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In
algebraic geometry Algebraic geometry is a branch of mathematics which uses abstract algebraic techniques, mainly from commutative algebra, to solve geometry, geometrical problems. Classically, it studies zero of a function, zeros of multivariate polynomials; th ...
, Bézout's theorem is a statement concerning the number of common zeros of
polynomial In mathematics, a polynomial is a Expression (mathematics), mathematical expression consisting of indeterminate (variable), indeterminates (also called variable (mathematics), variables) and coefficients, that involves only the operations of addit ...
s in indeterminates. In its original form the theorem states that ''in general'' the number of common zeros equals the product of the degrees of the polynomials. It is named after Étienne Bézout. In some elementary texts, Bézout's theorem refers only to the case of two variables, and asserts that, if two plane algebraic curves of degrees d_1 and d_2 have no component in common, they have d_1d_2 intersection points, counted with their multiplicity, and including points at infinity and points with
complex Complex commonly refers to: * Complexity, the behaviour of a system whose components interact in multiple ways so possible interactions are difficult to describe ** Complex system, a system composed of many components which may interact with each ...
coordinates. In its modern formulation, the theorem states that, if is the number of common points over an
algebraically closed field In mathematics, a field is algebraically closed if every non-constant polynomial in (the univariate polynomial ring with coefficients in ) has a root in . In other words, a field is algebraically closed if the fundamental theorem of algebra ...
of projective hypersurfaces defined by homogeneous polynomials in indeterminates, then is either infinite, or equals the product of the degrees of the polynomials. Moreover, the finite case occurs almost always. In the case of two variables and in the case of affine hypersurfaces, if multiplicities and points at infinity are not counted, this theorem provides only an upper bound of the number of points, which is almost always reached. This bound is often referred to as the Bézout bound. Bézout's theorem is fundamental in
computer algebra In mathematics and computer science, computer algebra, also called symbolic computation or algebraic computation, is a scientific area that refers to the study and development of algorithms and software for manipulating expression (mathematics), ...
and effective
algebraic geometry Algebraic geometry is a branch of mathematics which uses abstract algebraic techniques, mainly from commutative algebra, to solve geometry, geometrical problems. Classically, it studies zero of a function, zeros of multivariate polynomials; th ...
, by showing that most problems have a computational complexity that is at least exponential in the number of variables. It follows that in these areas, the best complexity that can be hoped for will occur with algorithms that have a complexity that is polynomial in the Bézout bound.


History

In the case of plane curves, Bézout's theorem was essentially stated by
Isaac Newton Sir Isaac Newton () was an English polymath active as a mathematician, physicist, astronomer, alchemist, theologian, and author. Newton was a key figure in the Scientific Revolution and the Age of Enlightenment, Enlightenment that followed ...
in his proof of Lemma 28 of volume 1 of his '' Principia'' in 1687, where he claims that two curves have a number of intersection points given by the product of their degrees. However, Newton had stated the theorem as early as 1665. The general theorem was later published in 1779 in Étienne Bézout's ''Théorie générale des équations algébriques''. He supposed the equations to be "complete", which in modern terminology would translate to generic. Since with generic polynomials, there are no points at infinity, and all multiplicities equal one, Bézout's formulation is correct, although his proof does not follow the modern requirements of rigor. This and the fact that the concept of intersection multiplicity was outside the knowledge of his time led to a sentiment expressed by some authors that his proof was neither correct nor the first proof to be given. The proof of the statement that includes multiplicities requires an accurate definition of the intersection multiplicities, and was therefore not possible before the 20th century. The definitions of multiplicities that was given during the first half of the 20th century involved continuous and infinitesimal deformations. It follows that the proofs of this period apply only over the field of complex numbers. It is only in 1958 that Jean-Pierre Serre gave a purely algebraic definition of multiplicities, which led to a proof valid over any algebraically closed field. Modern studies related to Bézout's theorem obtained different upper bounds to system of polynomials by using other properties of the polynomials, such as the Bernstein–Kushnirenko theorem, or generalized it to a large class of functions, such as Nash functions.


Statement


Plane curves

Suppose that ''X'' and ''Y'' are two plane projective curves defined over a field ''F'' that do not have a common component (this condition means that ''X'' and ''Y'' are defined by polynomials, without common divisor of positive degree). Then the total number of intersection points of ''X'' and ''Y'' with coordinates in an
algebraically closed field In mathematics, a field is algebraically closed if every non-constant polynomial in (the univariate polynomial ring with coefficients in ) has a root in . In other words, a field is algebraically closed if the fundamental theorem of algebra ...
''E'' that contains ''F'', counted with their multiplicities, is equal to the product of the degrees of ''X'' and ''Y''.


