such line can be represented by any non-zero point on the line.
For a degree-n form
and a scalar , we have:Therefore, if
, then and the zero-set of includes the one dimensional subspace containing (the line passing through and ).Our interest is in the zero sets of homogeneous polynomials.
Thus, it is useful to view
as a projective space.For a form
, is always 0.If
for some , then .The ring
can be viewed as a graded ring [56] and decomposed as(6.1)#where
consists of all homogeneous polynomials of degree . is the set of scalars (polynomials of degree 0). is the set of all 1-forms:Note that the polynomial
is included in every .This enables us to treat
as a vector space of -forms. can also be viewed as the dual-space of linear functionals for the vector space .We will also need following sets later:
An ideal in the ring
is an additive subgroup such that if and , then . is a trivial ideal. is called a proper ideal if .A proper ideal
is called maximal if no other proper ideal of contains .An ideal
is called a subideal of an ideal if .If
and are two ideals in , then is also an ideal.An ideal
is said to be generated by a subset , if every can be written asIt is denoted by
.If
is finite, , then the generated ideal is also denoted by .An ideal generated by a single element
is called a principal ideal denoted by .Given two ideals
and , the ideal that is generated by product of elements in and : is called the product ideal .A prime ideal is similar to prime numbers in the ring of integers.
A proper ideal
is called prime if implies that or .A polynomial
is said to be prime or irreducible if it generates a prime ideal.A homogeneous ideal of
is an ideal generated by homogeneous polynomials.
6.1.2. Algebraic Sets#
Given a set of homogeneous polynomials
, a corresponding projective algebraic set is defined asIn other words,
is the zero set of polynomials in (intersection of zero sets of each polynomial in ).Let
and be sets of homogeneous polynomials and and such that .Then
is called an algebraic subset of .A nonempty algebraic set is called irreducible if it is not the union of two nonempty smaller algebraic sets.
An irreducible algebraic set is also known as algebraic variety.
Any subspace of
is an algebraic variety.Given any subset
, we define the vanishing ideal of as the set of all polynomials that vanish on .It is easy to see that if
, then for all .Thus,
is indeed an ideal.
Let
be a set of homogeneous polynomials. is the zero set of (an algebraic set). is the vanishing ideal of the zero set of .It can be shown that
is an ideal that contains .Similarly, let
be an arbitrary set of vectors in . is the vanishing ideal of and is the zero set of the vanishing ideal of .Then,
is an algebraic set that contains .
It turns out that irreducible algebraic sets and
prime ideals are connected. In fact, If
The natural progression is to look for a one-to-one correspondence between ideals and algebraic sets. The concept of a radical ideal is useful in this context.
Given a (homogeneous) ideal
of , the *(homogeneous) radical ideal * of is defined to be is an ideal in itself and . is a fixed-point in the sense that .Also, if
is homogeneous, then so is . 1 A theorem by Hilbert suggests the following: If is an algebraically closed field (e.g. ) and is an (homogeneous) ideal, thenThus, the mappings
and induce a one-to-one correspondence between the collection of (projective) algebraic sets of and (homogeneous) radical ideals of .This result is known as Nullstellensatz.
6.1.3. Algebraic Sampling Theory#
We will now explore the problem of identifying
a (projective) algebraic set
In general, the algebraic set
may not be irreducible and the ideal may not be prime.Let
be the finite (but sufficiently large) set of sample points from for the following discussion.For an arbitrary point
, we abuse to mean the corresponding projective point (i.e. the line passing between 0 and ).Let
be the vanishing ideal of (the line) .Then,
is a submaximal ideal (i.e. it cannot be a subideal of any other homogeneous ideal of ). Let be the vanishing ideal of . Then the vanishing ideal for the set of points isThis is a radical ideal and is in general much larger than
.In order to ensure that we can infer
correctly from the set of samples , we need some additional constraints.We require that
is generated by a set of (homogeneous) polynomials whose degrees are bound by a relatively small .Then, the zero set of
is given byIn general,
is always a proper subideal of regardless of how large is.We introduce an algebraic sampling theorem which comes to our rescue.
It suggests that if
is generated by polynomials in , then there is a finite sequence of points such that the subspace generates .While the theorem doesn’t suggest a bound on
, it turns out that with probability one, the vanishing ideal of an algebraic set can be correctly determined from a randomly chosen sequence of samples.This theorem is analogous to the classical Nyquist-Shannon sampling theorem.
So far we have looked at modeling a data set as an algebraic
set and obtaining its vanishing ideal.
The next step is to extract the internal geometric
or algebraic structure of the algebraic set.
