Plane Conics in Algebraic Geometry
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Bézout's Theorem
Bézout's theorem Toni Annala Contents 1 Introduction 2 2 Bézout's theorem 4 2.1 Ane plane curves . .4 2.2 Projective plane curves . .6 2.3 An elementary proof for the upper bound . 10 2.4 Intersection numbers . 12 2.5 Proof of Bézout's theorem . 16 3 Intersections in Pn 20 3.1 The Hilbert series and the Hilbert polynomial . 20 3.2 A brief overview of the modern theory . 24 3.3 Intersections of hypersurfaces in Pn ...................... 26 3.4 Intersections of subvarieties in Pn ....................... 32 3.5 Serre's Tor-formula . 36 4 Appendix 42 4.1 Homogeneous Noether normalization . 42 4.2 Primes associated to a graded module . 43 1 Chapter 1 Introduction The topic of this thesis is Bézout's theorem. The classical version considers the number of points in the intersection of two algebraic plane curves. It states that if we have two algebraic plane curves, dened over an algebraically closed eld and cut out by multi- variate polynomials of degrees n and m, then the number of points where these curves intersect is exactly nm if we count multiple intersections and intersections at innity. In Chapter 2 we dene the necessary terminology to state this theorem rigorously, give an elementary proof for the upper bound using resultants, and later prove the full Bézout's theorem. A very modest background should suce for understanding this chapter, for example the course Algebra II given at the University of Helsinki should cover most, if not all, of the prerequisites. In Chapter 3, we generalize Bézout's theorem to higher dimensional projective spaces. -
Chapter 1 Geometry of Plane Curves
Chapter 1 Geometry of Plane Curves Definition 1 A (parametrized) curve in Rn is a piece-wise differentiable func- tion α :(a, b) Rn. If I is any other subset of R, α : I Rn is a curve provided that α→extends to a piece-wise differentiable function→ on some open interval (a, b) I. The trace of a curve α is the set of points α ((a, b)) Rn. ⊃ ⊂ AsubsetS Rn is parametrized by α if and only if there exists set I R ⊂ ⊆ such that α : I Rn is a curve for which α (I)=S. A one-to-one parame- trization α assigns→ and orientation toacurveC thought of as the direction of increasing parameter, i.e., if s<t,the direction of increasing parameter runs from α (s) to α (t) . AsubsetS Rn may be parametrized in many ways. ⊂ Example 2 Consider the circle C : x2 + y2 =1and let ω>0. The curve 2π α : 0, R2 given by ω → ¡ ¤ α(t)=(cosωt, sin ωt) . is a parametrization of C for each choice of ω R. Recall that the velocity and acceleration are respectively given by ∈ α0 (t)=( ω sin ωt, ω cos ωt) − and α00 (t)= ω2 cos 2πωt, ω2 sin 2πωt = ω2α(t). − − − The speed is given by ¡ ¢ 2 2 v(t)= α0(t) = ( ω sin ωt) +(ω cos ωt) = ω. (1.1) k k − q 1 2 CHAPTER 1. GEOMETRY OF PLANE CURVES The various parametrizations obtained by varying ω change the velocity, ac- 2π celeration and speed but have the same trace, i.e., α 0, ω = C for each ω. -
2D and 3D Transformations, Homogeneous Coordinates Lecture 03
2D and 3D Transformations, Homogeneous Coordinates Lecture 03 Patrick Karlsson [email protected] Centre for Image Analysis Uppsala University Computer Graphics November 6 2006 Patrick Karlsson (Uppsala University) Transformations and Homogeneous Coords. Computer Graphics 1 / 23 Reading Instructions Chapters 4.1–4.9. Edward Angel. “Interactive Computer Graphics: A Top-down Approach with OpenGL”, Fourth Edition, Addison-Wesley, 2004. Patrick Karlsson (Uppsala University) Transformations and Homogeneous Coords. Computer Graphics 2 / 23 Todays lecture ... in the pipeline Patrick Karlsson (Uppsala University) Transformations and Homogeneous Coords. Computer Graphics 3 / 23 Scalars, points, and vectors Scalars α, β Real (or complex) numbers. Points P, Q Locations in space (but no size or shape). Vectors u, v Directions in space (magnitude but no position). Patrick Karlsson (Uppsala University) Transformations and Homogeneous Coords. Computer Graphics 4 / 23 Mathematical spaces Scalar field A set of scalars obeying certain properties. New scalars can be formed through addition and multiplication. (Linear) Vector space Made up of scalars and vectors. New vectors can be created through scalar-vector multiplication, and vector-vector addition. Affine space An extended vector space that include points. This gives us additional operators, such as vector-point addition, and point-point subtraction. Patrick Karlsson (Uppsala University) Transformations and Homogeneous Coords. Computer Graphics 5 / 23 Data types Polygon based objects Objects are described using polygons. A polygon is defined by its vertices (i.e., points). Transformations manipulate the vertices, thus manipulates the objects. Some examples in 2D Scalar α 1 float. Point P(x, y) 2 floats. Vector v(x, y) 2 floats. Matrix M 4 floats. -
