USING NUMBER FIELDS to COMPUTE LOGARITHMS in FINITE FIELDS 1. Introduction Let Q = Pn, Where P Is a Prime Number and N a Positiv
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APPLICATIONS of GALOIS THEORY 1. Finite Fields Let F Be a Finite Field
CHAPTER IX APPLICATIONS OF GALOIS THEORY 1. Finite Fields Let F be a finite field. It is necessarily of nonzero characteristic p and its prime field is the field with p r elements Fp.SinceFis a vector space over Fp,itmusthaveq=p elements where r =[F :Fp]. More generally, if E ⊇ F are both finite, then E has qd elements where d =[E:F]. As we mentioned earlier, the multiplicative group F ∗ of F is cyclic (because it is a finite subgroup of the multiplicative group of a field), and clearly its order is q − 1. Hence each non-zero element of F is a root of the polynomial Xq−1 − 1. Since 0 is the only root of the polynomial X, it follows that the q elements of F are roots of the polynomial Xq − X = X(Xq−1 − 1). Hence, that polynomial is separable and F consists of the set of its roots. (You can also see that it must be separable by finding its derivative which is −1.) We q may now conclude that the finite field F is the splitting field over Fp of the separable polynomial X − X where q = |F |. In particular, it is unique up to isomorphism. We have proved the first part of the following result. Proposition. Let p be a prime. For each q = pr, there is a unique (up to isomorphism) finite field F with |F | = q. Proof. We have already proved the uniqueness. Suppose q = pr, and consider the polynomial Xq − X ∈ Fp[X]. As mentioned above Df(X)=−1sof(X) cannot have any repeated roots in any extension, i.e. -
A Note on Presentation of General Linear Groups Over a Finite Field
Southeast Asian Bulletin of Mathematics (2019) 43: 217–224 Southeast Asian Bulletin of Mathematics c SEAMS. 2019 A Note on Presentation of General Linear Groups over a Finite Field Swati Maheshwari and R. K. Sharma Department of Mathematics, Indian Institute of Technology Delhi, New Delhi, India Email: [email protected]; [email protected] Received 22 September 2016 Accepted 20 June 2018 Communicated by J.M.P. Balmaceda AMS Mathematics Subject Classification(2000): 20F05, 16U60, 20H25 Abstract. In this article we have given Lie regular generators of linear group GL(2, Fq), n where Fq is a finite field with q = p elements. Using these generators we have obtained presentations of the linear groups GL(2, F2n ) and GL(2, Fpn ) for each positive integer n. Keywords: Lie regular units; General linear group; Presentation of a group; Finite field. 1. Introduction Suppose F is a finite field and GL(n, F) is the general linear the group of n × n invertible matrices and SL(n, F) is special linear group of n × n matrices with determinant 1. We know that GL(n, F) can be written as a semidirect product, GL(n, F)= SL(n, F) oF∗, where F∗ denotes the multiplicative group of F. Let H and K be two groups having presentations H = hX | Ri and K = hY | Si, then a presentation of semidirect product of H and K is given by, −1 H oη K = hX, Y | R,S,xyx = η(y)(x) ∀x ∈ X,y ∈ Y i, where η : K → Aut(H) is a group homomorphism. Now we summarize some literature survey related to the presentation of groups. -
The General Linear Group
18.704 Gabe Cunningham 2/18/05 [email protected] The General Linear Group Definition: Let F be a field. Then the general linear group GLn(F ) is the group of invert- ible n × n matrices with entries in F under matrix multiplication. It is easy to see that GLn(F ) is, in fact, a group: matrix multiplication is associative; the identity element is In, the n × n matrix with 1’s along the main diagonal and 0’s everywhere else; and the matrices are invertible by choice. It’s not immediately clear whether GLn(F ) has infinitely many elements when F does. However, such is the case. Let a ∈ F , a 6= 0. −1 Then a · In is an invertible n × n matrix with inverse a · In. In fact, the set of all such × matrices forms a subgroup of GLn(F ) that is isomorphic to F = F \{0}. It is clear that if F is a finite field, then GLn(F ) has only finitely many elements. An interesting question to ask is how many elements it has. Before addressing that question fully, let’s look at some examples. ∼ × Example 1: Let n = 1. Then GLn(Fq) = Fq , which has q − 1 elements. a b Example 2: Let n = 2; let M = ( c d ). Then for M to be invertible, it is necessary and sufficient that ad 6= bc. If a, b, c, and d are all nonzero, then we can fix a, b, and c arbitrarily, and d can be anything but a−1bc. This gives us (q − 1)3(q − 2) matrices. -
On the Discrete Logarithm Problem in Finite Fields of Fixed Characteristic
