SIMULATING THE CONSTRUCTIONS OF FINITE FIELDS USING MAPLETS L OEKY H ARYANTO Mathematics Department, Hasanuddin University,

Slides:



Advertisements
Similar presentations
Finite Fields Rong-Jaye Chen. p2. Finite fields 1. Irreducible polynomial f(x)  K[x], f(x) has no proper divisors in K[x] Eg. f(x)=1+x+x 2 is irreducible.
Advertisements

BCH Codes Hsin-Lung Wu NTPU.
Mathematics of Cryptography Part II: Algebraic Structures
Cryptography and Network Security
Information and Coding Theory
CHANNEL CODING REED SOLOMON CODES.
Error Detection and Correction Parity Schemes: Modulo 2 addition (XOR) Word parity Block Parity.
Math 3121 Abstract Algebra I
Cryptography and Network Security Chapter 4
Cryptography and Network Security Chapter 4 Fourth Edition by William Stallings.
Quantum Error Correction Michele Mosca. Quantum Error Correction: Bit Flip Errors l Suppose the environment will effect error (i.e. operation ) on our.
Introduction to Gröbner Bases for Geometric Modeling Geometric & Solid Modeling 1989 Christoph M. Hoffmann.
Chapter 11 Algebraic Coding Theory. Single Error Detection M = (1, 1, …, 1) is the m  1 parity check matrix for single error detection. If c = (0, 1,
Chapter 4 – Finite Fields Introduction  will now introduce finite fields  of increasing importance in cryptography AES, Elliptic Curve, IDEA, Public.
1 Foundations of Interval Computation Trong Wu Phone: Department of Computer Science Southern Illinois University Edwardsville.
Factors, Roots, and zeroes
M. Khalily Dermany Islamic Azad University.  finite number of element  important in number theory, algebraic geometry, Galois theory, cryptography,
MTH-376 Algebra Lecture 1. Instructor: Dr. Muhammad Fazeel Anwar Assistant Professor Department of Mathematics COMSATS Institute of Information Technology.
FINITE FIELDS 7/30 陳柏誠.
Cyclic codes 1 CHAPTER 3: Cyclic and convolution codes Cyclic codes are of interest and importance because They posses rich algebraic structure that can.
CPSC 3730 Cryptography and Network Security
1 Cryptography and Network Security Third Edition by William Stallings Lecture slides by Lawrie Brown Chapter 4 – Finite Fields.
Information Security and Management 4. Finite Fields 8
Cryptography and Network Security Introduction to Finite Fields.
By: Hector L Contreras SSGT / USMC
Great Theoretical Ideas in Computer Science.
Polynomials and Rational Functions (2.1)
Small Finite Fields computation Abstract: This note describes how to use the GF(p^{n}).xls worksheet to compute Small Finite Fields. © César Bravo, 2009.
Section 4.3 Zeros of Polynomials. Approximate the Zeros.
Session 1 Stream ciphers 1.
Chapter 4 – Finite Fields
Data Security and Encryption (CSE348) 1. Lecture # 12 2.
Great Theoretical Ideas in Computer Science.
COMPLEX ZEROS: FUNDAMENTAL THEOREM OF ALGEBRA Why do we have to know imaginary numbers?
Math 1304 Calculus I 2.3 – Rules for Limits.
Information and Coding Theory Cyclic codes Juris Viksna, 2015.
Math 3121 Abstract Algebra I Lecture 10 Finish Section 11 Skip 12 – read on your own Start Section 13.
Review 1.Competing the square geometrically and computationally. 2.Graph the equation from completed the square form using transformations.
Cryptography and Network Security Chapter 4. Introduction  will now introduce finite fields  of increasing importance in cryptography AES, Elliptic.
Complex Zeros and the Fundamental Theorem of Algebra.
FINDING A POLYNOMIAL PASSING THROUGH A POINT. Review: the Linear Factorization Theorem If where n > 1 and a n ≠ 0 then Where c 1, c 2, … c n are complex.
Advanced Engineering Mathematics, 7 th Edition Peter V. O’Neil © 2012 Cengage Learning Engineering. All Rights Reserved. CHAPTER 4 Series Solutions.
International Iran conference on Quantum Information September 2007, Kish Island Evaluation of bounds of codes defined over hexagonal and honeycomb lattices.
Abstract Algebra 2004/9/29Yuh-Ming Huang, CSIE NCNU1 Introduction to Algebra Def 2.0 ( G, * ) G: a set A binary operation * on G : a * b  G  a,b  G.
Solving Polynomials.
Definition of Limit, Properties of Limits Section 2.1a.
1 What you will learn today…  How to use the Fundamental Theorem of Algebra to determine the number of zeros of a polynomial function  How to use your.
2.5 The Fundamental Theorem of Algebra. The Fundamental Theorem of Algebra The Fundamental Theorem of Algebra – If f(x) is a polynomial of degree n, where.
15-499Page :Algorithms and Applications Cryptography II – Number theory (groups and fields)
COMM 604:Channel Coding Course Instructor: Tallal Elshabrawy Instructor Office: C3.321 Lecture Time & Loc.: Tues. 2 nd Slot H19 Instructor
Multiplicative Group The multiplicative group of Z n includes every a, 0
Cryptography and Network Security Third Edition by William Stallings Lecture slides by Lawrie Brown.
Page : 1 bfolieq.drw Technical University of Braunschweig IDA: Institute of Computer and Network Engineering  W. Adi 2011 Lecture-5 Mathematical Background:
Sec 5.3 – Undetermined Coefficients
3.8 Complex Zeros; Fundamental Theorem of Algebra
Algebra II Section 4.5a Complete the Square
Apply the Remainder and Factor Theorems
Introduction to Reed-Solomon Coding ( Part II )
Zeros of a Polynomial Function
I. Finite Field Algebra.
AS-Level Maths: Core 2 for Edexcel
MA5242 Wavelets Lecture 1 Numbers and Vector Spaces
Apply the Fundamental Theorem of Algebra
Packet #9 Zeros of Polynomials
CHAPTER 3: Cyclic and convolution codes
Mathematical Background: Extension Finite Fields
Presentation transcript:

