Growth in Finite Groups and the Graph Isomorphism Problem

Total Page:16

File Type:pdf, Size:1020Kb

Growth in Finite Groups and the Graph Isomorphism Problem Growth in finite groups and the Graph Isomorphism Problem Dissertation for the award of the degree \Doctor rerum naturalium" (Dr. rer. nat.) of the Georg-August-Universit¨atG¨ottingen within the doctoral program \Mathematical Sciences" of the Georg-August University School of Science (GAUSS) submitted by Daniele Dona from Torino G¨ottingen,2020 Thesis committee Harald Andr´esHelfgott Mathematisches Institut Georg-August-Universit¨atG¨ottingen Valentin Blomer Mathematisches Institut Universit¨atBonn Members of the Examination Board First reviewer: Harald Andr´esHelfgott Mathematisches Institut Georg-August-Universit¨atG¨ottingen Second reviewer: Laurent Bartholdi Mathematisches Institut Georg-August-Universit¨atG¨ottingen Further members of the Examination Board Valentin Blomer Mathematisches Institut Universit¨atBonn Axel Munk Institut f¨urMathematische Stochastik Georg-August-Universit¨atG¨ottingen Matthew Tointon Department of Pure Mathematics and Mathematical Statistics University of Cambridge P´eterVarj´u Department of Pure Mathematics and Mathematical Statistics University of Cambridge Date of the oral examination: 17 July 2020. Contents Preface 5 Acknowledgements 7 1 General introduction 11 1.1 Growth in groups, Cayley graphs, diameters . 11 1.2 Finite simple groups . 15 1.3 Babai's conjecture . 19 1.4 Other results on growth and diameter . 22 1.5 The graph isomorphism problem . 26 1.6 Babai's algorithm . 29 2 The Weisfeiler-Leman algorithm and the diameter of Schreier graphs 33 2.1 Introduction . 33 2.2 The upper bound . 38 2.3 The lower bound . 42 2.4 The case of Cayley graphs . 45 2.5 Concluding remarks . 48 3 Short expressions for cosets of permutation subgroups 51 3.1 Standard definitions . 52 3.2 Main theorem: statement . 53 3.3 Elementary routines . 56 3.4 Major routines . 61 3.5 The algorithm . 64 3.5.1 The algorithm, assuming CFSG . 71 3.5.2 The algorithm, not assuming CFSG . 79 3.6 Main theorem: proof . 82 3.7 Concluding remarks . 88 4 Slowly growing sets in Aff(Fq) 91 4.1 Introduction . 92 2 4.2 Number of directions in Fq ...................... 94 4.3 Growth in Aff(Fq)........................... 99 3 4.4 Concluding remarks . 101 5 Diameter bounds for products of finite simple groups 103 5.1 Main theorem . 103 5.2 Preliminaries . 105 5.3 Proof of the main theorem . 106 5.4 Concluding remarks . 109 6 Towards a CFSG-free diameter bound for Alt(n) 111 6.1 Background and strategy . 112 6.2 Tools . 114 6.3 Main theorem . 117 6.4 Concluding remarks . 127 Bibliography 129 4 Preface The present thesis embraces two major areas of mathematics, namely group the- ory (especially growth in finite groups) and graph theory (especially the graph isomorphism problem). Chapter 1 serves as a somewhat lengthy introduction to both, with x1.1-1.2- 1.3-1.4 focusing on growth in groups and x1.5-1.6 on graph isomorphisms. The next two chapters are mostly graph-theoretic, although they bear many connections to growth in groups as well. Chapter 2 is based on the author's published article [Don19c]; its main results are Theorem 2.1.6, Theorem 2.1.7 and Theorem 2.1.8. Chapter 3 is based on the author's preprint [Don18]; its main result is Theorem 3.2.1. The two chapters that follow are entirely on the topic of growth in groups. Chapter 4 is based on the author's preprint [Don19b]; its main results are Theo- rem 4.1.3 and Theorem 4.1.4. Chapter 5 is based on the author's preprint [Don19a]; its main result is Theorem 5.1.1. Finally the last one, Chapter 6, is firmly rooted into both areas at once: more precisely, graph-theoretic tools intervene in group-theoretic problems; its main result is Theorem 6.3.6, dependent on Conjecture 6.3.4. Notation. Any and all notations hold unless otherwise stated. We adopt the big O notation for describing orders of magnitude. If f; g are some real-valued functions, we say f(x) = O(g(x)) to mean that there exists a constant C > 0 such that jf(x)j ≤ Cg(x) for all x in the intersection of the domains of f; g; since we are almost always considering f to have domain N and codomain inside R≥0, in those cases it suffices to say that f(x) ≤ Cg(x) for all x large enough. We also use f(x) = o(g(x)) to mean that for all C > 0 and all x large enough (depending on C) we have f(x) < Cg(x). Finally, f(x) = Ω(g(x)) means that there exists C > 0 such