Combination of Cubic and Quartic Plane Curve
IOSR Journal of Mathematics (IOSR-JM) e-ISSN: 2278-5728,p-ISSN: 2319-765X, Volume 6, Issue 2 (Mar. - Apr. 2013), PP 43-53 www.iosrjournals.org Combination of Cubic and Quartic Plane Curve C.Dayanithi Research Scholar, Cmj University, Megalaya Abstract The set of complex eigenvalues of unistochastic matrices of order three forms a deltoid. A cross-section of the set of unistochastic matrices of order three forms a deltoid. The set of possible traces of unitary matrices belonging to the group SU(3) forms a deltoid. The intersection of two deltoids parametrizes a family of Complex Hadamard matrices of order six. The set of all Simson lines of given triangle, form an envelope in the shape of a deltoid. This is known as the Steiner deltoid or Steiner's hypocycloid after Jakob Steiner who described the shape and symmetry of the curve in 1856. The envelope of the area bisectors of a triangle is a deltoid (in the broader sense defined above) with vertices at the midpoints of the medians. The sides of the deltoid are arcs of hyperbolas that are asymptotic to the triangle's sides. I. Introduction Various combinations of coefficients in the above equation give rise to various important families of curves as listed below. 1. Bicorn curve 2. Klein quartic 3. Bullet-nose curve 4. Lemniscate of Bernoulli 5. Cartesian oval 6. Lemniscate of Gerono 7. Cassini oval 8. Lüroth quartic 9. Deltoid curve 10. Spiric section 11. Hippopede 12. Toric section 13. Kampyle of Eudoxus 14. Trott curve II. Bicorn curve In geometry, the bicorn, also known as a cocked hat curve due to its resemblance to a bicorne, is a rational quartic curve defined by the equation It has two cusps and is symmetric about the y-axis. -
Section 6.2 Introduction to Conics: Parabolas 103
Section 6.2 Introduction to Conics: Parabolas 103 Course Number Section 6.2 Introduction to Conics: Parabolas Instructor Objective: In this lesson you learned how to write the standard form of the equation of a parabola. Date Important Vocabulary Define each term or concept. Directrix A fixed line in the plane from which each point on a parabola is the same distance as the distance from the point to a fixed point in the plane. Focus A fixed point in the plane from which each point on a parabola is the same distance as the distance from the point to a fixed line in the plane. Focal chord A line segment that passes through the focus of a parabola and has endpoints on the parabola. Latus rectum The specific focal chord perpendicular to the axis of a parabola. Tangent A line is tangent to a parabola at a point on the parabola if the line intersects, but does not cross, the parabola at the point. I. Conics (Page 433) What you should learn How to recognize a conic A conic section, or conic, is . the intersection of a plane as the intersection of a and a double-napped cone. plane and a double- napped cone Name the four basic conic sections: circle, ellipse, parabola, and hyperbola. In the formation of the four basic conics, the intersecting plane does not pass through the vertex of the cone. When the plane does pass through the vertex, the resulting figure is a(n) degenerate conic , such as . a point, a line, or a pair of intersecting lines. -
2-D Drawing Geometry Homogeneous Coordinates
2-D Drawing Geometry Homogeneous Coordinates The rotation of a point, straight line or an entire image on the screen, about a point other than origin, is achieved by first moving the image until the point of rotation occupies the origin, then performing rotation, then finally moving the image to its original position. The moving of an image from one place to another in a straight line is called a translation. A translation may be done by adding or subtracting to each point, the amount, by which picture is required to be shifted. Translation of point by the change of coordinate cannot be combined with other transformation by using simple matrix application. Such a combination is essential if we wish to rotate an image about a point other than origin by translation, rotation again translation. To combine these three transformations into a single transformation, homogeneous coordinates are used. In homogeneous coordinate system, two-dimensional coordinate positions (x, y) are represented by triple- coordinates. Homogeneous coordinates are generally used in design and construction applications. Here we perform translations, rotations, scaling to fit the picture into proper position 2D Transformation in Computer Graphics- In Computer graphics, Transformation is a process of modifying and re- positioning the existing graphics. • 2D Transformations take place in a two dimensional plane. • Transformations are helpful in changing the position, size, orientation, shape etc of the object. Transformation Techniques- In computer graphics, various transformation techniques are- 1. Translation 2. Rotation 3. Scaling 4. Reflection 2D Translation in Computer Graphics- In Computer graphics, 2D Translation is a process of moving an object from one position to another in a two dimensional plane. -
