Incidence (geometry)

Last updated

In geometry, an incidence relation is a heterogeneous relation that captures the idea being expressed when phrases such as "a point lies on a line" or "a line is contained in a plane" are used. The most basic incidence relation is that between a point, P, and a line, l, sometimes denoted P I l. If P and l are incident, P I l, the pair (P, l) is called a flag.

Contents

There are many expressions used in common language to describe incidence (for example, a line passes through a point, a point lies in a plane, etc.) but the term "incidence" is preferred because it does not have the additional connotations that these other terms have, and it can be used in a symmetric manner. Statements such as "line l1 intersects line l2" are also statements about incidence relations, but in this case, it is because this is a shorthand way of saying that "there exists a point P that is incident with both line l1 and line l2". When one type of object can be thought of as a set of the other type of object (viz., a plane is a set of points) then an incidence relation may be viewed as containment.

Statements such as "any two lines in a plane meet" are called incidence propositions. This particular statement is true in a projective plane, though not true in the Euclidean plane where lines may be parallel. Historically, projective geometry was developed in order to make the propositions of incidence true without exceptions, such as those caused by the existence of parallels. From the point of view of synthetic geometry, projective geometry should be developed using such propositions as axioms. This is most significant for projective planes due to the universal validity of Desargues' theorem in higher dimensions.

In contrast, the analytic approach is to define projective space based on linear algebra and utilizing homogeneous co-ordinates. The propositions of incidence are derived from the following basic result on vector spaces: given subspaces U and W of a (finite-dimensional) vector space V, the dimension of their intersection is dim U + dim W dim (U + W). Bearing in mind that the geometric dimension of the projective space P(V) associated to V is dim V 1 and that the geometric dimension of any subspace is positive, the basic proposition of incidence in this setting can take the form: linear subspaces L and M of projective space P meet provided dim L + dim M ≥ dim P. [1]

The following sections are limited to projective planes defined over fields, often denoted by PG(2, F), where F is a field, or P2F. However these computations can be naturally extended to higher-dimensional projective spaces, and the field may be replaced by a division ring (or skewfield) provided that one pays attention to the fact that multiplication is not commutative in that case.

PG(2,F)

Let V be the three-dimensional vector space defined over the field F. The projective plane P(V) = PG(2, F) consists of the one-dimensional vector subspaces of V, called points, and the two-dimensional vector subspaces of V, called lines. Incidence of a point and a line is given by containment of the one-dimensional subspace in the two-dimensional subspace.

Fix a basis for V so that we may describe its vectors as coordinate triples (with respect to that basis). A one-dimensional vector subspace consists of a non-zero vector and all of its scalar multiples. The non-zero scalar multiples, written as coordinate triples, are the homogeneous coordinates of the given point, called point coordinates. With respect to this basis, the solution space of a single linear equation {(x, y, z) | ax + by + cz = 0} is a two-dimensional subspace of V, and hence a line of P(V). This line may be denoted by line coordinates[a, b, c], which are also homogeneous coordinates since non-zero scalar multiples would give the same line. Other notations are also widely used. Point coordinates may be written as column vectors, (x, y, z)T, with colons, (x : y : z), or with a subscript, (x, y, z)P. Correspondingly, line coordinates may be written as row vectors, (a, b, c), with colons, [a : b : c] or with a subscript, (a, b, c)L. Other variations are also possible.

Incidence expressed algebraically

Given a point P = (x, y, z) and a line l = [a, b, c], written in terms of point and line coordinates, the point is incident with the line (often written as P I l), if and only if,

ax + by + cz = 0.

This can be expressed in other notations as:

No matter what notation is employed, when the homogeneous coordinates of the point and line are just considered as ordered triples, their incidence is expressed as having their dot product equal 0.

The line incident with a pair of distinct points

Let P1 and P2 be a pair of distinct points with homogeneous coordinates (x1, y1, z1) and (x2, y2, z2) respectively. These points determine a unique line l with an equation of the form ax + by + cz = 0 and must satisfy the equations:

ax1 + by1 + cz1 = 0 and
ax2 + by2 + cz2 = 0.

In matrix form this system of simultaneous linear equations can be expressed as:

This system has a nontrivial solution if and only if the determinant,

Expansion of this determinantal equation produces a homogeneous linear equation, which must be the equation of line l. Therefore, up to a common non-zero constant factor we have l = [a, b, c] where:

a = y1z2 - y2z1,
b = x2z1 - x1z2, and
c = x1y2 - x2y1.

In terms of the scalar triple product notation for vectors, the equation of this line may be written as:

PP1 × P2 = 0,

where P = (x, y, z) is a generic point.

Collinearity

Points that are incident with the same line are said to be collinear. The set of all points incident with the same line is called a range.