that f(x) ≥ Cg(x) for all x large enough: in this, we follow Knuth's definition of the symbol instead of Hardy and Littlewood's convention (see Knuth's own letter to the editor [Knu76], where \O" is incidentally revealed to be an omicron!). If we want to emphasize that the constant C in the notations above depends on other parameters (say n; k), we write them as indices to the symbol (say On;k(g(x))). Many other authors, especially of the number theory school, use also Vinogradov's and notation: the author appreciates the fact that essentially the same symbol facing two directions can do the job of both O(·) and Ω(·), but he also needs to write things like eO(x), for which Vinogradov provides no solution; thus, no will be used. 5 For the set f1; 2; : : : ; ng of natural numbers from 1 to n, we often write [n] for brevity, as is common in the literature regarding permutation groups; to be clear, the author subscribes to the convention that 0 2 N, but 0 has usually little space in the context of permutations. For us, p denotes a prime number, and q denotes a prime power. If X is a finite set, the set of permutations of X is denoted by Sym(X), and the set of even permutations by Alt(X); in particular, we write Sym(n); Alt(n) for Sym([n]); Alt([n]) (we will not use the notations Sn;An and Symn; Altn that frequently occur elsewhere). As for algebraic groups, say the special linear group, we use the notation SLn(Fq) instead of the equally widespread SL(n; Fq) and SL(n; q). a We use loga x to denote the logarithm of x in base a, and log x to denote (log x)a. Since we will not be using longer expressions than log log x, there is no need to use either notation for the iterated logarithm, as some authors do (and for good reasons need to do). About identity elements, notation varies with the context. For general groups, like in x1 and x5, we use e to denote the group's identity; for permutation groups of degree n like in x3 we use Idn, while for the matrix groups in x4 we use Id without index since we work only with 2×2 matrices. In x2, where several identities coexist, we try and use distinct notations: e for general groups, Idn for n × n matrices, IdX for automorphisms on the object X. In x6, where we work with permutation groups but their identity elements are encountered only in their quality of group identities, we use e. Finally, since we abundantly use several terms describing orders of magnitude, which may be unfamiliar to the readers, we collect them here: k • f(x) is quasipolynomial in x when f(x) ≤ eC log x for some absolute con- stants C; k > 0; • f(x) is polylogarithmic in x when f(x) ≤ C logk x for some absolute constants C; k > 0. 6 Acknowledgements One can always aspire to be like the Laplacian intelligence, embracing the whole universe in her thought, for whom nothing would be uncertain, the future as well as the past always present in her eyes1. And one can always delude oneself about having an arm strong enough to pull Leviathan out of the water2; and being able to produce a book on which everything is contained as a whole, and from it judge the world3, as if Protagoras had actually meant a very specific man to be the measure of all things4. These solitary God-worthy feats one can surely believe to be within reach, and fancy oneself the fixed terminus of eternal counsel5, the skies and the stars revolving and revolving under the push of this one finger6; and expect that all that is in the world bends slowly and surely to one's will, weighed by the doom of one's thought7. But mit der Dummheit k¨ampfenG¨otterselbst vergebens8. And even as I pile quotations in the hope of building a stand high enough for my sense of self- importance, and lose myself in my own mighty station and my stupendous brain9 until disillusion comes too late to evade my own ruinous shipwreck10, I must recognize the many other people around me that have contributed to making this achievement of mine possible, people without whom I would not be standing where I am, and to whom I owe in different ways all that I have today. Half-joking ram- blings aside, I often hesitate, get discouraged, and doubt that the position that I am in is well-deserved11; that is why people who supported me throughout this whole endeavour, and continue to do so even now, deserve all the gratitude that I can muster and should get their due credit. 1Pierre-Simon Laplace, Essai philosophique sur les probabilit´es, p. 4 (1840 edition). 2Anonymous, -Iyy¯ob, 41:1.