On the discrete logarithm problem in finite fields of fixed characteristic Robert Granger1⋆, Thorsten Kleinjung2⋆⋆, and Jens Zumbr¨agel1⋆ ⋆ ⋆ 1 Laboratory for Cryptologic Algorithms School of Computer and Communication Sciences Ecole´ polytechnique f´ed´erale de Lausanne, Switzerland 2 Institute of Mathematics, Universit¨at Leipzig, Germany {robert.granger,thorsten.kleinjung,jens.zumbragel}@epfl.ch Abstract. × For q a prime power, the discrete logarithm problem (DLP) in Fq consists in finding, for × x any g ∈ Fq and h ∈hgi, an integer x such that g = h. For each prime p we exhibit infinitely many n × extension fields Fp for which the DLP in Fpn can be solved in expected quasi-polynomial time. 1 Introduction In this paper we prove the following result. Theorem 1. For every prime p there exist infinitely many explicit extension fields Fpn for which × the DLP in Fpn can be solved in expected quasi-polynomial time exp (1/ log2+ o(1))(log n)2 . (1) Theorem 1 is an easy corollary of the following much stronger result, which we prove by presenting a randomised algorithm for solving any such DLP. Theorem 2. Given a prime power q > 61 that is not a power of 4, an integer k ≥ 18, polyno- q mials h0, h1 ∈ Fqk [X] of degree at most two and an irreducible degree l factor I of h1X − h0, × ∼ the DLP in Fqkl where Fqkl = Fqk [X]/(I) can be solved in expected time qlog2 l+O(k). (2) To deduce Theorem 1 from Theorem 2, note that thanks to Kummer theory, when l = q − 1 q−1 such h0, h1 are known to exist; indeed, for all k there exists an a ∈ Fqk such that I = X −a ∈ q i Fqk [X] is irreducible and therefore I | X − aX. -
A Second Course in Algebraic Number Theory
A second course in Algebraic Number Theory Vlad Dockchitser Prerequisites: • Galois Theory • Representation Theory Overview: ∗ 1. Number Fields (Review, K; OK ; O ; ClK ; etc) 2. Decomposition of primes (how primes behave in eld extensions and what does Galois's do) 3. L-series (Dirichlet's Theorem on primes in arithmetic progression, Artin L-functions, Cheboterev's density theorem) 1 Number Fields 1.1 Rings of integers Denition 1.1. A number eld is a nite extension of Q Denition 1.2. An algebraic integer α is an algebraic number that satises a monic polynomial with integer coecients Denition 1.3. Let K be a number eld. It's ring of integer OK consists of the elements of K which are algebraic integers Proposition 1.4. 1. OK is a (Noetherian) Ring 2. , i.e., ∼ [K:Q] as an abelian group rkZ OK = [K : Q] OK = Z 3. Each can be written as with and α 2 K α = β=n β 2 OK n 2 Z Example. K OK Q Z ( p p [ a] a ≡ 2; 3 mod 4 ( , square free) Z p Q( a) a 2 Z n f0; 1g a 1+ a Z[ 2 ] a ≡ 1 mod 4 where is a primitive th root of unity Q(ζn) ζn n Z[ζn] Proposition 1.5. 1. OK is the maximal subring of K which is nitely generated as an abelian group 2. O`K is integrally closed - if f 2 OK [x] is monic and f(α) = 0 for some α 2 K, then α 2 OK . Example (Of Factorisation). -
Factoring Polynomials Over Finite Fields
Factoring Polynomials over Finite Fields More precisely: Factoring and testing irreduciblity of sparse polynomials over small finite fields Richard P. Brent MSI, ANU joint work with Paul Zimmermann INRIA, Nancy 27 August 2009 Richard Brent (ANU) Factoring Polynomials over Finite Fields 27 August 2009 1 / 64 Outline Introduction I Polynomials over finite fields I Irreducible and primitive polynomials I Mersenne primes Part 1: Testing irreducibility I Irreducibility criteria I Modular composition I Three algorithms I Comparison of the algorithms I The “best” algorithm I Some computational results Part 2: Factoring polynomials I Distinct degree factorization I Avoiding GCDs, blocking I Another level of blocking I Average-case complexity I New primitive trinomials Richard Brent (ANU) Factoring Polynomials over Finite Fields 27 August 2009 2 / 64 Polynomials over finite fields We consider univariate polynomials P(x) over a finite field F. The algorithms apply, with minor changes, for any small positive characteristic, but since time is limited we assume that the characteristic is two, and F = Z=2Z = GF(2). P(x) is irreducible if it has no nontrivial factors. If P(x) is irreducible of degree r, then [Gauss] r x2 = x mod P(x): 2r Thus P(x) divides the polynomial Pr (x) = x − x. In fact, Pr (x) is the product of all irreducible polynomials of degree d, where d runs over the divisors of r. Richard Brent (ANU) Factoring Polynomials over Finite Fields 27 August 2009 3 / 64 Counting irreducible polynomials Let N(d) be the number of irreducible polynomials of degree d. Thus X r dN(d) = deg(Pr ) = 2 : djr By Möbius inversion we see that X rN(r) = µ(d)2r=d : djr Thus, the number of irreducible polynomials of degree r is ! 2r 2r=2 N(r) = + O : r r Since there are 2r polynomials of degree r, the probability that a randomly selected polynomial is irreducible is ∼ 1=r ! 0 as r ! +1. -
