Gröbner Bases in Commutative Algebra
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Homogeneous Polynomial Solutions to Constant Coefficient Pde’S
HOMOGENEOUS POLYNOMIAL SOLUTIONS TO CONSTANT COEFFICIENT PDE'S Bruce Reznick University of Illinois 1409 W. Green St. Urbana, IL 61801 [email protected] October 21, 1994 1. Introduction Suppose p is a homogeneous polynomial over a field K. Let p(D) be the differen- @ tial operator defined by replacing each occurence of xj in p by , defined formally @xj 2 in case K is not a subset of C. (The classical example is p(x1; · · · ; xn) = j xj , for which p(D) is the Laplacian r2.) In this paper we solve the equation p(DP)q = 0 for homogeneous polynomials q over K, under the restriction that K be an algebraically closed field of characteristic 0. (This restriction is mild, considering that the \natu- ral" field is C.) Our Main Theorem and its proof are the natural extensions of work by Sylvester, Clifford, Rosanes, Gundelfinger, Cartan, Maass and Helgason. The novelties in the presentation are the generalization of the base field and the removal of some restrictions on p. The proofs require only undergraduate mathematics and Hilbert's Nullstellensatz. A fringe benefit of the proof of the Main Theorem is an Expansion Theorem for homogeneous polynomials over R and C. This theorem is 2 2 2 trivial for linear forms, goes back at least to Gauss for p = x1 + x2 + x3, and has also been studied by Maass and Helgason. Main Theorem (See Theorem 4.1). Let K be an algebraically closed field of mj characteristic 0. Suppose p 2 K[x1; · · · ; xn] is homogeneous and p = j pj for distinct non-constant irreducible factors pj 2 K[x1; · · · ; xn]. -
Algebra Polynomial(Lecture-I)
Algebra Polynomial(Lecture-I) Dr. Amal Kumar Adak Department of Mathematics, G.D.College, Begusarai March 27, 2020 Algebra Dr. Amal Kumar Adak Definition Function: Any mathematical expression involving a quantity (say x) which can take different values, is called a function of that quantity. The quantity (x) is called the variable and the function of it is denoted by f (x) ; F (x) etc. Example:f (x) = x2 + 5x + 6 + x6 + x3 + 4x5. Algebra Dr. Amal Kumar Adak Polynomial Definition Polynomial: A polynomial in x over a real or complex field is an expression of the form n n−1 n−3 p (x) = a0x + a1x + a2x + ::: + an,where a0; a1;a2; :::; an are constants (free from x) may be real or complex and n is a positive integer. Example: (i)5x4 + 4x3 + 6x + 1,is a polynomial where a0 = 5; a1 = 4; a2 = 0; a3 = 6; a4 = 1a0 = 4; a1 = 4; 2 1 3 3 2 1 (ii)x + x + x + 2 is not a polynomial, since 3 ; 3 are not integers. (iii)x4 + x3 cos (x) + x2 + x + 1 is not a polynomial for the presence of the term cos (x) Algebra Dr. Amal Kumar Adak Definition Zero Polynomial: A polynomial in which all the coefficients a0; a1; a2; :::; an are zero is called a zero polynomial. Definition Complete and Incomplete polynomials: A polynomial with non-zero coefficients is called a complete polynomial. Other-wise it is incomplete. Example of a complete polynomial:x5 + 2x4 + 3x3 + 7x2 + 9x + 1. Example of an incomplete polynomial: x5 + 3x3 + 7x2 + 9x + 1. -
Quadratic Form - Wikipedia, the Free Encyclopedia