Projective Geometry Lecture Notes
Projective Geometry Lecture Notes Thomas Baird March 26, 2014 Contents 1 Introduction 2 2 Vector Spaces and Projective Spaces 4 2.1 Vector spaces and their duals . 4 2.1.1 Fields . 4 2.1.2 Vector spaces and subspaces . 5 2.1.3 Matrices . 7 2.1.4 Dual vector spaces . 7 2.2 Projective spaces and homogeneous coordinates . 8 2.2.1 Visualizing projective space . 8 2.2.2 Homogeneous coordinates . 13 2.3 Linear subspaces . 13 2.3.1 Two points determine a line . 14 2.3.2 Two planar lines intersect at a point . 14 2.4 Projective transformations and the Erlangen Program . 15 2.4.1 Erlangen Program . 16 2.4.2 Projective versus linear . 17 2.4.3 Examples of projective transformations . 18 2.4.4 Direct sums . 19 2.4.5 General position . 20 2.4.6 The Cross-Ratio . 22 2.5 Classical Theorems . 23 2.5.1 Desargues' Theorem . 23 2.5.2 Pappus' Theorem . 24 2.6 Duality . 26 3 Quadrics and Conics 28 3.1 Affine algebraic sets . 28 3.2 Projective algebraic sets . 30 3.3 Bilinear and quadratic forms . 31 3.3.1 Quadratic forms . 33 3.3.2 Change of basis . 33 1 3.3.3 Digression on the Hessian . 36 3.4 Quadrics and conics . 37 3.5 Parametrization of the conic . 40 3.5.1 Rational parametrization of the circle . 42 3.6 Polars . 44 3.7 Linear subspaces of quadrics and ruled surfaces . 46 3.8 Pencils of quadrics and degeneration . 47 4 Exterior Algebras 52 4.1 Multilinear algebra . -
TWO FAMILIES of STABLE BUNDLES with the SAME SPECTRUM Nonreduced [M]
proceedings of the american mathematical society Volume 109, Number 3, July 1990 TWO FAMILIES OF STABLE BUNDLES WITH THE SAME SPECTRUM A. P. RAO (Communicated by Louis J. Ratliff, Jr.) Abstract. We study stable rank two algebraic vector bundles on P and show that the family of bundles with fixed Chern classes and spectrum may have more than one irreducible component. We also produce a component where the generic bundle has a monad with ghost terms which cannot be deformed away. In the last century, Halphen and M. Noether attempted to classify smooth algebraic curves in P . They proceeded with the invariants d , g , the degree and genus, and worked their way up to d = 20. As the invariants grew larger, the number of components of the parameter space grew as well. Recent work of Gruson and Peskine has settled the question of which invariant pairs (d, g) are admissible. For a fixed pair (d, g), the question of determining the number of components of the parameter space is still intractable. For some values of (d, g) (for example [E-l], if d > g + 3) there is only one component. For other values, one may find many components including components which are nonreduced [M]. More recently, similar questions have been asked about algebraic vector bun- dles of rank two on P . We will restrict our attention to stable bundles a? with first Chern class c, = 0 (and second Chern class c2 = n, so that « is a positive integer and i? has no global sections). To study these, we have the invariants n, the a-invariant (which is equal to dim//"'(P , f(-2)) mod 2) and the spectrum. -
Geometry of Algebraic Curves
Geometry of Algebraic Curves Fall 2011 Course taught by Joe Harris Notes by Atanas Atanasov One Oxford Street, Cambridge, MA 02138 E-mail address: [email protected] Contents Lecture 1. September 2, 2011 6 Lecture 2. September 7, 2011 10 2.1. Riemann surfaces associated to a polynomial 10 2.2. The degree of KX and Riemann-Hurwitz 13 2.3. Maps into projective space 15 2.4. An amusing fact 16 Lecture 3. September 9, 2011 17 3.1. Embedding Riemann surfaces in projective space 17 3.2. Geometric Riemann-Roch 17 3.3. Adjunction 18 Lecture 4. September 12, 2011 21 4.1. A change of viewpoint 21 4.2. The Brill-Noether problem 21 Lecture 5. September 16, 2011 25 5.1. Remark on a homework problem 25 5.2. Abel's Theorem 25 5.3. Examples and applications 27 Lecture 6. September 21, 2011 30 6.1. The canonical divisor on a smooth plane curve 30 6.2. More general divisors on smooth plane curves 31 6.3. The canonical divisor on a nodal plane curve 32 6.4. More general divisors on nodal plane curves 33 Lecture 7. September 23, 2011 35 7.1. More on divisors 35 7.2. Riemann-Roch, finally 36 7.3. Fun applications 37 7.4. Sheaf cohomology 37 Lecture 8. September 28, 2011 40 8.1. Examples of low genus 40 8.2. Hyperelliptic curves 40 8.3. Low genus examples 42 Lecture 9. September 30, 2011 44 9.1. Automorphisms of genus 0 an 1 curves 44 9.2. -
Chapter 12 the Cross Ratio