SIMULATING THE CONSTRUCTIONS OF FINITE FIELDS USING MAPLETS L OEKY H ARYANTO Mathematics Department, Hasanuddin University, GSM#s: Related presentations (will be uploaded soon): Factorization of x N  1 over F p

A MOTIVATION FOR EVERY ABSTRACT ALGEBRA INSTRUCTOR: USE THIS PRESENTATION AS A NEW STRATEGY FOR STUDENT-CENTERED LEARNING (SCL) METHOD. The Maplet copies here were created to make students firstly being familiar with (not necessarily mastering the theory of) finite fields before the students being introduced with the theoretical parts of the subject; e.g. before they were given some formal theories which were written in the next page! By the way, since mathematics is a language which is full of written symbols, without visual and ‘seemingly’ interactive presentations, most of students tend to sleep in abstract algebra classes. Nevertheless, IMO most strategies proposed for the SCL method by experts in education are not appropriate for math classes, or even worse than the common usual (old) teaching method.

Theoretical Review Given a prime p and a polynomial f(x)  F p [x] of degree m. Let q = p m. We need f(x) to be primitive; i.e. it has a primitive root a that generates the following multiplicative group of order N = p m  1 F q * ={1, a, a 2, …, a N  1 }. If a is primitive, then using the element 0  f (a), the (additive) factor group F p [x]/(f(x)) and with the obvious multiplicative operator, we can construct a field by identifying the isomorphism F p [x]/(f(x))  F q = F q *  {0} = {0, 1, a, a 2, …, a N  1 }. Main reference: Chapter 3 of W. C. Huffman, V. Pless, Fundamentals of Error- Correcting Codes, Cambridge Univ. Press, 2003

How Maplet determines if F p [x]/(f(x))  F q or F p [x]/(g(x))  F q ? Compute the order of the quotient rings! (Should be equal to p m ) Is q 1 = |F p [x]/(f(x))| = p m ? Is q 2 = |F p [x]/(g(x))| = p m ?

Here F 2 [x]/(f(x)) ≇ F 32 and F 2 [x]/(g(x))  F 16

Wait, CONFUSING NOTATIONS FOR NEW LEARNERS: Different notations for the same mathematical object: 1. F p or GF(p) or Z p are three different notations for the same (prime) field; where p is prime and F p = {0, 1, …, p  1}. 2. F q or GF(q) are two different notations for the same field; the field F q = {0, 1, a, a 2 …, a q  2 } = F p [x]/(f(x)) where f is primitive and of degree m, q = p m. For every k  m, the a k can be presented as a polynomial of degree < m in the indeterminate a. When N = p m  1, we have a q  2 = a N  More confusing for a new learner is the identification between the field F q and its associate linear space: F q = F p  F p  …  F p where the right hand side consists of m factors.

A little bit of group theory: A CYCLIC GROUP GENERATED BY A ZERO OF A PRIMITIVE POLYNOMIAL f(x) OF DEGREE m. The zero of f(x) is a, i.e. f(a) = 0. Symbols: q = p m, N = q – 1 = p m  1. The intended constructed finite field of characteristic p is F q (or GF(q) = GF(p m )) The cyclic group is = {1, a, a 2, …, a N  1 } = F q * = F q DO NOT TRY TO MEMORIZE ALL THESE SYMBOLS RIGHT NOW. YOU WILL REMEMBER MOST OF THEM ONCE YOUR INSTRUCTOR KEEPS RUNNING AND EXPLAINING THE MATERIAL IN THIS PRESENTATION

Notice that a 16 = a 1.

