On a Theory of Computation and Complexity Over the Real Numbers: Np-Completeness, Recursive Functions and Universal Machines1
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Infinitary Logic and Inductive Definability Over Finite Structures
University of Pennsylvania ScholarlyCommons Technical Reports (CIS) Department of Computer & Information Science November 1991 Infinitary Logic and Inductive Definability Over Finite Structures Anuj Dawar University of Pennsylvania Steven Lindell University of Pennsylvania Scott Weinstein University of Pennsylvania Follow this and additional works at: https://repository.upenn.edu/cis_reports Recommended Citation Anuj Dawar, Steven Lindell, and Scott Weinstein, "Infinitary Logic and Inductive Definability Over Finite Structures", . November 1991. University of Pennsylvania Department of Computer and Information Science Technical Report No. MS-CIS-91-97. This paper is posted at ScholarlyCommons. https://repository.upenn.edu/cis_reports/365 For more information, please contact [email protected]. Infinitary Logic and Inductive Definability Over Finite Structures Abstract The extensions of first-order logic with a least fixed point operators (FO + LFP) and with a partial fixed point operator (FO + PFP) are known to capture the complexity classes P and PSPACE respectively in the presence of an ordering relation over finite structures. Recently, Abiteboul and Vianu [AV91b] investigated the relation of these two logics in the absence of an ordering, using a mchine model of generic computation. In particular, they showed that the two languages have equivalent expressive power if and only if P = PSPACE. These languages can also be seen as fragments of an infinitary logic where each ω formula has a bounded number of variables, L ∞ω (see, for instance, [KV90]). We present a treatment of the results in [AV91b] from this point of view. In particular, we show that we can write a formula of FO + LFP and P from ordered structures to classes of structures where every element is definable. -
1 Lenore Blum, Matemática Computacional, Algoritmos, Lógica, Geometría Algebraica
MATEMATICOS ACTUALES Lenore Blum, Matemática computacional, Algoritmos, Lógica, Geometría algebraica. Debemos dejar claro desde el comienzo de esta biografía de Lenore Blum que Blum es su apellido de casada, que solo tomó después de casarse con Manuel Blum, que también era matemático. Sin embargo, para evitar confusiones, nos referiremos a ella como Blum a lo largo de este artículo. Los padres de Lenore eran Irving y Rose y, además de una hermana, Harriet, que era dos años menor que Lenore, ella era parte de una extensa familia judía con varias tías y tíos. Su madre Rose era maestra de ciencias de secundaria en Nueva York. Lenore asistió a una escuela pública en la ciudad de Nueva York hasta que tuvo nueve años cuando su familia se mudó a América del Sur. Su padre Irving trabajaba en el negocio de importación/exportación y él y su esposa se instalaron en Venezuela con Lenore y Harriet. Durante su primer año en Caracas, Lenore no asistió a la escuela, sin embargo su madre le enseñó. Básicamente, la familia era demasiado pobre para poder pagar las tasas escolares. Al cabo de un año, Rose ocupó un puesto docente en la Escuela Americana E. Campo Alegre, en Caracas, y esto proporcionó suficiente dinero para permitir que Lenore asistiera a la escuela secundaria y luego a la escuela secundaria en Caracas. Mientras estaba en Caracas, conoció a Manuel Blum, quien también era de una familia judía. Manuel salió de Caracas mientras Lenore todavía estaba allí en la escuela y se fue a los Estados Unidos donde ingresó como estudiante en el Instituto de Tecnología de Massachusetts. -
The Association for Women in Mathematics: How and Why It Was