Chapter 12 The cross ratio Math 4520, Fall 2017 We have studied the collineations of a projective plane, the automorphisms of the underlying field, the linear functions of Affine geometry, etc. We have been led to these ideas by various problems at hand, but let us step back and take a look at one important point of view of the big picture. 12.1 Klein's Erlanger program In 1872, Felix Klein, one of the leading mathematicians and geometers of his day, in the city of Erlanger, took the following point of view as to what the role of geometry was in mathematics. This is from his \Recent trends in geometric research." Let there be given a manifold and in it a group of transforma- tions; it is our task to investigate those properties of a figure belonging to the manifold that are not changed by the transfor- mation of the group. So our purpose is clear. Choose the group of transformations that you are interested in, and then hunt for the \invariants" that are relevant. This search for invariants has proved very fruitful and useful since the time of Klein for many areas of mathematics, not just classical geometry. In some case the invariants have turned out to be simple polynomials or rational functions, such as the case with the cross ratio. In other cases the invariants were groups themselves, such as homology groups in the case of algebraic topology. 12.2 The projective line In Chapter 11 we saw that the collineations of a projective plane come in two \species," projectivities and field automorphisms. -
Homogeneous Representations of Points, Lines and Planes
Chapter 5 Homogeneous Representations of Points, Lines and Planes 5.1 Homogeneous Vectors and Matrices ................................. 195 5.2 Homogeneous Representations of Points and Lines in 2D ............... 205 n 5.3 Homogeneous Representations in IP ................................ 209 5.4 Homogeneous Representations of 3D Lines ........................... 216 5.5 On Plücker Coordinates for Points, Lines and Planes .................. 221 5.6 The Principle of Duality ........................................... 229 5.7 Conics and Quadrics .............................................. 236 5.8 Normalizations of Homogeneous Vectors ............................. 241 5.9 Canonical Elements of Coordinate Systems ........................... 242 5.10 Exercises ........................................................ 245 This chapter motivates and introduces homogeneous coordinates for representing geo- metric entities. Their name is derived from the homogeneity of the equations they induce. Homogeneous coordinates represent geometric elements in a projective space, as inhomoge- neous coordinates represent geometric entities in Euclidean space. Throughout this book, we will use Cartesian coordinates: inhomogeneous in Euclidean spaces and homogeneous in projective spaces. A short course in the plane demonstrates the usefulness of homogeneous coordinates for constructions, transformations, estimation, and variance propagation. A characteristic feature of projective geometry is the symmetry of relationships between points and lines, called -
Bézout's Theorem
Bézout’s Theorem Jennifer Li Department of Mathematics University of Massachusetts Amherst, MA ¡ No common components How many intersection points are there? Motivation f (x,y) g(x,y) Jennifer Li (University of Massachusetts) Bézout’s Theorem November 30, 2016 2 / 80 How many intersection points are there? Motivation f (x,y) ¡ No common components g(x,y) Jennifer Li (University of Massachusetts) Bézout’s Theorem November 30, 2016 2 / 80 Motivation f (x,y) ¡ No common components g(x,y) How many intersection points are there? Jennifer Li (University of Massachusetts) Bézout’s Theorem November 30, 2016 2 / 80 Algebra Geometry { set of solutions } { intersection points of curves } Motivation f (x,y) = 0 g(x,y) = 0 Jennifer Li (University of Massachusetts) Bézout’s Theorem November 30, 2016 3 / 80 Geometry { intersection points of curves } Motivation f (x,y) = 0 g(x,y) = 0 Algebra { set of solutions } Jennifer Li (University of Massachusetts) Bézout’s Theorem November 30, 2016 3 / 80 Motivation f (x,y) = 0 g(x,y) = 0 Algebra Geometry { set of solutions } { intersection points of curves } Jennifer Li (University of Massachusetts) Bézout’s Theorem November 30, 2016 3 / 80 Motivation f (x,y) = 0 g(x,y) = 0 How many intersections are there? Jennifer Li (University of Massachusetts) Bézout’s Theorem November 30, 2016 4 / 80 Motivation f (x,y) = 0 g(x,y) = 0 How many intersections are there? Jennifer Li (University of Massachusetts) Bézout’s Theorem November 30, 2016 5 / 80 Motivation f (x,y) = 0 g(x,y) = 0 How many intersections are there? Jennifer Li (University of Massachusetts) Bézout’s Theorem November 30, 2016 6 / 80 f (x): polynomial in one variable 2 n f (x) = a0 + a1x + a2x +⋯+ anx Example.