Michael Oser Rabin Automata, Logic and Randomness in Computation
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Tarjan Transcript Final with Timestamps
A.M. Turing Award Oral History Interview with Robert (Bob) Endre Tarjan by Roy Levin San Mateo, California July 12, 2017 Levin: My name is Roy Levin. Today is July 12th, 2017, and I’m in San Mateo, California at the home of Robert Tarjan, where I’ll be interviewing him for the ACM Turing Award Winners project. Good afternoon, Bob, and thanks for spending the time to talk to me today. Tarjan: You’re welcome. Levin: I’d like to start by talking about your early technical interests and where they came from. When do you first recall being interested in what we might call technical things? Tarjan: Well, the first thing I would say in that direction is my mom took me to the public library in Pomona, where I grew up, which opened up a huge world to me. I started reading science fiction books and stories. Originally, I wanted to be the first person on Mars, that was what I was thinking, and I got interested in astronomy, started reading a lot of science stuff. I got to junior high school and I had an amazing math teacher. His name was Mr. Wall. I had him two years, in the eighth and ninth grade. He was teaching the New Math to us before there was such a thing as “New Math.” He taught us Peano’s axioms and things like that. It was a wonderful thing for a kid like me who was really excited about science and mathematics and so on. The other thing that happened was I discovered Scientific American in the public library and started reading Martin Gardner’s columns on mathematical games and was completely fascinated. -
1 Introduction and Contents
University of Padova - DEI Course “Introduction to Natural Language Processing”, Academic Year 2002-2003 Term paper Fast Matrix Multiplication PhD Student: Carlo Fantozzi, XVI ciclo 1 Introduction and Contents This term paper illustrates some results concerning the fast multiplication of n × n matrices: we use the adjective “fast” as a synonym of “in time asymptotically lower than n3”. This subject is relevant to natural language processing since, in 1975, Valiant showed [27] that Boolean matrix multiplication can be used to parse context-free grammars (or CFGs, for short): as a consequence, a fast boolean matrix multiplication algorithm yields a fast CFG parsing algorithm. Indeed, Valiant’s algorithm parses a string of length n in time proportional to TBOOL(n), i.e. the time required to multiply two n × n boolean matrices. Although impractical because of its high constants, Valiant’s algorithm is the asymptotically fastest CFG parsing solution known to date. A simpler (hence nearer to practicality) version of Valiant’s algorithm has been devised by Rytter [20]. One might hope to find a fast, practical parsing scheme which do not rely on matrix multiplica- tion: however, some results seem to suggest that this is a hard quest. Satta has demonstrated [21] that tree-adjoining grammar (TAG) parsing can be reduced to boolean matrix multiplication. Subsequently, Lee has proved [18] that any CFG parser running in time O gn3−, with g the size of the context-free grammar, can be converted into an O m3−/3 boolean matrix multiplication algorithm∗; the constants involved in the translation process are small. Since canonical parsing schemes exhibit a linear depen- dence on g, it can be reasonably stated that fast, practical CFG parsing algorithms can be translated into fast matrix multiplication algorithms. -
Qualitative and Quantitative Security Analyses for Zigbee Wireless Sensor Networks
Downloaded from orbit.dtu.dk on: Sep 27, 2018 Qualitative and Quantitative Security Analyses for ZigBee Wireless Sensor Networks Yuksel, Ender; Nielson, Hanne Riis; Nielson, Flemming Publication date: 2011 Document Version Publisher's PDF, also known as Version of record Link back to DTU Orbit Citation (APA): Yuksel, E., Nielson, H. R., & Nielson, F. (2011). Qualitative and Quantitative Security Analyses for ZigBee Wireless Sensor Networks. Kgs. Lyngby, Denmark: Technical University of Denmark (DTU). (IMM-PHD-2011; No. 247). General rights Copyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright owners and it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights. • Users may download and print one copy of any publication from the public portal for the purpose of private study or research. • You may not further distribute the material or use it for any profit-making activity or commercial gain • You may freely distribute the URL