Notice that a 18 = a 3.

Notice that a 20 = a 5.

Notice that a 22 = a 7.

Notice that a 24 = a 9.

Notice that a 26 = a 11.

Notice that a 28 = a 13.

Notice that a 30 = a 15.

A little bit of finite field’s theory: THE SUBFIELD F s OF THE FIELD F q where q = p m and s = p r. Here, F q is the quotient ring F 2 [x]/ where f(x) = x 6 + x + 1. THEOREM (Huffman, Pless, Th (modified)): When q = p m and s = p r (i) F q has subfield F s if and only if r | m; (ii) if r | m, then there is only one field of order s, which is F s, of the field F q The Maplets make use p = 2, q = 64 and s = 8 (equivalently, m = 6 and r = 3) The constructed finite field of order 2 6 (including its elements) is F 64 (or GF(64)) The constructed subfield of order 2 3 (including its elements) is F 8 (or GF(8)) DO NOT TRY TO MEMORIZE THESE THEORIES RIGHT NOW. YOU WILL REMEMBER MOST OF THEM ONCE YOUR INSTRUCTOR KEEPS RUNNING AND EXPLAINING THE MATERIAL IN THIS PRESENTATION

a 0 = 1, b = a 9, b 0 = 1 or a 0 = 1, b = a 4 +a 3 b 0 = 1 F 64 * =  = F 8 *

a 1 = a, b = a 9, b 1 = a 9 or a 1 = a, b = a 4 + a 3, b 1 = a 4 + a 3, F 64 * =  = F 8 *

a 2 = a 2, b = a 9, b 2 = a 18 or a 2 = a 2, b = a 4 + a 3, b 2 = a 3 +a 2 + a 1 + 1

a 3 = a 3, b = a 9, b 3 = a 27 or a 3 = a 3, b = a 4 +a 3 b 3 = a 3 + a 2 + a F 64 * =  = F 8 *

a 4 = a 4, b = a 9, b 4 = a 36 or a 4 = a 4, b = a 4 +a 3 b 4 = a 4 + a 2 + a F 64 * =  = F 8 *

a 5 = a 5, b = a 9, b 5 = a 45 or a 5 = a 5, b = a 4 +a 3 b 5 = a 4 + a F 64 * =  = F 8 *

a 6 = a 6, b = a 9, b 6 = a 54 or a 6 = a + 1 b = a 4 + a 3 b 6 = a 4 + a 2 + a + 1 F 64 * =  = F 8 *

a 7 = a 7, b = a 9, b 7 = a 63 or a 7 = a 2 + a b = a 4 + a 3 b 7 = 1 F 64 * =  = F 8 *

a 8 = a 8, b = a 9, b 8 = a 72 or a 8 = a 3 + a 2 b = a 4 + a 3 b 8 = a 4 + a 3 F 64 * =  = F 8 *

a 9 = a 9, b = a 9, b 9 = a 81 or a 9 = a 4 + a 3 b = a 4 + a 3 b 9 = a 3 + a 2 + a + 1 F 64 * =  = F 8 *

a 10 = a 10, b = a 9, b 10 = a 90 or a 10 = a 5 + a 4 b = a 4 + a 3 b 10 = a 3 + a 2 + a F 64 * =  = F 8 *

a 11 = a 11, b = a 9, b 11 = a 99 or a 11 = a 5 + a + 1 b = a 4 + a 3 b 11 = a 4 + a 2 + a F 64 * =  = F 8 *

a 12 = a 12, b = a 9, b 12 = a 108 or a 12 = a b = a 4 + a 3 b 12 = a 4 + a F 64 * =  = F 8 *

a 13 = a 13, b = a 9, b 13 = a 117 or a 13 = a 3 + a b = a 4 + a 3 b 13 = a 4 + a 2 + a + 1 F 64 * =  = F 8 *

a 14 = a 14, b = a 9, b 14 = a 126 or a 14 = a 4 + a 2 b = a 4 + a 3 b 14 = 1 F 64 * =  = F 8 *

a 61 = a 61, b = a 9, b 61 = a 549 or a 61 = a 5 + a b = a 4 + a 3 b 61 = a 4 + a F 64 * =  = F 8 *

a 62 = a 62, b = a 9, b 62 = a 558 or a 62 = a b = a 4 + a 3 b 61 = a 4 + a 2 + a + 1 F 64 * =  = F 8 *

a 63 = a 63, b = a 9, b 63 = a 567 or a 63 = 1 b = a 4 + a 3 b 63 = 1 F 64 * =  = F 8 *

Conclusion