Introduction to Fields and Vector Spaces
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On Stochastic Distributions and Currents
NISSUNA UMANA INVESTIGAZIONE SI PUO DIMANDARE VERA SCIENZIA S’ESSA NON PASSA PER LE MATEMATICHE DIMOSTRAZIONI LEONARDO DA VINCI vol. 4 no. 3-4 2016 Mathematics and Mechanics of Complex Systems VINCENZO CAPASSO AND FRANCO FLANDOLI ON STOCHASTIC DISTRIBUTIONS AND CURRENTS msp MATHEMATICS AND MECHANICS OF COMPLEX SYSTEMS Vol. 4, No. 3-4, 2016 dx.doi.org/10.2140/memocs.2016.4.373 ∩ MM ON STOCHASTIC DISTRIBUTIONS AND CURRENTS VINCENZO CAPASSO AND FRANCO FLANDOLI Dedicated to Lucio Russo, on the occasion of his 70th birthday In many applications, it is of great importance to handle random closed sets of different (even though integer) Hausdorff dimensions, including local infor- mation about initial conditions and growth parameters. Following a standard approach in geometric measure theory, such sets may be described in terms of suitable measures. For a random closed set of lower dimension with respect to the environment space, the relevant measures induced by its realizations are sin- gular with respect to the Lebesgue measure, and so their usual Radon–Nikodym derivatives are zero almost everywhere. In this paper, how to cope with these difficulties has been suggested by introducing random generalized densities (dis- tributions) á la Dirac–Schwarz, for both the deterministic case and the stochastic case. For the last one, mean generalized densities are analyzed, and they have been related to densities of the expected values of the relevant measures. Ac- tually, distributions are a subclass of the larger class of currents; in the usual Euclidean space of dimension d, currents of any order k 2 f0; 1;:::; dg or k- currents may be introduced. -
SOME ALGEBRAIC DEFINITIONS and CONSTRUCTIONS Definition
SOME ALGEBRAIC DEFINITIONS AND CONSTRUCTIONS Definition 1. A monoid is a set M with an element e and an associative multipli- cation M M M for which e is a two-sided identity element: em = m = me for all m M×. A−→group is a monoid in which each element m has an inverse element m−1, so∈ that mm−1 = e = m−1m. A homomorphism f : M N of monoids is a function f such that f(mn) = −→ f(m)f(n) and f(eM )= eN . A “homomorphism” of any kind of algebraic structure is a function that preserves all of the structure that goes into the definition. When M is commutative, mn = nm for all m,n M, we often write the product as +, the identity element as 0, and the inverse of∈m as m. As a convention, it is convenient to say that a commutative monoid is “Abelian”− when we choose to think of its product as “addition”, but to use the word “commutative” when we choose to think of its product as “multiplication”; in the latter case, we write the identity element as 1. Definition 2. The Grothendieck construction on an Abelian monoid is an Abelian group G(M) together with a homomorphism of Abelian monoids i : M G(M) such that, for any Abelian group A and homomorphism of Abelian monoids−→ f : M A, there exists a unique homomorphism of Abelian groups f˜ : G(M) A −→ −→ such that f˜ i = f. ◦ We construct G(M) explicitly by taking equivalence classes of ordered pairs (m,n) of elements of M, thought of as “m n”, under the equivalence relation generated by (m,n) (m′,n′) if m + n′ = −n + m′. -
Modular Arithmetic
CS 70 Discrete Mathematics and Probability Theory Fall 2009 Satish Rao, David Tse Note 5 Modular Arithmetic One way to think of modular arithmetic is that it limits numbers to a predefined range f0;1;:::;N ¡ 1g, and wraps around whenever you try to leave this range — like the hand of a clock (where N = 12) or the days of the week (where N = 7). Example: Calculating the day of the week. Suppose that you have mapped the sequence of days of the week (Sunday, Monday, Tuesday, Wednesday, Thursday, Friday, Saturday) to the sequence of numbers (0;1;2;3;4;5;6) so that Sunday is 0, Monday is 1, etc. Suppose that today is Thursday (=4), and you want to calculate what day of the week will be 10 days from now. Intuitively, the answer is the remainder of 4 + 10 = 14 when divided by 7, that is, 0 —Sunday. In fact, it makes little sense to add a number like 10 in this context, you should probably find its remainder modulo 7, namely 3, and then add this to 4, to find 7, which is 0. What if we want to continue this in 10 day jumps? After 5 such jumps, we would have day 4 + 3 ¢ 5 = 19; which gives 5 modulo 7 (Friday). This example shows that in certain circumstances it makes sense to do arithmetic within the confines of a particular number (7 in this example), that is, to do arithmetic by always finding the remainder of each number modulo 7, say, and repeating this for the results, and so on. -
MTH 620: 2020-04-28 Lecture
MTH 620: 2020-04-28 lecture Alexandru Chirvasitu Introduction In this (last) lecture we'll mix it up a little and do some topology along with the homological algebra. I wanted to bring up the cohomology of profinite groups if only briefly, because we discussed these in MTH619 in the context of Galois theory. Consider this as us connecting back to that material. 1 Topological and profinite groups This is about the cohomology of profinite groups; we discussed these briefly in MTH619 during Fall 2019, so this will be a quick recollection. First things first though: Definition 1.1 A topological group is a group G equipped with a topology, such that both the multiplication G × G ! G and the inverse map g 7! g−1 are continuous. Unless specified otherwise, all of our topological groups will be assumed separated (i.e. Haus- dorff) as topological spaces. Ordinary, plain old groups can be regarded as topological groups equipped with the discrete topology (i.e. so that all subsets are open). When I want to be clear we're considering plain groups I might emphasize that by referring to them as `discrete groups'. The main concepts we will work with are covered by the following two definitions (or so). Definition 1.2 A profinite group is a compact (and as always for us, Hausdorff) topological group satisfying any of the following equivalent conditions: Q G embeds as a closed subgroup into a product i2I Gi of finite groups Gi, equipped with the usual product topology; For every open neighborhood U of the identity 1 2 G there is a normal, open subgroup N E G contained in U. -
Arxiv:2011.03427V2 [Math.AT] 12 Feb 2021 Riae Fmp Ffiiest.W Eosrt Hscategor This Demonstrate We Sets
HYPEROCTAHEDRAL HOMOLOGY FOR INVOLUTIVE ALGEBRAS DANIEL GRAVES Abstract. Hyperoctahedral homology is the homology theory associated to the hyperoctahe- dral crossed simplicial group. It is defined for involutive algebras over a commutative ring using functor homology and the hyperoctahedral bar construction of Fiedorowicz. The main result of the paper proves that hyperoctahedral homology is related to equivariant stable homotopy theory: for a discrete group of odd order, the hyperoctahedral homology of the group algebra is isomorphic to the homology of the fixed points under the involution of an equivariant infinite loop space built from the classifying space of the group. Introduction Hyperoctahedral homology for involutive algebras was introduced by Fiedorowicz [Fie, Sec- tion 2]. It is the homology theory associated to the hyperoctahedral crossed simplicial group [FL91, Section 3]. Fiedorowicz and Loday [FL91, 6.16] had shown that the homology theory constructed from the hyperoctahedral crossed simplicial group via a contravariant bar construc- tion, analogously to cyclic homology, was isomorphic to Hochschild homology and therefore did not detect the action of the hyperoctahedral groups. Fiedorowicz demonstrated that a covariant bar construction did detect this action and sketched results connecting the hyperoctahedral ho- mology of monoid algebras and group algebras to May’s two-sided bar construction and infinite loop spaces, though these were never published. In Section 1 we recall the hyperoctahedral groups. We recall the hyperoctahedral category ∆H associated to the hyperoctahedral crossed simplicial group. This category encodes an involution compatible with an order-preserving multiplication. We introduce the category of involutive non-commutative sets, which encodes the same information by adding data to the preimages of maps of finite sets. -