Mathematical Communities t’s 2011 and the Association for Women in Mathematics The Association (AWM) is celebrating 40 years of supporting and II promoting female students, teachers, and researchers. It’s a joyous occasion filled with good food, warm for Women conversation, and great mathematics—four plenary lectures and eighteen special sessions. There’s even a song for the conference, titled ‘‘((3 + 1) 9 3 + 1) 9 3 + 1 Anniversary in Mathematics: How of the AWM’’ and sung (robustly!) to the tune of ‘‘This Land is Your Land’’ [ICERM 2011]. The spirit of community and and Why It Was the beautiful mathematics on display during ‘‘40 Years and Counting: AWM’s Celebration of Women in Mathematics’’ are truly a triumph for the organization and for women in Founded, and Why mathematics. It’s Still Needed in the 21st Century SARAH J. GREENWALD,ANNE M. LEGGETT, AND JILL E. THOMLEY This column is a forum for discussion of mathematical communities throughout the world, and through all time. Our definition of ‘‘mathematical community’’ is Participants from the Special Session in Number Theory at the broadest: ‘‘schools’’ of mathematics, circles of AWM’s 40th Anniversary Celebration. Back row: Cristina Ballantine, Melanie Matchett Wood, Jackie Anderson, Alina correspondence, mathematical societies, student Bucur, Ekin Ozman, Adriana Salerno, Laura Hall-Seelig, Li-Mei organizations, extra-curricular educational activities Lim, Michelle Manes, Kristin Lauter; Middle row: Brooke Feigon, Jessica Libertini-Mikhaylov, Jen Balakrishnan, Renate (math camps, math museums, math clubs), and more. Scheidler; Front row: Lola Thompson, Hatice Sahinoglu, Bianca Viray, Alice Silverberg, Nadia Heninger. (Photo Cour- What we say about the communities is just as tesy of Kiran Kedlaya.) unrestricted. -
HHMC 2017 (2017 Workshop on Hybrid Human-Machine Computing)
CRonEM CRonEM HHMC 2017 (2017 Workshop on Hybrid Human-Machine Computing) 20 & 21 September 2017 Treetops, Wates House, University of Surrey Guildford, Surrey, UK Programme INTRODUCTION KEYNOTE 1 The 2017 Workshop on Hybrid Human-Machine Computing (HHMC 2017) is 2-day workshop, to be held Title: Password Generation, an Example of Human Computation at the University of Surrey, Guildford, UK, on 20 and 21 September, 2017. It is a workshop co-funded by Abstract: University of Surrey’s Institute for Advanced Studies (IAS), a number of other organizations and related research projects. A password schema is an algorithm for humans - working in their heads - without paper and pencil - to transform challenges (typically website names) into responses (passwords). When we talk about “computing” we often mean computers do something (for humans), but due to the more and more blurred boundary between humans and computers, this old paradigm of “computing” has To start this talk, the speaker will ask for 2 or 3 volunteers, whisper instructions in their ears, then have them changed drastically, e.g., in human computation humans do all or part of the computing (for machines), transform audience-proposed challenges (like AMAZON and FACEBOOK) into passwords. in computer-supported cooperative work (CSCW) humans are working together with assistance from The passwords will look random. The audience will be challenged to guess properties of the passwords but computers to conduct cooperative work, in social computing and computer-mediated communication even the simple schema the speaker whispered to the volunteers will produce passwords that look random. people’s social behaviors are intermingled with computer systems so computing happens with humans and These passwords can be easily made so strong that they pass virtually all password tests, like passwordmeter. -
On Uniformity Within NC
On Uniformity Within NC David A Mix Barrington Neil Immerman HowardStraubing University of Massachusetts University of Massachusetts Boston Col lege Journal of Computer and System Science Abstract In order to study circuit complexity classes within NC in a uniform setting we need a uniformity condition which is more restrictive than those in common use Twosuch conditions stricter than NC uniformity RuCo have app eared in recent research Immermans families of circuits dened by rstorder formulas ImaImb and a unifor mity corresp onding to Buss deterministic logtime reductions Bu We show that these two notions are equivalent leading to a natural notion of uniformity for lowlevel circuit complexity classes Weshow that recent results on the structure of NC Ba still hold true in this very uniform setting Finallyweinvestigate a parallel notion of uniformity still more restrictive based on the regular languages Here we givecharacterizations of sub classes of the regular languages based on their logical expressibility extending recentwork of Straubing Therien and Thomas STT A preliminary version of this work app eared as BIS Intro duction Circuit Complexity Computer scientists have long tried to classify problems dened as Bo olean predicates or functions by the size or depth of Bo olean circuits needed to solve them This eort has Former name David A Barrington Supp orted by NSF grant CCR Mailing address Dept of Computer and Information Science U of Mass Amherst MA USA Supp orted by NSF grants DCR and CCR Mailing address Dept of -