General case

The generalization in higher dimension may be stated as: Let ''n'' projective hypersurfaces be given in a projective space of dimension ''n'' over an algebraically closed field, which are defined by ''n'' homogeneous polynomials in ''n'' + 1 variables, of degrees d_1, \ldots,d_n. Then either the number of intersection points is infinite, or the number of intersection points, counted with multiplicity, is equal to the product d_1 \cdots d_n. If the hypersurfaces are in relative general position, then there are d_1 \cdots d_n intersection points, all with multiplicity 1. There are various proofs of this theorem, which either are expressed in purely algebraic terms, or use the language of
algebraic geometry Algebraic geometry is a branch of mathematics which uses abstract algebraic techniques, mainly from commutative algebra, to solve geometry, geometrical problems. Classically, it studies zero of a function, zeros of multivariate polynomials; th ...
. Three algebraic proofs are sketched below. Bézout's theorem has been generalized as the so-called multi-homogeneous Bézout theorem.


Affine case

The affine case of the theorem is the following statement, that was proven in 1983 by David Masser and Gisbert Wüstholz. ''Consider affine hypersurfaces that are defined over an algebraically closed field by polynomials in variables, of degrees d_1, \ldots,d_n. Then either the number of intersection points is infinite, or the number of intersection points, counted with their multiplicities, is at most the product d_1 \cdots d_n.'' If the hypersurfaces are in relative general position, then there are exactly d_1 \cdots d_n intersection points, all with multiplicity 1. The last assertion is a corollary of Bézout's theorem, but the first assertion is not, because of the possibility of a finite number of intersection points in the affine space, together with infinitely many intersection points at infinity. This theorem a corollary, not explicitly stated, of a more general statement proved by Masser and Wüstholz. For stating the general result, one has to recall that the intersection points form an algebraic set, and that there is a finite number of intersection points if and only if all component of the intersection have a zero
dimension In physics and mathematics, the dimension of a mathematical space (or object) is informally defined as the minimum number of coordinates needed to specify any point within it. Thus, a line has a dimension of one (1D) because only one coo ...
(an algebraic set of positive dimension has an infinity of points over an algebraically closed field). An intersection point is said ''isolated'' if it does not belong to a component of positive dimension of the intersection; the terminology make sense, since an isolated intersection point has neighborhoods (for Zariski topology or for the usual topology in the case of complex hypersurfaces) that does not contain any other intersection point. Consider projective hypersurfaces that are defined over an algebraically closed field by homogeneous polynomials in n+1 variables, of degrees d_1, \ldots,d_n. Then, the sum of the multiplicities of their isolated intersection points is at most the product d_1 \cdots d_n. The result remains valid for any number of hypersurfaces, if one sets d_=0 in the case m and, otherwise, if one orders the degrees for having d_2\ge d_3\ge\cdots \ge d_m \ge d_1. That is, there is no isolated intersection point if m and, otherwise, the bound is the product of the smallest degree and the n-1 largest degrees.


Examples (plane curves)


Two lines

The equation of a line in a
Euclidean plane In mathematics, a Euclidean plane is a Euclidean space of Two-dimensional space, dimension two, denoted \textbf^2 or \mathbb^2. It is a geometric space in which two real numbers are required to determine the position (geometry), position of eac ...
is
linear In mathematics, the term ''linear'' is used in two distinct senses for two different properties: * linearity of a '' function'' (or '' mapping''); * linearity of a '' polynomial''. An example of a linear function is the function defined by f(x) ...
, that is, it equates a
polynomial In mathematics, a polynomial is a Expression (mathematics), mathematical expression consisting of indeterminate (variable), indeterminates (also called variable (mathematics), variables) and coefficients, that involves only the operations of addit ...
of degree one to zero. So, the Bézout bound for two lines is , meaning that two lines either intersect at a single point, or do not intersect. In the latter case, the lines are parallel and meet at a point at infinity. One can verify this with equations. The equation of a first line can be written in slope-intercept form y=sx+m or, in projective coordinates y=sx+mt (if the line is vertical, one may exchange and ). If the equation of a second line is (in projective coordinates) ax+by+ct=0, by substituting sx+mt for in it, one gets (a+bs)x + (c+bm)t=0. If a+bs\ne 0, one gets the -coordinate of the intersection point by solving the latter equation in and putting If a+bs= 0, that is s=-a/b, the two line are parallel as having the same slope. If m\ne -c/b, they are distinct, and the substituted equation gives . This gives the point at infinity of projective coordinates .