Quadratic form - Wikipedia, the free encyclopedia http://en.wikipedia.org/wiki/Quadratic_form Quadratic form From Wikipedia, the free encyclopedia In mathematics, a quadratic form is a homogeneous polynomial of degree two in a number of variables. For example, is a quadratic form in the variables x and y. Quadratic forms occupy a central place in various branches of mathematics, including number theory, linear algebra, group theory (orthogonal group), differential geometry (Riemannian metric), differential topology (intersection forms of four-manifolds), and Lie theory (the Killing form). Contents 1 Introduction 2 History 3 Real quadratic forms 4 Definitions 4.1 Quadratic spaces 4.2 Further definitions 5 Equivalence of forms 6 Geometric meaning 7 Integral quadratic forms 7.1 Historical use 7.2 Universal quadratic forms 8 See also 9 Notes 10 References 11 External links Introduction Quadratic forms are homogeneous quadratic polynomials in n variables. In the cases of one, two, and three variables they are called unary, binary, and ternary and have the following explicit form: where a,…,f are the coefficients.[1] Note that quadratic functions, such as ax2 + bx + c in the one variable case, are not quadratic forms, as they are typically not homogeneous (unless b and c are both 0). The theory of quadratic forms and methods used in their study depend in a large measure on the nature of the 1 of 8 27/03/2013 12:41 Quadratic form - Wikipedia, the free encyclopedia http://en.wikipedia.org/wiki/Quadratic_form coefficients, which may be real or complex numbers, rational numbers, or integers. In linear algebra, analytic geometry, and in the majority of applications of quadratic forms, the coefficients are real or complex numbers. -
Solving Quadratic Equations in Many Variables
Snapshots of modern mathematics № 12/2017 from Oberwolfach Solving quadratic equations in many variables Jean-Pierre Tignol 1 Fields are number systems in which every linear equa- tion has a solution, such as the set of all rational numbers Q or the set of all real numbers R. All fields have the same properties in relation with systems of linear equations, but quadratic equations behave dif- ferently from field to field. Is there a field in which every quadratic equation in five variables has a solu- tion, but some quadratic equation in four variables has no solution? The answer is in this snapshot. 1 Fields No problem is more fundamental to algebra than solving polynomial equations. Indeed, the name algebra itself derives from a ninth century treatise [1] where the author explains how to solve quadratic equations like x2 +10x = 39. It was clear from the start that some equations with integral coefficients like x2 = 2 may not have any integral solution. Even allowing positive and negative numbers with infinite decimal expansion as solutions (these numbers are called real numbers), one cannot solve x2 = −1 because the square of every real number is positive or zero. However, it is only a small step from the real numbers to the solution 1 Jean-Pierre Tignol acknowledges support from the Fonds de la Recherche Scientifique (FNRS) under grant n◦ J.0014.15. He is grateful to Karim Johannes Becher, Andrew Dolphin, and David Leep for comments on a preliminary version of this text. 1 of every polynomial equation: one gives the solution of the equation x2 = −1 (or x2 + 1 = 0) the name i and defines complex numbers as expressions of the form a + bi, where a and b are real numbers. -
Groebner Bases
1 Monomial Orders. In the polynomial algebra over F a …eld in one variable x; F [x], we can do long division (sometimes incorrectly called the Euclidean algorithm). If f(x) = n a0 + a1x + ::: + anx F [x] with an = 0 then we write deg f(x) = n and 2 6 LC(f(x)) = am. If g(x) is another element of F [x] then we have f(x) = h(x)g(x) + r(x) with h(x); r(x) F [x] and deg r[x] < m. This expression is unique. This result can be vari…ed2 by long division. As with all divisions we assume g(x) = 0. Which we will recall as a pseudo code (such code terminates on a return)6 the input being f; g and the output h and r: f0 = f; h0 = 0; k = 0; m = deg g; Repeat: If deg(fk(x) < deg(g(x) return hk(x); fk(x);n = deg fk; LC(fk(x)) n m fk+1(x) = fk(x) x g(x) LC(g(x)) LC(fk(x)) n m hk+1(x) = hk(x) + LC(g(x)) x ; k = k + 1; Continue; We note that this code terminates since at each step when there is no return then the new value of the degree of fx(x) has strictly decreased. The theory of Gröbner bases is based on a generalization of this algorithm to more than one variable. Unfortunately there is an immediate di¢ culty. The degree of a polynomial does not determine the highest degree part of the poly- nomial up to scalar multiple. -