Recommended publications
  • The Algebra of Open and Interconnected Systems
    The Algebra of Open and Interconnected Systems Brendan Fong Hertford College University of Oxford arXiv:1609.05382v1 [math.CT] 17 Sep 2016 A thesis submitted for the degree of Doctor of Philosophy in Computer Science Trinity 2016 For all those who have prepared food so I could eat and created homes so I could live over the past four years. You too have laboured to produce this; I hope I have done your labours justice. Abstract Herein we develop category-theoretic tools for understanding network- style diagrammatic languages. The archetypal network-style diagram- matic language is that of electric circuits; other examples include signal flow graphs, Markov processes, automata, Petri nets, chemical reaction networks, and so on. The key feature is that the language is comprised of a number of components with multiple (input/output) terminals, each possibly labelled with some type, that may then be connected together along these terminals to form a larger network. The components form hyperedges between labelled vertices, and so a diagram in this language forms a hypergraph. We formalise the compositional structure by intro- ducing the notion of a hypergraph category. Network-style diagrammatic languages and their semantics thus form hypergraph categories, and se- mantic interpretation gives a hypergraph functor. The first part of this thesis develops the theory of hypergraph categories. In particular, we introduce the tools of decorated cospans and corela- tions. Decorated cospans allow straightforward construction of hyper- graph categories from diagrammatic languages: the inputs, outputs, and their composition are modelled by the cospans, while the `decorations' specify the components themselves.
    [Show full text]
  • IT Project Quality Management
    10 IT Project Quality Management CHAPTER OVERVIEW The focus of this chapter will be on several concepts and philosophies of quality man- agement. By learning about the people who founded the quality movement over the last fifty years, we can better understand how to apply these philosophies and teach- ings to develop a project quality management plan. After studying this chapter, you should understand and be able to: • Describe the Project Management Body of Knowledge (PMBOK) area called project quality management (PQM) and how it supports quality planning, qual ity assurance, quality control, and continuous improvement of the project's products and supporting processes. • Identify several quality gurus, or founders of the quality movement, and their role in shaping quality philosophies worldwide. • Describe some of the more common quality initiatives and management sys tems that include ISO certification, Six Sigma, and the Capability Maturity Model (CMM) for software engineering. • Distinguish between validation and verification activities and how these activi ties support IT project quality management. • Describe the software engineering discipline called configuration management and how it is used to manage the changes associated with all of the project's deliverables and work products. • Apply the quality concepts, methods, and tools introduced in this chapter to develop a project quality plan. GLOBAL TECHNOLOGY SOLUTIONS It was mid-afternoon when Tim Williams walked into the GTS conference room. Two of the Husky Air team members, Sitaraman and Yan, were already seated at the 217 218 CHAPTER 10 / IT PROJECT QUALITY MANAGEMENT conference table. Tim took his usual seat, and asked "So how did the demonstration of the user interface go this morning?" Sitaraman glanced at Yan and then focused his attention on Tim's question.