If P1 = (x1, y1, z1), P2 = (x2, y2, z2), and P3 = (x3, y3, z3), then these points are collinear if and only if

i.e., if and only if the determinant of the homogeneous coordinates of the points is equal to zero.

Intersection of a pair of lines

Let l1 = [a1, b1, c1] and l2 = [a2, b2, c2] be a pair of distinct lines. Then the intersection of lines l1 and l2 is point a P = (x0, y0, z0) that is the simultaneous solution (up to a scalar factor) of the system of linear equations:

a1x + b1y + c1z = 0 and
a2x + b2y + c2z = 0.

The solution of this system gives:

x0 = b1c2 - b2c1,
y0 = a2c1 - a1c2, and
z0 = a1b2 - a2b1.

Alternatively, consider another line l = [a, b, c] passing through the point P, that is, the homogeneous coordinates of P satisfy the equation:

ax+ by + cz = 0.

Combining this equation with the two that define P, we can seek a non-trivial solution of the matrix equation:

Such a solution exists provided the determinant,

The coefficients of a, b and c in this equation give the homogeneous coordinates of P.

The equation of the generic line passing through the point P in scalar triple product notation is:

ll1 × l2 = 0.

Concurrence

Lines that meet at the same point are said to be concurrent. The set of all lines in a plane incident with the same point is called a pencil of lines centered at that point. The computation of the intersection of two lines shows that the entire pencil of lines centered at a point is determined by any two of the lines that intersect at that point. It immediately follows that the algebraic condition for three lines, [a1, b1, c1], [a2, b2, c2], [a3, b3, c3] to be concurrent is that the determinant,

See also

Related Research Articles

In mathematics, and more specifically in linear algebra, a linear map is a mapping between two vector spaces that preserves the operations of vector addition and scalar multiplication. The same names and the same definition are also used for the more general case of modules over a ring; see Module homomorphism.

<span class="mw-page-title-main">Linear algebra</span> Branch of mathematics

Linear algebra is the branch of mathematics concerning linear equations such as:

<span class="mw-page-title-main">Projective plane</span> Geometric concept of a 2D space with a "point at infinity" adjoined

In mathematics, a projective plane is a geometric structure that extends the concept of a plane. In the ordinary Euclidean plane, two lines typically intersect at a single point, but there are some pairs of lines that do not intersect. A projective plane can be thought of as an ordinary plane equipped with additional "points at infinity" where parallel lines intersect. Thus any two distinct lines in a projective plane intersect at exactly one point.

<span class="mw-page-title-main">Vector space</span> Algebraic structure in linear algebra

In mathematics and physics, a vector space is a set whose elements, often called vectors, can be added together and multiplied ("scaled") by numbers called scalars. The operations of vector addition and scalar multiplication must satisfy certain requirements, called vector axioms. Real vector spaces and complex vector spaces are kinds of vector spaces based on different kinds of scalars: real numbers and complex numbers. Scalars can also be, more generally, elements of any field.

<span class="mw-page-title-main">Affine transformation</span> Geometric transformation that preserves lines but not angles nor the origin

In Euclidean geometry, an affine transformation or affinity is a geometric transformation that preserves lines and parallelism, but not necessarily Euclidean distances and angles.

In mathematics, and more specifically in linear algebra, a linear subspace or vector subspace is a vector space that is a subset of some larger vector space. A linear subspace is usually simply called a subspace when the context serves to distinguish it from other types of subspaces.

<span class="mw-page-title-main">Euclidean planes in three-dimensional space</span> Flat surface

In Euclidean geometry, a plane is a flat two-dimensional surface that extends indefinitely. Euclidean planes often arise as subspaces of three-dimensional space . A prototypical example is one of a room's walls, infinitely extended and assumed infinitesimal thin. While a pair of real numbers suffices to describe points on a plane, the relationship with out-of-plane points requires special consideration for their embedding in the ambient space .

<span class="mw-page-title-main">Row and column spaces</span> Vector spaces associated to a matrix

In linear algebra, the column space of a matrix A is the span of its column vectors. The column space of a matrix is the image or range of the corresponding matrix transformation.

<span class="mw-page-title-main">System of linear equations</span> Several equations of degree 1 to be solved simultaneously

In mathematics, a system of linear equations is a collection of two or more linear equations involving the same variables. For example,

<span class="mw-page-title-main">Normal (geometry)</span> Line or vector perpendicular to a curve or a surface

In geometry, a normal is an object that is perpendicular to a given object. For example, the normal line to a plane curve at a given point is the line perpendicular to the tangent line to the curve at the point.