Degree Bounds for Gröbner Bases in Algebras of Solvable Type
Degree Bounds for Gröbner Bases in Algebras of Solvable Type Matthias Aschenbrenner University of California, Los Angeles (joint with Anton Leykin) Algebras of Solvable Type • . introduced by Kandri-Rody & Weispfenning (1990); • . form a class of associative algebras over fields which generalize • commutative polynomial rings; • Weyl algebras; • universal enveloping algebras of f. d. Lie algebras; • . are sometimes also called polynomial rings of solvable type or PBW-algebras (Poincaré-Birkhoff-Witt). Weyl Algebras Systems of linear PDE with polynomial coefficients can be represented by left ideals in the Weyl algebra An(C) = Chx1,..., xn, ∂1, . , ∂ni, the C-algebra generated by the xi , ∂j subject to the relations: xj xi = xi xj , ∂j ∂i = ∂i ∂j and ( xi ∂j if i 6= j ∂j xi = xi ∂j + 1 if i = j. The Weyl algebra acts naturally on C[x1,..., xn]: ∂f (∂i , f ) 7→ , (xi , f ) 7→ xi f . ∂xi Universal Enveloping Algebras Let g be a Lie algebra over a field K . The universal enveloping algebra U(g) of g is the K -algebra obtained by imposing the relations g ⊗ h − h ⊗ g = [g, h]g on the tensor algebra of the K -linear space g. Poincaré-Birkhoff-Witt Theorem: the canonical morphism g → U(g) is injective, and g generates the K -algebra U(g). If g corresponds to a Lie group G, then U(g) can be identified with the algebra of left-invariant differential operators on G. Affine Algebras and Monomials N Let R be a K -algebra, and x = (x1,..., xN ) ∈ R . Write α α1 αN N x := x1 ··· xN for a multi-index α = (α1, . -
Hyperbolicity and Stable Polynomials in Combinatorics and Probability
Hyperbolicity and stable polynomials in combinatorics and probability Robin Pemantle 1,2 ABSTRACT: These lectures survey the theory of hyperbolic and stable polynomials, from their origins in the theory of linear PDE’s to their present uses in combinatorics and probability theory. Keywords: amoeba, cone, dual cone, G˚arding-hyperbolicity, generating function, half-plane prop- erty, homogeneous polynomial, Laguerre–P´olya class, multiplier sequence, multi-affine, multivariate stability, negative dependence, negative association, Newton’s inequalities, Rayleigh property, real roots, semi-continuity, stochastic covering, stochastic domination, total positivity. Subject classification: Primary: 26C10, 62H20; secondary: 30C15, 05A15. 1Supported in part by National Science Foundation grant # DMS 0905937 2University of Pennsylvania, Department of Mathematics, 209 S. 33rd Street, Philadelphia, PA 19104 USA, pe- [email protected] Contents 1 Introduction 1 2 Origins, definitions and properties 4 2.1 Relation to the propagation of wave-like equations . 4 2.2 Homogeneous hyperbolic polynomials . 7 2.3 Cones of hyperbolicity for homogeneous polynomials . 10 3 Semi-continuity and Morse deformations 14 3.1 Localization . 14 3.2 Amoeba boundaries . 15 3.3 Morse deformations . 17 3.4 Asymptotics of Taylor coefficients . 19 4 Stability theory in one variable 23 4.1 Stability over general regions . 23 4.2 Real roots and Newton’s inequalities . 26 4.3 The Laguerre–P´olya class . 31 5 Multivariate stability 34 5.1 Equivalences . 36 5.2 Operations preserving stability . 38 5.3 More closure properties . 41 6 Negative dependence 41 6.1 A brief history of negative dependence . 41 6.2 Search for a theory . 43 i 6.3 The grail is found: application of stability theory to joint laws of binary random variables . -