The idea is to find simpler (possibly irreducible)
algebraic sets which can be composed to form the given algebraic
set. For example, if an algebraic set is a union of subspaces,
then we would like to find out the component subspaces. In other
words, given an algebraic set
An algebraic set can have only finitely many irreducible components.
In other words, there exists a finite
such thatwhere
are irreducible algebraic varieties.The vanishing ideal
must be a prime ideal that is minimal over the radical ideal (i.e. there is no prime subideal of ) that includes .The ideal
is given byThis is known as the minimal primary decomposition of the radical ideal
.Given a (projective) algebraic set
and its vanishing ideal , we can grade the ideal by degree as:The Hilbert function of
is defined to be(6.2)# denotes the number of linearly independent polynomials of degree that vanish on .Hilbert series of an ideal
is defined as the power series:
6.1.4. Subspace Arrangements#
We are interested in special class of algebraic sets known as
subspace arrangements in
A subspace arrangement is a finite collection of linear or affine subspaces in
.The set
is the union of subspaces.It is an algebraic set.
We will explore the algebraic properties of
in the following.We say a subspace arrangement is central if every subspace passes through origin.
In the sequel, we will focus on central subspace arrangements only.
A
-dimensional subspace can be defined by linearly independent linear forms :Let
denote the vector space of all linear forms that vanish on .Then
. is the zero set of (i.e. .The vanishing ideal of
is is an ideal generated by linear forms in .It contains polynomials of all degrees that vanish on
.Every polynomial
can be written aswhere
. is a prime ideal.The vanishing ideal of the subspace arrangement
isThe ideal can be graded by degree of the polynomial as:
(6.3)#Each
is a vector space that contains forms of degree in and is the least degree of the polynomials in .The sequence of dimensions of
is the Hilbert function of .Based on a result on the regularity of subspace arrangements [27], the subspace arrangement
is uniquely determined as the zero set of all polynomials of degree up to in its vanishing ideal. i.e.Thus, we don’t really need to determine polynomials of higher degree.
We need to characterize
further.Recall that
is a (linear) subspace and is the vector space of linear forms which vanish on .We can construct a product of linear forms by choosing one linear form from each
.Let
be the ideal generated by the products of linear formsEquivalently, we can say that :
is the product ideal of the vanishing ideals of each of the subspaces.
Evidently,
is a subideal in .In fact, the two ideals share the same zero set:
Now,
is the largest ideal which vanishes on .In fact,
is the radical ideal of .Now, just like we graded
, we can also grade as:Note that, the lowest degree of polynomials is always
which is the number of subspaces in .Hilbert function of
is denoted as .It turns out that Hilbert functions of the vanishing ideal
and the product ideal have interesting and useful relationships.
6.1.5. Subspace Embeddings#
Let
be another (central) subspace arrangement such that .Then it is necessary that for each
, there exists such that .We call
, a subspace embedding.If
happens to be hyperplane arrangement, we call the embedding as a hyperplane embedding.Let us consider how to create a hyperplane embedding for a given subspace arrangement.
In general, the zero set of each homogeneous component of
(i.e. ), need not be a subspace embedding of .In fact, it may not even be a subspace arrangement.
However, the derivatives of the polynomials in
come to our rescue.We denote the derivative of
w.r.t. by .Consider a polynomial
.Pick a point
from each subspace ( ).Compute the derivative of
and evaluate it at as .Now, construct the hyperplane
.Recall that the derivative of a smooth function
is orthogonal to (the tangent space of) its level set .Thus,
contains .It turns out that if the
points (from each subspace) are in general position, then the union of hyperplanes is a hyperplane embedding of the subspace arrangement .For each polynomial in
, we can construct a hyperplane embedding of the subspace arrangement .The intersection of hyperplane embeddings constructed from a collection of polynomials in
is a subspace embedding of .When this collection of polynomials contains all the generators of
, the subspace embedding becomes tight.In fact, the resulting subspace arrangement coincides with the original one.
An ideal is said to be pl-generated if it is generated by products of linear forms.
The
defined above is a pl-generated ideal.If the ideal of a subspace arrangement
is pl-generated, then the zero-set of every generator gives a hyperplane embedding of .If
is a hyperplane arrangement, then is always pl-generated as it is generated by a single polynomial of the form where are the normal vectors to the hyperplanes in the arrangement.In fact, it is also a principal ideal.
The vanishing ideal of a single subspace is always pl-generated.
The vanishing ideal of an arrangement of two subspaces is also pl-generated but this is not true in general.
But something can be said if the
subspaces in the arrangement are in general position.
6.1.6. Hilbert Functions of Subspace Arrangements#
If a subspace arrangement