Ring (Mathematics) 1 Ring (Mathematics)
Ring (mathematics) 1 Ring (mathematics) In mathematics, a ring is an algebraic structure consisting of a set together with two binary operations usually called addition and multiplication, where the set is an abelian group under addition (called the additive group of the ring) and a monoid under multiplication such that multiplication distributes over addition.a[›] In other words the ring axioms require that addition is commutative, addition and multiplication are associative, multiplication distributes over addition, each element in the set has an additive inverse, and there exists an additive identity. One of the most common examples of a ring is the set of integers endowed with its natural operations of addition and multiplication. Certain variations of the definition of a ring are sometimes employed, and these are outlined later in the article. Polynomials, represented here by curves, form a ring under addition The branch of mathematics that studies rings is known and multiplication. as ring theory. Ring theorists study properties common to both familiar mathematical structures such as integers and polynomials, and to the many less well-known mathematical structures that also satisfy the axioms of ring theory. The ubiquity of rings makes them a central organizing principle of contemporary mathematics.[1] Ring theory may be used to understand fundamental physical laws, such as those underlying special relativity and symmetry phenomena in molecular chemistry. The concept of a ring first arose from attempts to prove Fermat's last theorem, starting with Richard Dedekind in the 1880s. After contributions from other fields, mainly number theory, the ring notion was generalized and firmly established during the 1920s by Emmy Noether and Wolfgang Krull.[2] Modern ring theory—a very active mathematical discipline—studies rings in their own right. -
Sieve Algorithms for the Discrete Logarithm in Medium Characteristic Finite Fields Laurent Grémy
Sieve algorithms for the discrete logarithm in medium characteristic finite fields Laurent Grémy To cite this version: Laurent Grémy. Sieve algorithms for the discrete logarithm in medium characteristic finite fields. Cryptography and Security [cs.CR]. Université de Lorraine, 2017. English. NNT : 2017LORR0141. tel-01647623 HAL Id: tel-01647623 https://tel.archives-ouvertes.fr/tel-01647623 Submitted on 24 Nov 2017 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. AVERTISSEMENT Ce document est le fruit d'un long travail approuvé par le jury de soutenance et mis à disposition de l'ensemble de la communauté universitaire élargie. Il est soumis à la propriété intellectuelle de l'auteur. Ceci implique une obligation de citation et de référencement lors de l’utilisation de ce document. D'autre part, toute contrefaçon, plagiat, reproduction illicite encourt une poursuite pénale. Contact : [email protected] LIENS Code de la Propriété Intellectuelle. articles L 122. 4 Code de la Propriété Intellectuelle. articles L 335.2- L 335.10 http://www.cfcopies.com/V2/leg/leg_droi.php -
Finite Fields: Further Properties
Chapter 4 Finite fields: further properties 8 Roots of unity in finite fields In this section, we will generalize the concept of roots of unity (well-known for complex numbers) to the finite field setting, by considering the splitting field of the polynomial xn − 1. This has links with irreducible polynomials, and provides an effective way of obtaining primitive elements and hence representing finite fields. Definition 8.1 Let n ∈ N. The splitting field of xn − 1 over a field K is called the nth cyclotomic field over K and denoted by K(n). The roots of xn − 1 in K(n) are called the nth roots of unity over K and the set of all these roots is denoted by E(n). The following result, concerning the properties of E(n), holds for an arbitrary (not just a finite!) field K. Theorem 8.2 Let n ∈ N and K a field of characteristic p (where p may take the value 0 in this theorem). Then (i) If p ∤ n, then E(n) is a cyclic group of order n with respect to multiplication in K(n). (ii) If p | n, write n = mpe with positive integers m and e and p ∤ m. Then K(n) = K(m), E(n) = E(m) and the roots of xn − 1 are the m elements of E(m), each occurring with multiplicity pe. Proof. (i) The n = 1 case is trivial. For n ≥ 2, observe that xn − 1 and its derivative nxn−1 have no common roots; thus xn −1 cannot have multiple roots and hence E(n) has n elements. -