KRULL DIMENSION and MONOMIAL ORDERS Introduction Let R Be An
KRULL DIMENSION AND MONOMIAL ORDERS GREGOR KEMPER AND NGO VIET TRUNG Abstract. We introduce the notion of independent sequences with respect to a mono- mial order by using the least terms of polynomials vanishing at the sequence. Our main result shows that the Krull dimension of a Noetherian ring is equal to the supremum of the length of independent sequences. The proof has led to other notions of indepen- dent sequences, which have interesting applications. For example, we can show that dim R=0 : J 1 is the maximum number of analytically independent elements in an arbi- trary ideal J of a local ring R and that dim B ≤ dim A if B ⊂ A are (not necessarily finitely generated) subalgebras of a finitely generated algebra over a Noetherian Jacobson ring. Introduction Let R be an arbitrary Noetherian ring, where a ring is always assumed to be commu- tative with identity. The aim of this paper is to characterize the Krull dimension dim R by means of a monomial order on polynomial rings over R. We are inspired of a result of Lombardi in [13] (see also Coquand and Lombardi [4], [5]) which says that for a positive integer s, dim R < s if and only if for every sequence of elements a1; : : : ; as in R, there exist nonnegative integers m1; : : : ; ms and elements c1; : : : ; cs 2 R such that m1 ms m1+1 m1 m2+1 m1 ms−1 ms+1 a1 ··· as + c1a1 + c2a1 a2 + ··· + csa1 ··· as−1 as = 0: This result has helped to develop a constructive theory for the Krull dimension [6], [7], [8]. -
Resultant and Discriminant of Polynomials
RESULTANT AND DISCRIMINANT OF POLYNOMIALS SVANTE JANSON Abstract. This is a collection of classical results about resultants and discriminants for polynomials, compiled mainly for my own use. All results are well-known 19th century mathematics, but I have not inves- tigated the history, and no references are given. 1. Resultant n m Definition 1.1. Let f(x) = anx + ··· + a0 and g(x) = bmx + ··· + b0 be two polynomials of degrees (at most) n and m, respectively, with coefficients in an arbitrary field F . Their resultant R(f; g) = Rn;m(f; g) is the element of F given by the determinant of the (m + n) × (m + n) Sylvester matrix Syl(f; g) = Syln;m(f; g) given by 0an an−1 an−2 ::: 0 0 0 1 B 0 an an−1 ::: 0 0 0 C B . C B . C B . C B C B 0 0 0 : : : a1 a0 0 C B C B 0 0 0 : : : a2 a1 a0C B C (1.1) Bbm bm−1 bm−2 ::: 0 0 0 C B C B 0 bm bm−1 ::: 0 0 0 C B . C B . C B C @ 0 0 0 : : : b1 b0 0 A 0 0 0 : : : b2 b1 b0 where the m first rows contain the coefficients an; an−1; : : : ; a0 of f shifted 0; 1; : : : ; m − 1 steps and padded with zeros, and the n last rows contain the coefficients bm; bm−1; : : : ; b0 of g shifted 0; 1; : : : ; n−1 steps and padded with zeros. In other words, the entry at (i; j) equals an+i−j if 1 ≤ i ≤ m and bi−j if m + 1 ≤ i ≤ m + n, with ai = 0 if i > n or i < 0 and bi = 0 if i > m or i < 0. -
Algebraic Combinatorics and Resultant Methods for Polynomial System Solving Anna Karasoulou