10 Heat Equation: Interpretation of the Solution
Math 124A { October 26, 2011 «Viktor Grigoryan 10 Heat equation: interpretation of the solution Last time we considered the IVP for the heat equation on the whole line u − ku = 0 (−∞ < x < 1; 0 < t < 1); t xx (1) u(x; 0) = φ(x); and derived the solution formula Z 1 u(x; t) = S(x − y; t)φ(y) dy; for t > 0; (2) −∞ where S(x; t) is the heat kernel, 1 2 S(x; t) = p e−x =4kt: (3) 4πkt Substituting this expression into (2), we can rewrite the solution as 1 1 Z 2 u(x; t) = p e−(x−y) =4ktφ(y) dy; for t > 0: (4) 4πkt −∞ Recall that to derive the solution formula we first considered the heat IVP with the following particular initial data 1; x > 0; Q(x; 0) = H(x) = (5) 0; x < 0: Then using dilation invariance of the Heaviside step function H(x), and the uniquenessp of solutions to the heat IVP on the whole line, we deduced that Q depends only on the ratio x= t, which lead to a reduction of the heat equation to an ODE. Solving the ODE and checking the initial condition (5), we arrived at the following explicit solution p x= 4kt 1 1 Z 2 Q(x; t) = + p e−p dp; for t > 0: (6) 2 π 0 The heat kernel S(x; t) was then defined as the spatial derivative of this particular solution Q(x; t), i.e. @Q S(x; t) = (x; t); (7) @x and hence it also solves the heat equation by the differentiation property. -
Discrete Mathematics
Slides for Part IA CST 2016/17 Discrete Mathematics <www.cl.cam.ac.uk/teaching/1617/DiscMath> Prof Marcelo Fiore [email protected] — 0 — What are we up to ? ◮ Learn to read and write, and also work with, mathematical arguments. ◮ Doing some basic discrete mathematics. ◮ Getting a taste of computer science applications. — 2 — What is Discrete Mathematics ? from Discrete Mathematics (second edition) by N. Biggs Discrete Mathematics is the branch of Mathematics in which we deal with questions involving finite or countably infinite sets. In particular this means that the numbers involved are either integers, or numbers closely related to them, such as fractions or ‘modular’ numbers. — 3 — What is it that we do ? In general: Build mathematical models and apply methods to analyse problems that arise in computer science. In particular: Make and study mathematical constructions by means of definitions and theorems. We aim at understanding their properties and limitations. — 4 — Lecture plan I. Proofs. II. Numbers. III. Sets. IV. Regular languages and finite automata. — 6 — Proofs Objectives ◮ To develop techniques for analysing and understanding mathematical statements. ◮ To be able to present logical arguments that establish mathematical statements in the form of clear proofs. ◮ To prove Fermat’s Little Theorem, a basic result in the theory of numbers that has many applications in computer science. — 16 — Proofs in practice We are interested in examining the following statement: The product of two odd integers is odd. This seems innocuous enough, but it is in fact full of baggage. — 18 — Proofs in practice We are interested in examining the following statement: The product of two odd integers is odd. -
EE 595 (PMP) Advanced Topics in Communication Theory Handout #1