    [Show full text]
  • Computer Algebra and Mathematics with the HP40G Version 1.0
    Computer Algebra and Mathematics with the HP40G Version 1.0 Renée de Graeve Lecturer at Grenoble I Exact Calculation and Mathematics with the HP40G Acknowledgments It was not believed possible to write an efficient program for computer algebra all on one’s own. But one bright person by the name of Bernard Parisse didn’t know that—and did it! This is his program for computer algebra (called ERABLE), built for the second time into an HP calculator. The development of this calculator has led Bernard Parisse to modify his program somewhat so that the computer algebra functions could be edited and cause the appropriate results to be displayed in the Equation Editor. Explore all the capabilities of this calculator, as set out in the following pages. I would like to thank: • Bernard Parisse for his invaluable counsel, his remarks on the text, his reviews, and for his ability to provide functions on demand both efficiently and graciously. • Jean Tavenas for the concern shown towards the completion of this guide. • Jean Yves Avenard for taking on board our requests, and for writing the PROMPT command in the very spirit of promptness—and with no advance warning. (refer to 6.4.2.). © 2000 Hewlett-Packard, http://www.hp.com/calculators The reproduction, distribution and/or the modification of this document is authorised according to the terms of the GNU Free Documentation License, Version 1.1 or later, published by the Free Software Foundation. A copy of this license exists under the section entitled “GNU Free Documentation License” (Chapter 8, p. 141).
    [Show full text]
  • CAS, an Introduction to the HP Computer Algebra System
    CAS, An introduction to the HP Computer Algebra System Background Any mathematician will quickly appreciate the advantages offered by a CAS, or Computer Algebra System1, which allows the user to perform complex symbolic algebraic manipulations on the calculator. Algebraic integration by parts and by substitution, the solution of differential equations, inequalities, simultaneous equations with algebraic or complex coefficients, the evaluation of limits and many other problems can be solved quickly and easily using a CAS. Importantly, solutions can be obtained as exact values such as 5−1, 25≤ x < or 4π rather than the usual decimal values given by numeric methods of successive approximation. Values can be displayed to almost any degree of accuracy required, allowing the user to view, for example, the exact value of a number such as 100 factorial. The HP CAS The HP CAS system was created by Bernard Parisse, Université de Grenoble, for the HP 49g calculator. It was improved and adapted for inclusion on the HP 40g with the help of Renée De Graeve, Jean-Yves Avenard and Jean Tavenas2. The HP CAS system offers the user a vast array of functions and abilities as well as an easy user interface which displays equations as they appear on the page. It also includes the ability to display many algebraic calculations in ‘step-by-step’ mode, making it an invaluable teaching tool in universities and schools. Functions are grouped by category and accessed via menus at the bottom of the screen. Copyright© 2005, Applications in Mathematics Learning to use the CAS Learning to use the CAS is very easy but, as with any powerful tool, truly effective use requires familiarity and time.
    [Show full text]
  • Access to Communications Technology
    A Access to Communications Technology ABSTRACT digital divide: the Pew Research Center reported in 2019 that 42 percent of African American adults and Early proponents of digital communications tech- 43 percent of Hispanic adults did not have a desk- nology believed that it would be a powerful tool for top or laptop computer at home, compared to only disseminating knowledge and advancing civilization. 18 percent of Caucasian adults. Individuals without While there is little dispute that the Internet has home computers must instead use smartphones or changed society radically in a relatively short period public facilities such as libraries (which restrict how of time, there are many still unable to take advantage long a patron can remain online), which severely lim- of the benefits it confers because of a lack of access. its their ability to fill out job applications and com- Whether the lack is due to economic, geographic, or plete homework effectively. demographic factors, this “digital divide” has serious There is also a marked divide between digital societal repercussions, particularly as most aspects access in highly developed nations and that which of life in the twenty-first century, including banking, is available in other parts of the world. Globally, the health care, and education, are increasingly con- International Telecommunication Union (ITU), a ducted online. specialized agency within the United Nations that deals with information and communication tech- DIGITAL DIVIDE nologies (ICTs), estimates that as many as 3 billion people living in developing countries may still be In its simplest terms, the digital divide refers to the gap unconnected by 2023.