A line and a curve

As above, one may write the equation of the line in projective coordinates as y=sx+mt. If curve is defined in projective coordinates by a homogeneous polynomial p(x,y,t) of degree , the substitution of provides a homogeneous polynomial of degree in and . The fundamental theorem of algebra implies that it can be factored in linear factors. Each factor gives the ratio of the and coordinates of an intersection point, and the multiplicity of the factor is the multiplicity of the intersection point. If is viewed as the ''coordinate of infinity'', a factor equal to represents an intersection point at infinity. If at least one partial derivative of the polynomial is not zero at an intersection point, then the tangent of the curve at this point is defined (see ), and the intersection multiplicity is greater than one if and only if the line is tangent to the curve. If all partial derivatives are zero, the intersection point is a singular point, and the intersection multiplicity is at least two.


Two conic sections

Two
conic section A conic section, conic or a quadratic curve is a curve obtained from a cone's surface intersecting a plane. The three types of conic section are the hyperbola, the parabola, and the ellipse; the circle is a special case of the ellipse, tho ...
s generally intersect in four points, some of which may coincide. To properly account for all intersection points, it may be necessary to allow complex coordinates and include the points on the infinite line in the projective plane. For example: *Two circles never intersect in more than two points in the plane, while Bézout's theorem predicts four. The discrepancy comes from the fact that every circle passes through the same two complex points on the line at infinity. Writing the circle (x-a)^2+(y-b)^2 = r^2 in homogeneous coordinates, we get (x-az)^2+(y-bz)^2 - r^2z^2 = 0, from which it is clear that the two points and lie on every circle. When two circles do not meet at all in the real plane, the two other intersections have non-real coordinates, or if the circles are concentric then they meet at exactly the two points on the line at infinity with an intersection multiplicity of two. *Any conic should meet the line at infinity at two points according to the theorem. A hyperbola meets it at two real points corresponding to the two directions of the asymptotes. An ellipse meets it at two complex points, which are conjugate to one anotherin the case of a circle, the points and . A parabola meets it at only one point, but it is a point of tangency and therefore counts twice. *The following pictures show examples in which the circle meets another ellipse in fewer intersection points because at least one of them has multiplicity greater than one:


Multiplicity

The concept of multiplicity is fundamental for Bézout's theorem, as it allows having an equality instead of a much weaker inequality. Intuitively, the multiplicity of a common zero of several polynomials is the number of zeros into which the common zero can split when the coefficients are slightly changed. For example, a tangent to a curve is a line that cuts the curve at a point that splits in several points if the line is slightly moved. This number is two in general (ordinary points), but may be higher (three for inflection points, four for undulation points, etc.). This number is the "multiplicity of contact" of the tangent. This definition of a multiplicities by deformation was sufficient until the end of the 19th century, but has several problems that led to more convenient modern definitions: Deformations are difficult to manipulate; for example, in the case of a
root In vascular plants, the roots are the plant organ, organs of a plant that are modified to provide anchorage for the plant and take in water and nutrients into the plant body, which allows plants to grow taller and faster. They are most often bel ...
of a univariate polynomial, for proving that the multiplicity obtained by deformation equals the multiplicity of the corresponding linear factor of the polynomial, one has to know that the roots are
continuous function In mathematics, a continuous function is a function such that a small variation of the argument induces a small variation of the value of the function. This implies there are no abrupt changes in value, known as '' discontinuities''. More preci ...
s of the coefficients. Deformations cannot be used over fields of positive characteristic. Moreover, there are cases where a convenient deformation is difficult to define (as in the case of more than two plane curves having a common intersection point), and even cases where no deformation is possible. Currently, following Jean-Pierre Serre, a multiplicity is generally defined as the
length Length is a measure of distance. In the International System of Quantities, length is a quantity with Dimension (physical quantity), dimension distance. In most systems of measurement a Base unit (measurement), base unit for length is chosen, ...
of a
local ring In mathematics, more specifically in ring theory, local rings are certain rings that are comparatively simple, and serve to describe what is called "local behaviour", in the sense of functions defined on algebraic varieties or manifolds, or of ...
associated with the point where the multiplicity is considered. Most specific definitions can be shown to be special case of Serre's definition. In the case of Bézout's theorem, the general intersection theory can be avoided, as there are proofs (see below) that associate to each input data for the theorem a polynomial in the coefficients of the equations, which factorizes into linear factors, each corresponding to a single intersection point. So, the multiplicity of an intersection point is the multiplicity of the corresponding factor. The proof that this multiplicity equals the one that is obtained by deformation, results then from the fact that the intersection points and the factored polynomial depend continuously on the roots.