EE 595 (PMP) Advanced Topics in Communication Theory Handout #1 Introduction to Cryptography. Symmetric Encryption.1 Wednesday, January 13, 2016 Tamara Bonaci Department of Electrical Engineering University of Washington, Seattle Outline: 1. Review - Security goals 2. Terminology 3. Secure communication { Symmetric vs. asymmetric setting 4. Background: Modular arithmetic 5. Classical cryptosystems { The shift cipher { The substitution cipher 6. Background: The Euclidean Algorithm 7. More classical cryptosystems { The affine cipher { The Vigen´erecipher { The Hill cipher { The permutation cipher 8. Cryptanalysis { The Kerchoff Principle { Types of cryptographic attacks { Cryptanalysis of the shift cipher { Cryptanalysis of the affine cipher { Cryptanalysis of the Vigen´erecipher { Cryptanalysis of the Hill cipher Review - Security goals Last lecture, we introduced the following security goals: 1. Confidentiality - ability to keep information secret from all but authorized users. 2. Data integrity - property ensuring that messages to and from a user have not been corrupted by communication errors or unauthorized entities on their way to a destination. 3. Identity authentication - ability to confirm the unique identity of a user. 4. Message authentication - ability to undeniably confirm message origin. 5. Authorization - ability to check whether a user has permission to conduct some action. 6. Non-repudiation - ability to prevent the denial of previous commitments or actions (think of a con- tract). 7. Certification - endorsement of information by a trusted entity. In the rest of today's lecture, we will focus on three of these goals, namely confidentiality, integrity and authentication (CIA). In doing so, we begin by introducing the necessary terminology. 1 We thank Professors Radha Poovendran and Andrew Clark for the help in preparing this material. -
Chapter 3 Proofs
Chapter 3 Proofs Many mathematical proofs use a small range of standard outlines: direct proof, examples/counter-examples, and proof by contrapositive. These notes explain these basic proof methods, as well as how to use definitions of new concepts in proofs. More advanced methods (e.g. proof by induction, proof by contradiction) will be covered later. 3.1 Proving a universal statement Now, let’s consider how to prove a claim like For every rational number q, 2q is rational. First, we need to define what we mean by “rational”. A real number r is rational if there are integers m and n, n = 0, such m that r = n . m In this definition, notice that the fraction n does not need to satisfy conditions like being proper or in lowest terms So, for example, zero is rational 0 because it can be written as 1 . However, it’s critical that the two numbers 27 CHAPTER 3. PROOFS 28 in the fraction be integers, since even irrational numbers can be written as π fractions with non-integers on the top and/or bottom. E.g. π = 1 . The simplest technique for proving a claim of the form ∀x ∈ A, P (x) is to pick some representative value for x.1. Think about sticking your hand into the set A with your eyes closed and pulling out some random element. You use the fact that x is an element of A to show that P (x) is true. Here’s what it looks like for our example: Proof: Let q be any rational number. -
Quaternion Algebra and Calculus
Quaternion Algebra and Calculus David Eberly, Geometric Tools, Redmond WA 98052 https://www.geometrictools.com/ This work is licensed under the Creative Commons Attribution 4.0 International License. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ or send a letter to Creative Commons, PO Box 1866, Mountain View, CA 94042, USA. Created: March 2, 1999 Last Modified: August 18, 2010 Contents 1 Quaternion Algebra 2 2 Relationship of Quaternions to Rotations3 3 Quaternion Calculus 5 4 Spherical Linear Interpolation6 5 Spherical Cubic Interpolation7 6 Spline Interpolation of Quaternions8 1 This document provides a mathematical summary of quaternion algebra and calculus and how they relate to rotations and interpolation of rotations. The ideas are based on the article [1]. 1 Quaternion Algebra A quaternion is given by q = w + xi + yj + zk where w, x, y, and z are real numbers. Define qn = wn + xni + ynj + znk (n = 0; 1). Addition and subtraction of quaternions is defined by q0 ± q1 = (w0 + x0i + y0j + z0k) ± (w1 + x1i + y1j + z1k) (1) = (w0 ± w1) + (x0 ± x1)i + (y0 ± y1)j + (z0 ± z1)k: Multiplication for the primitive elements i, j, and k is defined by i2 = j2 = k2 = −1, ij = −ji = k, jk = −kj = i, and ki = −ik = j. Multiplication of quaternions is defined by q0q1 = (w0 + x0i + y0j + z0k)(w1 + x1i + y1j + z1k) = (w0w1 − x0x1 − y0y1 − z0z1)+ (w0x1 + x0w1 + y0z1 − z0y1)i+ (2) (w0y1 − x0z1 + y0w1 + z0x1)j+ (w0z1 + x0y1 − y0x1 + z0w1)k: Multiplication is not commutative in that the products q0q1 and q1q0 are not necessarily equal. -