19 Theory of Computation
19 Theory of Computation "You are about to embark on the study of a fascinating and important subject: the theory of computation. It com- prises the fundamental mathematical properties of computer hardware, software, and certain applications thereof. In studying this subject we seek to determine what can and cannot be computed, how quickly, with how much memory, and on which type of computational model." - Michael Sipser, "Introduction to the Theory of Computation", one of the driest computer science textbooks ever In which we go back to the basics with arcane, boring, and irrelevant set theory and counting. This week’s material is made challenging by two orthogonal issues. There’s a whole bunch of stuff to cover, and 95% of it isn’t the least bit interesting to a physical scientist. Nevertheless, being the starry-eyed optimist that I am, I’ll forge ahead through the mountainous bulk of knowledge. In other words, expect these notes to be long! But skim when necessary; if you look at the homework first (and haven’t entirely forgotten the lectures), you should be able to pick out the important parts. I understand if this type of stuff isn’t exactly your cup of tea, but bear with me while you can. In some sense, most of what we refer to as computer science isn’t computer science at all, any more than what an accountant does is math. Sure, modern economics takes some crazy hardcore theory to make it all work, but un- derlying the whole thing is a solid layer of applications and industrial moolah. -
Turing's Influence on Programming — Book Extract from “The Dawn of Software Engineering: from Turing to Dijkstra”
Turing's Influence on Programming | Book extract from \The Dawn of Software Engineering: from Turing to Dijkstra" Edgar G. Daylight∗ Eindhoven University of Technology, The Netherlands [email protected] Abstract Turing's involvement with computer building was popularized in the 1970s and later. Most notable are the books by Brian Randell (1973), Andrew Hodges (1983), and Martin Davis (2000). A central question is whether John von Neumann was influenced by Turing's 1936 paper when he helped build the EDVAC machine, even though he never cited Turing's work. This question remains unsettled up till this day. As remarked by Charles Petzold, one standard history barely mentions Turing, while the other, written by a logician, makes Turing a key player. Contrast these observations then with the fact that Turing's 1936 paper was cited and heavily discussed in 1959 among computer programmers. In 1966, the first Turing award was given to a programmer, not a computer builder, as were several subsequent Turing awards. An historical investigation of Turing's influence on computing, presented here, shows that Turing's 1936 notion of universality became increasingly relevant among programmers during the 1950s. The central thesis of this paper states that Turing's in- fluence was felt more in programming after his death than in computer building during the 1940s. 1 Introduction Many people today are led to believe that Turing is the father of the computer, the father of our digital society, as also the following praise for Martin Davis's bestseller The Universal Computer: The Road from Leibniz to Turing1 suggests: At last, a book about the origin of the computer that goes to the heart of the story: the human struggle for logic and truth. -
The Complexity Zoo