    [Show full text]
  • SMT Solving in a Nutshell
    SAT and SMT Solving in a Nutshell Erika Abrah´ am´ RWTH Aachen University, Germany LuFG Theory of Hybrid Systems February 27, 2020 Erika Abrah´ am´ - SAT and SMT solving 1 / 16 What is this talk about? Satisfiability problem The satisfiability problem is the problem of deciding whether a logical formula is satisfiable. We focus on the automated solution of the satisfiability problem for first-order logic over arithmetic theories, especially using SAT and SMT solving. Erika Abrah´ am´ - SAT and SMT solving 2 / 16 CAS SAT SMT (propositional logic) (SAT modulo theories) Enumeration Computer algebra DP (resolution) systems [Davis, Putnam’60] DPLL (propagation) [Davis,Putnam,Logemann,Loveland’62] Decision procedures NP-completeness [Cook’71] for combined theories CAD Conflict-directed [Shostak’79] [Nelson, Oppen’79] backjumping Partial CAD Virtual CDCL [GRASP’97] [zChaff’04] DPLL(T) substitution Watched literals Equalities and uninterpreted Clause learning/forgetting functions Variable ordering heuristics Bit-vectors Restarts Array theory Arithmetic Decision procedures for first-order logic over arithmetic theories in mathematical logic 1940 Computer architecture development 1960 1970 1980 2000 2010 Erika Abrah´ am´ - SAT and SMT solving 3 / 16 SAT SMT (propositional logic) (SAT modulo theories) Enumeration DP (resolution) [Davis, Putnam’60] DPLL (propagation) [Davis,Putnam,Logemann,Loveland’62] Decision procedures NP-completeness [Cook’71] for combined theories Conflict-directed [Shostak’79] [Nelson, Oppen’79] backjumping CDCL [GRASP’97] [zChaff’04]
    [Show full text]
  • Programming for Computations – Python
    15 Svein Linge · Hans Petter Langtangen Programming for Computations – Python Editorial Board T. J.Barth M.Griebel D.E.Keyes R.M.Nieminen D.Roose T.Schlick Texts in Computational 15 Science and Engineering Editors Timothy J. Barth Michael Griebel David E. Keyes Risto M. Nieminen Dirk Roose Tamar Schlick More information about this series at http://www.springer.com/series/5151 Svein Linge Hans Petter Langtangen Programming for Computations – Python A Gentle Introduction to Numerical Simulations with Python Svein Linge Hans Petter Langtangen Department of Process, Energy and Simula Research Laboratory Environmental Technology Lysaker, Norway University College of Southeast Norway Porsgrunn, Norway On leave from: Department of Informatics University of Oslo Oslo, Norway ISSN 1611-0994 Texts in Computational Science and Engineering ISBN 978-3-319-32427-2 ISBN 978-3-319-32428-9 (eBook) DOI 10.1007/978-3-319-32428-9 Springer Heidelberg Dordrecht London New York Library of Congress Control Number: 2016945368 Mathematic Subject Classification (2010): 26-01, 34A05, 34A30, 34A34, 39-01, 40-01, 65D15, 65D25, 65D30, 68-01, 68N01, 68N19, 68N30, 70-01, 92D25, 97-04, 97U50 © The Editor(s) (if applicable) and the Author(s) 2016 This book is published open access. Open Access This book is distributed under the terms of the Creative Commons Attribution-Non- Commercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, duplication, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, a link is provided to the Creative Commons license and any changes made are indicated.