Algebraic combinatorics and resultant methods for polynomial system solving Anna Karasoulou To cite this version: Anna Karasoulou. Algebraic combinatorics and resultant methods for polynomial system solving. Computer Science [cs]. National and Kapodistrian University of Athens, Greece, 2017. English. tel-01671507 HAL Id: tel-01671507 https://hal.inria.fr/tel-01671507 Submitted on 5 Jan 2018 HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. ΕΘΝΙΚΟ ΚΑΙ ΚΑΠΟΔΙΣΤΡΙΑΚΟ ΠΑΝΕΠΙΣΤΗΜΙΟ ΑΘΗΝΩΝ ΣΧΟΛΗ ΘΕΤΙΚΩΝ ΕΠΙΣΤΗΜΩΝ ΤΜΗΜΑ ΠΛΗΡΟΦΟΡΙΚΗΣ ΚΑΙ ΤΗΛΕΠΙΚΟΙΝΩΝΙΩΝ ΠΡΟΓΡΑΜΜΑ ΜΕΤΑΠΤΥΧΙΑΚΩΝ ΣΠΟΥΔΩΝ ΔΙΔΑΚΤΟΡΙΚΗ ΔΙΑΤΡΙΒΗ Μελέτη και επίλυση πολυωνυμικών συστημάτων με χρήση αλγεβρικών και συνδυαστικών μεθόδων Άννα Ν. Καρασούλου ΑΘΗΝΑ Μάιος 2017 NATIONAL AND KAPODISTRIAN UNIVERSITY OF ATHENS SCHOOL OF SCIENCES DEPARTMENT OF INFORMATICS AND TELECOMMUNICATIONS PROGRAM OF POSTGRADUATE STUDIES PhD THESIS Algebraic combinatorics and resultant methods for polynomial system solving Anna N. Karasoulou ATHENS May 2017 ΔΙΔΑΚΤΟΡΙΚΗ ΔΙΑΤΡΙΒΗ Μελέτη και επίλυση πολυωνυμικών συστημάτων με -
1. Fields Fields and Vector Spaces. Typical Vector Spaces: R, Q, C. for Infinite Dimensional Vector Spaces, See Notes by Karen Smith
1. Fields Fields and vector spaces. Typical vector spaces: R; Q; C. For infinite dimensional vector spaces, see notes by Karen Smith. Important to consider a field as a vector space over a sub-field. Also have: algebraic closure of Q. Galois fields: GF (pa). Don't limit what field you work over. 2. Polynomial rings over a field Notation for a polynomial ring: K[x1; : : : ; xn]. α1 α2 αn Monomial: x1 x2 ··· xn n Set α = (α1; : : : ; αn) 2 N . α α1 α2 αn Write x for x1 x2 ··· xn . α A term is a monomial multiplied by a field element: cαx . A polynomial is a finite K-linear combination of monomials: X α f = cαx ; α so a polynomial is a finite sum of terms. The support of f are the monomials that appear (with non-zero coefficients) in the polynomial f. If α = (α1; : : : ; αn), put jαj = α1 + ··· + αn. α If f 2 K[x1; : : : ; xn], deg(f) = maxfjαj : x is in the support of fg. Example 2.1. f = 7x3y2z + 11xyz2 deg(f) = maxf6; 4g = 6. 7x3y2z is a term. x3y2z is a monomial. n Given f 2 K[x1; : : : ; xn], evaluation is the map Ff : K ! K given by (c1; : : : ; cn) ! f(c1; : : : ; cn). When is Ff the zero map? Example 2.2. If K is a finite field, Ff can be the zero map without f being the zero polynomial. For instance take the field with two elements, K = Z=2Z, and consider the polynomial f = x2 + x = x(x + 1). Then f is not zero in the ring K[x], however f(c) = 0 for all c 2 K (there are only two to check!). -
Spherical Harmonics and Homogeneous Har- Monic Polynomials
SPHERICAL HARMONICS AND HOMOGENEOUS HAR- MONIC POLYNOMIALS 1. The spherical Laplacean. Denote by S ½ R3 the unit sphere. For a function f(!) de¯ned on S, let f~ denote its extension to an open neighborhood N of S, constant along normals to S (i.e., constant along rays from the origin). We say f 2 C2(S) if f~ is a C2 function in N , and for such functions de¯ne a di®erential operator ¢S by: ¢Sf := ¢f;~ where ¢ on the right-hand side is the usual Laplace operator in R3. With a little work (omitted here) one may derive the expression for ¢ in polar coordinates (r; !) in R2 (r > 0;! 2 S): 2 1 ¢u = u + u + ¢ u: rr r r r2 S (Here ¢Su(r; !) is the operator ¢S acting on the function u(r; :) in S, for each ¯xed r.) A homogeneous polynomial of degree n ¸ 0 in three variables (x; y; z) is a linear combination of `monomials of degree n': d1 d2 d3 x y z ; di ¸ 0; d1 + d2 + d3 = n: This de¯nes a vector space (over R) denoted Pn. A simple combinatorial argument (involving balls and separators, as most of them do), seen in class, yields the dimension: 1 d := dim(P ) = (n + 1)(n + 2): n n 2 Writing a polynomial p 2 Pn in polar coordinates, we necessarily have: n p(r; !) = r f(!); f = pjS; where f is the restriction of p to S. This is an injective linear map p 7! f, but the functions on S so obtained are rather special (a dn-dimensional subspace of the in¯nite-dimensional space C(S) of continuous functions-let's call it Pn(S)) We are interested in the subspace Hn ½ Pn of homogeneous harmonic polynomials of degree n (¢p = 0).