The Complexity Zoo Scott Aaronson www.ScottAaronson.com LATEX Translation by Chris Bourke [email protected] 417 classes and counting 1 Contents 1 About This Document 3 2 Introductory Essay 4 2.1 Recommended Further Reading ......................... 4 2.2 Other Theory Compendia ............................ 5 2.3 Errors? ....................................... 5 3 Pronunciation Guide 6 4 Complexity Classes 10 5 Special Zoo Exhibit: Classes of Quantum States and Probability Distribu- tions 110 6 Acknowledgements 116 7 Bibliography 117 2 1 About This Document What is this? Well its a PDF version of the website www.ComplexityZoo.com typeset in LATEX using the complexity package. Well, what’s that? The original Complexity Zoo is a website created by Scott Aaronson which contains a (more or less) comprehensive list of Complexity Classes studied in the area of theoretical computer science known as Computa- tional Complexity. I took on the (mostly painless, thank god for regular expressions) task of translating the Zoo’s HTML code to LATEX for two reasons. First, as a regular Zoo patron, I thought, “what better way to honor such an endeavor than to spruce up the cages a bit and typeset them all in beautiful LATEX.” Second, I thought it would be a perfect project to develop complexity, a LATEX pack- age I’ve created that defines commands to typeset (almost) all of the complexity classes you’ll find here (along with some handy options that allow you to conveniently change the fonts with a single option parameters). To get the package, visit my own home page at http://www.cse.unl.edu/~cbourke/. -
Canonical Models and the Complexity of Modal Team Logic
On the Complexity of Team Logic and its Two-Variable Fragment Martin Lück Leibniz Universität Hannover, Germany [email protected] Abstract. We study the logic FO(∼), the extension of first-order logic with team semantics by unrestricted Boolean negation. It was recently shown axiomatizable, but otherwise has not yet received much attention in questions of computational complexity. In this paper, we consider its two-variable fragment FO2(∼) and prove that its satisfiability problem is decidable, and in fact complete for the recently introduced non-elementary class TOWER(poly). Moreover, we classify the complexity of model checking of FO(∼) with respect to the number of variables and the quantifier rank, and prove a di- chotomy between PSPACE- and ATIME-ALT(exp, poly)-completeness. To achieve the lower bounds, we propose a translation from modal team logic MTL to FO2(∼) that extends the well-known standard translation from modal logic ML to FO2. For the upper bounds, we translate to a fragment of second-order logic. Keywords: team semantics, two-variable logic, complexity, satisfiability, model checking 2012 ACM Subject Classification: Theory of computation → Complexity theory and logic; Logic; 1. Introduction In the last decades, the work of logicians has unearthed a plethora of decidable fragments of first-order logic FO. Many of these cases are restricted quantifier prefixes, such as the BSR-fragment which contains only ∃∗∀∗-sentences [30]. Others include the guarded arXiv:1804.04968v1 [cs.LO] 13 Apr 2018 fragment GF [1], the recently introduced separated fragment SF [32, 34], or the two-variable fragment FO2 [13, 27, 31]. -
2020 SIGACT REPORT SIGACT EC – Eric Allender, Shuchi Chawla, Nicole Immorlica, Samir Khuller (Chair), Bobby Kleinberg September 14Th, 2020
2020 SIGACT REPORT SIGACT EC – Eric Allender, Shuchi Chawla, Nicole Immorlica, Samir Khuller (chair), Bobby Kleinberg September 14th, 2020 SIGACT Mission Statement: The primary mission of ACM SIGACT (Association for Computing Machinery Special Interest Group on Algorithms and Computation Theory) is to foster and promote the discovery and dissemination of high quality research in the domain of theoretical computer science. The field of theoretical computer science is the rigorous study of all computational phenomena - natural, artificial or man-made. This includes the diverse areas of algorithms, data structures, complexity theory, distributed computation, parallel computation, VLSI, machine learning, computational biology, computational geometry, information theory, cryptography, quantum computation, computational number theory and algebra, program semantics and verification, automata theory, and the study of randomness. Work in this field is often distinguished by its emphasis on mathematical technique and rigor. 1. Awards ▪ 2020 Gödel Prize: This was awarded to Robin A. Moser and Gábor Tardos for their paper “A constructive proof of the general Lovász Local Lemma”, Journal of the ACM, Vol 57 (2), 2010. The Lovász Local Lemma (LLL) is a fundamental tool of the probabilistic method. It enables one to show the existence of certain objects even though they occur with exponentially small probability. The original proof was not algorithmic, and subsequent algorithmic versions had significant losses in parameters. This paper provides a simple, powerful algorithmic paradigm that converts almost all known applications of the LLL into randomized algorithms matching the bounds of the existence proof. The paper further gives a derandomized algorithm, a parallel algorithm, and an extension to the “lopsided” LLL. -