    [Show full text]
  • Modeling and Analysis of Hybrid Systems
    Building Bridges between Symbolic Computation and Satisfiability Checking Erika Abrah´ am´ RWTH Aachen University, Germany in cooperation with Florian Corzilius, Gereon Kremer, Stefan Schupp and others ISSAC’15, 7 July 2015 Photo: Prior Park, Bath / flickr Liam Gladdy What is this talk about? Satisfiability problem The satisfiability problem is the problem of deciding whether a logical formula is satisfiable. We focus on the automated solution of the satisfiability problem for first-order logic over arithmetic theories, especially on similarities and differences in symbolic computation and SAT and SMT solving. Erika Abrah´ am´ - SMT solving and Symbolic Computation 2 / 39 CAS SAT SMT (propositional logic) (SAT modulo theories) Enumeration Computer algebra DP (resolution) systems [Davis, Putnam’60] DPLL (propagation) [Davis,Putnam,Logemann,Loveland’62] Decision procedures NP-completeness [Cook’71] for combined theories CAD Conflict-directed [Shostak’79] [Nelson, Oppen’79] backjumping Partial CAD Virtual CDCL [GRASP’97] [zChaff’04] DPLL(T) substitution Watched literals Equalities and uninterpreted Clause learning/forgetting functions Variable ordering heuristics Bit-vectors Restarts Array theory Arithmetic Decision procedures for first-order logic over arithmetic theories in mathematical logic 1940 Computer architecture development 1960 1970 1980 2000 2010 Erika Abrah´ am´ - SMT solving and Symbolic Computation 3 / 39 SAT SMT (propositional logic) (SAT modulo theories) Enumeration DP (resolution) [Davis, Putnam’60] DPLL (propagation) [Davis,Putnam,Logemann,Loveland’62]
    [Show full text]
  • Easy-To-Use Chinese MTEX Suite Hongbin Ma
    The PracTEX Journal, 2012, No. 1 Article revision 2012/06/25 Easy-to-use Chinese MTEX Suite Hongbin Ma Email cnedu.bit.mathmhb@ Address School of Automation, Beijing Institute of Technology, Beijing 100081, P. R. China 1 Motivation of Developing MTEX As the main developer of Chinese MTEX Suite , or simply MTEX [1], I started to fall in love with TEX[2] and LATEX[3] in 2002 when I was still a graduate student major- ing in mathematics and cybernetics at the Academy of Mathematics and Systems Science, Chinese Academy of Sciences. At that time, recommended by some se- nior students, I started to use Chinese CTEX Suite , or simply CTEX[4], which was maintained by Dr. Lingyun Wu[5], a researcher in our academy, and is roughly a collection of pre-configured MiKTEX system[6] packaged with other tools such as customized WinEdt[7] for Chinese TEXers. CTEX brings significant benefits to China TEX users and it helps much to popularize the use of LATEX in China, es- pecially in the educational and academic areas with large requirement on mathe- matics typesetting. Furthermore, at that time, CTEX provides one way to typeset Chinese documents easily with LATEX and CCT [8](Chinese-Typesetting-System ), which was initially developed by another researcher Prof. Linbo Zhang[9] in our academy since 1998 for the purpose of typesetting Chinese with LATEX. Besides CCT system, another system called TY (Tian-Yuan ) system [10] was invented by a group in Eastern China Normal University so as to overcome the difficulties of typesetting Chinese with LATEX using different idea.
    [Show full text]
  • Robust Computer Algebra, Theorem Proving, and Oracle AI
    Robust Computer Algebra, Theorem Proving, and Oracle AI Gopal P. Sarma∗ Nick J. Hayyz School of Medicine, Emory University, Atlanta, GA USA Vicarious FPC, San Francisco, CA USA Abstract In the context of superintelligent AI systems, the term “oracle” has two meanings. One refers to modular systems queried for domain-specific tasks. Another usage, referring to a class of systems which may be useful for addressing the value alignment and AI control problems, is a superintelligent AI system that only answers questions. The aim of this manuscript is to survey contemporary research problems related to oracles which align with long-term research goals of AI safety. We examine existing question answering systems and argue that their high degree of architectural heterogeneity makes them poor candidates for rigorous analysis as oracles. On the other hand, we identify computer algebra systems (CASs) as being primitive examples of domain-specific oracles for mathematics and argue that efforts to integrate computer algebra systems with theorem provers, systems which have largely been developed independent of one another, provide a concrete set of problems related to the notion of provable safety that has emerged in the AI safety community. We review approaches to interfacing CASs with theorem provers, describe well-defined architectural deficiencies that have been identified with CASs, and suggest possible lines of research and practical software projects for scientists interested in AI safety. I. Introduction other hand, issues of privacy and surveillance, access and inequality, or economics and policy are Recently, significant public attention has been also of utmost importance and are distinct from drawn to the consequences of achieving human- the specific technical challenges posed by most level artificial intelligence.