<span class="mw-page-title-main">Projective space</span> Completion of the usual space with "points at infinity"

In mathematics, the concept of a projective space originated from the visual effect of perspective, where parallel lines seem to meet at infinity. A projective space may thus be viewed as the extension of a Euclidean space, or, more generally, an affine space with points at infinity, in such a way that there is one point at infinity of each direction of parallel lines.

<span class="mw-page-title-main">Homogeneous coordinates</span> Coordinate system used in projective geometry

In mathematics, homogeneous coordinates or projective coordinates, introduced by August Ferdinand Möbius in his 1827 work Der barycentrische Calcul, are a system of coordinates used in projective geometry, just as Cartesian coordinates are used in Euclidean geometry. They have the advantage that the coordinates of points, including points at infinity, can be represented using finite coordinates. Formulas involving homogeneous coordinates are often simpler and more symmetric than their Cartesian counterparts. Homogeneous coordinates have a range of applications, including computer graphics and 3D computer vision, where they allow affine transformations and, in general, projective transformations to be easily represented by a matrix. They are also used in fundamental elliptic curve cryptography algorithms.

<span class="mw-page-title-main">Real projective plane</span> Compact non-orientable two-dimensional manifold

In mathematics, the real projective plane, denoted or , is a two-dimensional projective space, similar to the familiar Euclidean plane in many respects but without the concepts of distance, circles, angle measure, or parallelism. It is the setting for planar projective geometry, in which the relationships between objects are not considered to change under projective transformations. The name projective comes from perspective drawing: projecting an image from one plane onto another as viewed from a point outside either plane, for example by photographing a flat painting from an oblique angle, is a projective transformation.

In projective geometry, duality or plane duality is a formalization of the striking symmetry of the roles played by points and lines in the definitions and theorems of projective planes. There are two approaches to the subject of duality, one through language and the other a more functional approach through special mappings. These are completely equivalent and either treatment has as its starting point the axiomatic version of the geometries under consideration. In the functional approach there is a map between related geometries that is called a duality. Such a map can be constructed in many ways. The concept of plane duality readily extends to space duality and beyond that to duality in any finite-dimensional projective geometry.

<span class="mw-page-title-main">Line (geometry)</span> Straight figure with zero width and depth

In geometry, a straight line, usually abbreviated line, is an infinitely long object with no width, depth, or curvature, an idealization of such physical objects as a straightedge, a taut string, or a ray of light. Lines are spaces of dimension one, which may be embedded in spaces of dimension two, three, or higher. The word line may also refer, in everyday life, to a line segment, which is a part of a line delimited by two points.

In mathematics, the kernel of a linear map, also known as the null space or nullspace, is the part of the domain which is mapped to the zero vector of the co-domain; the kernel is always a linear subspace of the domain. That is, given a linear map L : VW between two vector spaces V and W, the kernel of L is the vector space of all elements v of V such that L(v) = 0, where 0 denotes the zero vector in W, or more symbolically:

In geometry, Plücker coordinates, introduced by Julius Plücker in the 19th century, are a way to assign six homogeneous coordinates to each line in projective 3-space, . Because they satisfy a quadratic constraint, they establish a one-to-one correspondence between the 4-dimensional space of lines in and points on a quadric in . A predecessor and special case of Grassmann coordinates, Plücker coordinates arise naturally in geometric algebra. They have proved useful for computer graphics, and also can be extended to coordinates for the screws and wrenches in the theory of kinematics used for robot control.

<span class="mw-page-title-main">Blowing up</span> Type of geometric transformation

In mathematics, blowing up or blowup is a type of geometric transformation which replaces a subspace of a given space with the space of all directions pointing out of that subspace. For example, the blowup of a point in a plane replaces the point with the projectivized tangent space at that point. The metaphor is that of zooming in on a photograph to enlarge part of the picture, rather than referring to an explosion. The inverse operation is called blowing down.

<span class="mw-page-title-main">Three-dimensional space</span> Geometric model of the physical space

In geometry, a three-dimensional space is a mathematical space in which three values (coordinates) are required to determine the position of a point. Most commonly, it is the three-dimensional Euclidean space, that is, the Euclidean space of dimension three, which models physical space. More general three-dimensional spaces are called 3-manifolds. The term may also refer colloquially to a subset of space, a three-dimensional region, a solid figure.

In geometry, line coordinates are used to specify the position of a line just as point coordinates are used to specify the position of a point.

References

  1. Joel G. Broida & S. Gill Williamson (1998) A Comprehensive Introduction to Linear Algebra, Theorem 2.11, p 86, Addison-Wesley ISBN   0-201-50065-5. The theorem says that dim (L + M) = dim L + dim M dim (LM). Thus dim L + dim M > dim P implies dim (LM) > 0.