Proofs


Using the resultant (plane curves)

Let and be two homogeneous polynomials in the indeterminates of respective degrees and . Their zeros are the homogeneous coordinates of two projective curves. Thus the homogeneous coordinates of their intersection points are the common zeros of and . By collecting together the powers of one indeterminate, say , one gets univariate polynomials whose coefficients are homogeneous polynomials in and . For technical reasons, one must apply a change of coordinates so the degrees in of and equal their total degrees ( and ), and each line passing through two intersection points does not pass through the point (this means that no two point have the same Cartesian -coordinate. The
resultant In mathematics, the resultant of two polynomials is a polynomial expression of their coefficients that is equal to zero if and only if the polynomials have a common root (possibly in a field extension), or, equivalently, a common factor (over th ...
of and with respect to is a homogeneous polynomial in and that has the following property: R(\alpha,\tau)=0 with (\alpha, \tau)\ne (0,0) if and only if it exist \beta such that (\alpha, \beta, \tau) is a common zero of and (see ). The above technical condition ensures that \beta is unique. The first above technical condition means that the degrees used in the definition of the resultant are and ; this implies that the degree of is (see ). As is a homogeneous polynomial in two indeterminates, the fundamental theorem of algebra implies that is a product of linear polynomials. If one defines the multiplicity of a common zero of and as the number of occurrences of the corresponding factor in the product, Bézout's theorem is thus proved. For proving that the intersection multiplicity that has just been defined equals the definition in terms of a deformation, it suffices to remark that the resultant and thus its linear factors are
continuous function In mathematics, a continuous function is a function such that a small variation of the argument induces a small variation of the value of the function. This implies there are no abrupt changes in value, known as '' discontinuities''. More preci ...
s of the coefficients of and . Proving the equality with other definitions of intersection multiplicities relies on the technicalities of these definitions and is therefore outside the scope of this article.


Using -resultant

In the early 20th century, Francis Sowerby Macaulay introduced the multivariate resultant (also known as ''Macaulay's resultant'') of homogeneous polynomials in indeterminates, which is generalization of the usual
resultant In mathematics, the resultant of two polynomials is a polynomial expression of their coefficients that is equal to zero if and only if the polynomials have a common root (possibly in a field extension), or, equivalently, a common factor (over th ...
of two polynomials. Macaulay's resultant is a polynomial function of the coefficients of homogeneous polynomials that is zero if and only the polynomials have a nontrivial (that is some component is nonzero) common zero in an
algebraically closed field In mathematics, a field is algebraically closed if every non-constant polynomial in (the univariate polynomial ring with coefficients in ) has a root in . In other words, a field is algebraically closed if the fundamental theorem of algebra ...
containing the coefficients. The -resultant is a particular instance of Macaulay's resultant, introduced also by Macaulay. Given homogeneous polynomials f_1,\ldots,f_n in indeterminates x_0, \ldots, x_n, the -resultant is the resultant of f_1,\ldots,f_n, and U_0x_0+\cdots +U_nx_n, where the coefficients U_0, \ldots, U_n are auxiliary indeterminates. The -resultant is a homogeneous polynomial in U_0, \ldots, U_n, whose degree is the product of the degrees of the f_i. Although a multivariate polynomial is generally irreducible, the -resultant can be factorized into linear (in the U_i) polynomials over an
algebraically closed field In mathematics, a field is algebraically closed if every non-constant polynomial in (the univariate polynomial ring with coefficients in ) has a root in . In other words, a field is algebraically closed if the fundamental theorem of algebra ...
containing the coefficients of the f_i. These linear factors correspond to the common zeros of the f_i in the following way: to each common zero (\alpha_0, \ldots, \alpha_n) corresponds a linear factor (\alpha_0 U_0 + \cdots + \alpha_n U_n), and conversely. This proves Bézout's theorem, if the multiplicity of a common zero is defined as the multiplicity of the corresponding linear factor of the -resultant. As for the preceding proof, the equality of this multiplicity with the definition by deformation results from the continuity of the -resultant as a function of the coefficients of the f_i. This proof of Bézout's theorem seems the oldest proof that satisfies the modern criteria of rigor.


Using the degree of an ideal

Bézout's theorem can be proved by recurrence on the number of polynomials by using the following theorem. ''Let be a projective algebraic set of
dimension In physics and mathematics, the dimension of a mathematical space (or object) is informally defined as the minimum number of coordinates needed to specify any point within it. Thus, a line has a dimension of one (1D) because only one coo ...
\delta and degree d_1, and be a hypersurface (defined by a single polynomial) of degree d_2, that does not contain any irreducible component of ; under these hypotheses, the intersection of and has dimension \delta-1 and degree d_1d_2.'' For a (sketched) proof using Hilbert series, see . Beside allowing a conceptually simple proof of Bézout's theorem, this theorem is fundamental for intersection theory, since this theory is essentially devoted to the study of intersection multiplicities when the hypotheses of the above theorem do not apply.


See also

* Multi-homogeneous Bézout theorem * *


Notes


References

* * * Alternative translation of earlier (2nd) edition of Newton's ''Principia''. *


External links

* *
Bezout's Theorem at MathPages
{{DEFAULTSORT:Bezouts Theorem Theorems in plane geometry Incidence geometry Intersection theory Theorems in algebraic geometry