The Number Field Sieve for Discrete Logarithms
The Number Field Sieve for Discrete Logarithms Henrik Røst Haarberg Master of Science Submission date: June 2016 Supervisor: Kristian Gjøsteen, MATH Norwegian University of Science and Technology Department of Mathematical Sciences Abstract We present two general number field sieve algorithms solving the discrete logarithm problem in finite fields. The first algorithm pre- sented deals with discrete logarithms in prime fields Fp, while the second considers prime power fields Fpn . We prove, using the standard heuristic, that these algorithms will run in sub-exponential time. We also give an overview of different index calculus algorithms solving the discrete logarithm problem efficiently for different possible relations between the characteristic and the extension degree. To be able to give a good introduction to the algorithms, we present theory necessary to understand the underlying algebraic structures used in the algorithms. This theory is largely algebraic number theory. 1 Contents 1 Introduction 4 1.1 Discrete logarithms . .4 1.2 The general number field sieve and L-notation . .4 2 Theory 6 2.1 Number fields . .6 2.1.1 Dedekind domains . .7 2.1.2 Module structure . .9 2.1.3 Norm of ideals . .9 2.1.4 Units . 10 2.2 Prime ideals . 10 2.3 Smooth numbers . 13 2.3.1 Density . 13 2.3.2 Exponent vectors . 13 3 The number field sieve in prime fields 15 3.1 Overview . 15 3.2 Calculating logarithms . 15 3.3 Sieving . 17 3.4 Schirokauer maps . 18 3.5 Linear algebra . 20 3.5.1 A note about smooth t and g .............. 22 3.6 Run time . -
11.6 Discrete Logarithms Over Finite Fields
Algorithms 61 11.6 Discrete logarithms over finite fields Andrew Odlyzko, University of Minnesota Surveys and detailed expositions with proofs can be found in [7, 25, 26, 28, 33, 34, 47]. 11.6.1 Basic definitions 11.6.1 Remark Discrete exponentiation in a finite field is a direct analog of ordinary exponentiation. The exponent can only be an integer, say n, but for w in a field F , wn is defined except when w = 0 and n ≤ 0, and satisfies the usual properties, in particular wm+n = wmwn and (for u and v in F )(uv)m = umvm. The discrete logarithm is the inverse function, in analogy with the ordinary logarithm for real numbers. If F is a finite field, then it has at least one primitive element g; i.e., all nonzero elements of F are expressible as powers of g, see Chapter ??. 11.6.2 Definition Given a finite field F , a primitive element g of F , and a nonzero element w of F , the discrete logarithm of w to base g, written as logg(w), is the least non-negative integer n such that w = gn. 11.6.3 Remark The value logg(w) is unique modulo q − 1, and 0 ≤ logg(w) ≤ q − 2. It is often convenient to allow it to be represented by any integer n such that w = gn. 11.6.4 Remark The discrete logarithm of w to base g is often called the index of w with respect to the base g. More generally, we can define discrete logarithms in groups. -
Algorithms for Discrete Logarithms in Finite Fields and Elliptic Curves
Algorithms for discrete logarithms in finite fields and elliptic curves ECC “Summer” school 2015 E. Thomé /* */ C,A, /* */ R,a, /* */ M,E, CARAMEL L,i= 5,e, d[5],Q[999 ]={0};main(N ){for (;i--;e=scanf("%" "d",d+i));for(A =*d; ++i<A ;++Q[ i*i% A],R= i[Q]? R:i); for(;i --;) for(M =A;M --;N +=!M*Q [E%A ],e+= Q[(A +E*E- R*L* L%A) %A]) for( E=i,L=M,a=4;a;C= i*E+R*M*L,L=(M*E +i*L) %A,E=C%A+a --[d]);printf ("%d" "\n", (e+N* N)/2 /* cc caramel.c; echo f3 f2 f1 f0 p | ./a.out */ -A);} Sep. 23rd-25th, 2015 Algorithms for discrete logarithms in finite fields and elliptic curves 1/122 Part 1 Context and old algorithms Context, motivations Exponential algorithms L(1/2) algorithms Plan Context, motivations Exponential algorithms L(1/2) algorithms Plan Context, motivations Definition What is hardness? Good and bad families – should we care only about EC? Cost per logarithm The discrete logarithm problem In a cyclic group, written multiplicatively (g, x) → g x is easy: polynomial complexity; (g, g x ) → x is (often) hard: discrete logarithm problem. For an elliptic curve E, written additively: (P, k) → [k]P is easy; (P, Q = [k]P) → x is hard. Cryptographic applications rely on the hardness of the discrete logarithm problem (DLP). Algorithms for discrete logarithms in finite fields and elliptic curves3 Another view on the DLP In case the group we are working on is not itself cyclic, DLP is defined in a cyclic sub-group (say of order n).