    [Show full text]
  • On the Atkinson Formula for the Ζ Function
    On the Atkinson formula for the ζ function Daniele Dona, Sebastian Zuniga Alterman June 23, 2021 Abstract Thanks to Atkinson (1938), we know the first two terms of the asymptotic for- mula for the square mean integral value of the Riemann zeta function ζ on the criti- cal line. Following both his work and the approach of Titchmarsh (1986), we present an explicit version of the Atkinson formula, improving on a recent bound by Simoniˇc 1 3 (2020). Moreover, we extend the Atkinson formula to the range ℜ(s) ∈ 4 , 4 , giv- ing an explicit bound for the square mean integral value of ζ and improving on a bound by Helfgott and the authors (2019). We use mostly classical tools, such as the approximate functional equation and the explicit convexity bounds of the zeta function given by Backlund (1918). 1 Introduction The search for meaningful bounds for ζ(s) in the range 0 < (s) < 1 has spanned more ℜ than a century. The classical conjecture on L∞ bounds, called the Lindel¨of hypothesis, 1 ε states that ζ 2 + it = oε( t ) for any ε > 0; by Hadamard’s three-line theorem and | | ε the functional equation of ζ, this implies in particular that ζ(τ + it) = oε( t ) for 1 | | | | 1 2 τ+ε 1 2 <τ< 1 and ζ(τ + it) = oε( t − ) for 0 <τ< 2 . | 1 | τ | | − +ε Bounds of order t 2 are called convexity bounds, and bounds with even lower exponent are called subconvexity| | bounds. The current best bound is due to Bourgain [6], 13 1 84 +ε who showed that ζ 2 + it = oε( t ).
    [Show full text]
  • Satisfiability Checking and Symbolic Computation
    Satisfiability Checking and Symbolic Computation E. Abrah´am´ 1, J. Abbott11, B. Becker2, A.M. Bigatti3, M. Brain10, B. Buchberger4, A. Cimatti5, J.H. Davenport6, M. England7, P. Fontaine8, S. Forrest9, A. Griggio5, D. Kroening10, W.M. Seiler11 and T. Sturm12 1RWTH Aachen University, Aachen, Germany; 2Albert-Ludwigs-Universit¨at, Freiburg, Germany; 3Universit`adegli studi di Genova, Italy; 4Johannes Kepler Universit¨at, Linz, Austria; 5Fondazione Bruno Kessler, Trento, Italy; 6University of Bath, Bath, U.K.; 7Coventry University, Coventry, U.K.; 8LORIA, Inria, Universit´ede Lorraine, Nancy, France; 9Maplesoft Europe Ltd; 10University of Oxford, Oxford, U.K.; 11Universit¨at Kassel, Kassel, Germany; 12CNRS, LORIA, Nancy, France and Max-Planck-Institut f¨ur Informatik, Saarbr¨ucken, Germany. Abstract Symbolic Computation and Satisfiability Checking are viewed as individual research areas, but they share common interests in the development, implementation and application of decision procedures for arithmetic theories. Despite these commonalities, the two communities are currently only weakly con- nected. We introduce a new project SC2 to build a joint community in this area, supported by a newly accepted EU (H2020-FETOPEN-CSA) project of the same name. We aim to strengthen the connection between these communities by creating common platforms, initiating interaction and exchange, identi- fying common challenges, and developing a common roadmap. This abstract and accompanying poster describes the motivation and aims for the project, and reports on the first activities. 1 Introduction We describe a new project to bring together the communities of Symbolic Computation and Satisfiability Checking into a new joint community, SC2. Both communities have long histories, as illustrated by the tool development timeline in Figure 1, but traditionally they do not interact much even though they are now individually addressing similar problems in non-linear algebra.
    [Show full text]