Two-Way Automata Characterizations of L/Poly Versus NL
Two-way automata characterizations of L/poly versus NL Christos A. Kapoutsis1;? and Giovanni Pighizzini2 1 LIAFA, Universit´eParis VII, France 2 DICo, Universit`adegli Studi di Milano, Italia Abstract. Let L/poly and NL be the standard complexity classes, of languages recognizable in logarithmic space by Turing machines which are deterministic with polynomially-long advice and nondeterministic without advice, respectively. We recast the question whether L/poly ⊇ NL in terms of deterministic and nondeterministic two-way finite automata (2dfas and 2nfas). We prove it equivalent to the question whether every s-state unary 2nfa has an equivalent poly(s)-state 2dfa, or whether a poly(h)-state 2dfa can check accessibility in h-vertex graphs (even under unary encoding) or check two-way liveness in h-tall, h-column graphs. This complements two recent improvements of an old theorem of Berman and Lingas. On the way, we introduce new types of reductions between regular languages (even unary ones), use them to prove the completeness of specific languages for two-way nondeterministic polynomial size, and propose a purely combinatorial conjecture that implies L/poly + NL. 1 Introduction A prominent open question in complexity theory asks whether nondeterminism is essential in logarithmic-space Turing machines. Formally, this is the question whether L = NL, for L and NL the standard classes of languages recognizable by logarithmic-space deterministic and nondeterministic Turing machines. In the late 70's, Berman and Lingas [1] connected this question to the comparison between deterministic and nondeterministic two-way finite automata (2dfas and 2nfas), proving that if L = NL, then for every s-state σ-symbol 2nfa there is a poly(sσ)-state 2dfa which agrees with it on all inputs of length ≤ s. -
User's Guide for Complexity: a LATEX Package, Version 0.80
User’s Guide for complexity: a LATEX package, Version 0.80 Chris Bourke April 12, 2007 Contents 1 Introduction 2 1.1 What is complexity? ......................... 2 1.2 Why a complexity package? ..................... 2 2 Installation 2 3 Package Options 3 3.1 Mode Options .............................. 3 3.2 Font Options .............................. 4 3.2.1 The small Option ....................... 4 4 Using the Package 6 4.1 Overridden Commands ......................... 6 4.2 Special Commands ........................... 6 4.3 Function Commands .......................... 6 4.4 Language Commands .......................... 7 4.5 Complete List of Class Commands .................. 8 5 Customization 15 5.1 Class Commands ............................ 15 1 5.2 Language Commands .......................... 16 5.3 Function Commands .......................... 17 6 Extended Example 17 7 Feedback 18 7.1 Acknowledgements ........................... 19 1 Introduction 1.1 What is complexity? complexity is a LATEX package that typesets computational complexity classes such as P (deterministic polynomial time) and NP (nondeterministic polynomial time) as well as sets (languages) such as SAT (satisfiability). In all, over 350 commands are defined for helping you to typeset Computational Complexity con- structs. 1.2 Why a complexity package? A better question is why not? Complexity theory is a more recent, though mature area of Theoretical Computer Science. Each researcher seems to have his or her own preferences as to how to typeset Complexity Classes and has built up their own personal LATEX commands file. This can be frustrating, to say the least, when it comes to collaborations or when one has to go through an entire series of files changing commands for compatibility or to get exactly the look they want (or what may be required).