WORKSHEET # 7 QUATERNIONS the Set of Quaternions Are the Set Of
WORKSHEET # 7 QUATERNIONS The set of quaternions are the set of all formal R-linear combinations of \symbols" i; j; k a + bi + cj + dk for a; b; c; d 2 R. We give them the following addition rule: (a + bi + cj + dk) + (a0 + b0i + c0j + d0k) = (a + a0) + (b + b0)i + (c + c0)j + (d + d0)k Multiplication is induced by the following rules (λ 2 R) i2 = j2 = k2 = −1 ij = k; jk = i; ki = j ji = −k kj = −i ik = −j λi = iλ λj = jλ λk = kλ combined with the distributive rule. 1. Use the above rules to carefully write down the product (a + bi + cj + dk)(a0 + b0i + c0j + d0k) as an element of the quaternions. Solution: (a + bi + cj + dk)(a0 + b0i + c0j + d0k) = aa0 + ab0i + ac0j + ad0k + ba0i − bb0 + bc0k − bd0j ca0j − cb0k − cc0 + cd0i + da0k + db0j − dc0i − dd0 = (aa0 − bb0 − cc0 − dd0) + (ab0 + a0b + cd0 − dc0)i (ac0 − bd0 + ca0 + db0)j + (ad0 + bc0 − cb0 + da0)k 2. Prove that the quaternions form a ring. Solution: It is obvious that the quaternions form a group under addition. We just showed that they were closed under multiplication. We have defined them to satisfy the distributive property. The only thing left is to show the associative property. I will only prove this for the elements i; j; k (this is sufficient by the distributive property). i(ij) = i(k) = ik = −j = (ii)j i(ik) = i(−j) = −ij = −k = (ii)k i(ji) = i(−k) = −ik = j = ki = (ij)i i(jj) = −i = kj = (ij)j i(jk) = i(i) = (−1) = (k)k = (ij)k i(ki) = ij = k = −ji = (ik)i i(kk) = −i = −jk = (ik)k j(ii) = −j = −ki = (ji)i j(ij) = jk = i = −kj = (ji)j j(ik) = j(−j) = 1 = −kk = (ji)k j(ji) = j(−k) = −jk = −i = (jj)i j(jk) = ji = −k = (jj)k j(ki) = jj = −1 = ii = (jk)i j(kj) = j(−i) = −ji = k = ij = (jk)j j(kk) = −j = ik = (jk)k k(ii) = −k = ji = (ki)i k(ij) = kk = −1 = jj = (ki)j k(ik) = k(−j) = −kj = i = jk = (ki)k k(ji) = k(−k) = 1 = (−i)i = (kj)i k(jj) = k(−1) = −k = −ij = (kj)j k(jk) = ki = j = −ik = (kj)k k(ki) = kj = −i = (kk)i k(kj) = k(−i) = −ki = −j = (kk)j 1 WORKSHEET #7 2 3. -
Structure Theory of Set Addition
Structure Theory of Set Addition Notes by B. J. Green1 ICMS Instructional Conference in Combinatorial Aspects of Mathematical Analysis, Edinburgh March 25 { April 5 2002. 1 Lecture 1: Pl¨unnecke's Inequalities 1.1 Introduction The object of these notes is to explain a recent proof by Ruzsa of a famous result of Freiman, some significant modifications of Ruzsa's proof due to Chang, and all the background material necessary to understand these arguments. Freiman's theorem concerns the structure of sets with small sumset. Let A be a subset of an abelian group G, and define the sumset A + A to be the set of all pairwise sums a + a0, where a; a0 are (not necessarily distinct) elements of A. If A = n then A + A n, and equality can occur (for example if A is a subgroup of G).j Inj the otherj directionj ≥ we have A + A n(n + 1)=2, and equality can occur here too, for example when G = Z and j j ≤ 2 n 1 A = 1; 3; 3 ;:::; 3 − . It is easy to construct similar examples of sets with large sumset, but ratherf harder to findg examples with A + A small. Let us think more carefully about this problem in the special case G = Z. Proposition 1 Let A Z have size n. Then A + A 2n 1, with equality if and only if A is an arithmetic progression⊆ of length n. j j ≥ − Proof. Write A = a1; : : : ; an where a1 < a2 < < an. Then we have f g ··· a1 + a1 < a1 + a2 < < a1 + an < a2 + an < < an + an; ··· ··· which amounts to an exhibition of 2n 1 distinct elements of A + A.