identifying the publication in the public portal If you believe that this document breaches copyright please contact us providing details, and we will remove access to the work immediately and investigate your claim. Qualitative and Quantitative Security Analyses for ZigBee Wireless Sensor Networks Ender Y¨uksel Kongens Lyngby 2011 IMM-PHD-2011-247 Technical University of Denmark Informatics and Mathematical Modelling Building 321, DK-2800 Kongens Lyngby, Denmark Phone +45 45253351, Fax +45 45882673 [email protected] www.imm.dtu.dk IMM-PHD: ISSN 0909-3192 Summary Wireless sensor networking is a challenging and emerging technology that will soon become an inevitable part of our modern society. -
Mathematics People
Mathematics People Srinivas Receives TWAS Prize Strassen Awarded ACM Knuth in Mathematics Prize Vasudevan Srinivas of the Tata Institute of Fundamental Volker Strassen of the University of Konstanz has been Research, Mumbai, has been named the winner of the 2008 awarded the 2008 Knuth Prize of the Association for TWAS Prize in Mathematics, awarded by the Academy of Computing Machinery (ACM) Special Interest Group on Sciences for the Developing World (TWAS). He was hon- Algorithms and Computation Theory (SIGACT). He was ored “for his basic contributions to algebraic geometry honored for his contributions to the theory and practice that have helped deepen our understanding of cycles, of algorithm design. The award carries a cash prize of motives, and K-theory.” Srinivas will receive a cash prize US$5,000. of US$15,000 and will deliver a lecture at the academy’s According to the prize citation, “Strassen’s innovations twentieth general meeting, to be held in South Africa in enabled fast and efficient computer algorithms, the se- September 2009. quence of instructions that tells a computer how to solve a particular problem. His discoveries resulted in some of the —From a TWAS announcement most important algorithms used today on millions if not billions of computers around the world and fundamentally altered the field of cryptography, which uses secret codes Pujals Awarded ICTP/IMU to protect data from theft or alteration.” Ramanujan Prize His algorithms include fast matrix multiplication, inte- ger multiplication, and a test for the primality -
Relations and Equivalences Between Circuit Lower Bounds and Karp-Lipton Theorems*
Electronic Colloquium on Computational Complexity, Report No. 75 (2019) Relations and Equivalences Between Circuit Lower Bounds and Karp-Lipton Theorems* Lijie Chen Dylan M. McKay Cody D. Murray† R. Ryan Williams MIT MIT MIT Abstract A frontier open problem in circuit complexity is to prove PNP 6⊂ SIZE[nk] for all k; this is a neces- NP sary intermediate step towards NP 6⊂ P=poly. Previously, for several classes containing P , including NP NP NP , ZPP , and S2P, such lower bounds have been proved via Karp-Lipton-style Theorems: to prove k C 6⊂ SIZE[n ] for all k, we show that C ⊂ P=poly implies a “collapse” D = C for some larger class D, where we already know D 6⊂ SIZE[nk] for all k. It seems obvious that one could take a different approach to prove circuit lower bounds for PNP that does not require proving any Karp-Lipton-style theorems along the way. We show this intuition is wrong: (weak) Karp-Lipton-style theorems for PNP are equivalent to fixed-polynomial size circuit lower NP NP k NP bounds for P . That is, P 6⊂ SIZE[n ] for all k if and only if (NP ⊂ P=poly implies PH ⊂ i.o.-P=n ). Next, we present new consequences of the assumption NP ⊂ P=poly, towards proving similar re- sults for NP circuit lower bounds. We show that under the assumption, fixed-polynomial circuit lower bounds for NP, nondeterministic polynomial-time derandomizations, and various fixed-polynomial time simulations of NP are all equivalent. Applying this equivalence, we show that circuit lower bounds for NP imply better Karp-Lipton collapses. -
The Computational Complexity of Nash Equilibria in Concisely Represented Games∗
Electronic Colloquium on Computational Complexity, Report No. 52 (2005) The Computational Complexity of Nash Equilibria in Concisely Represented Games∗ Grant R. Schoenebeck y Salil P. Vadhanz May 4, 2005 Abstract Games may be represented in many different ways, and different representations of games affect the complexity of problems associated with games, such as finding a Nash equilibrium. The traditional method of representing a game is to explicitly list all the payoffs, but this incurs an exponential blowup as the number of agents grows. We study two models of concisely represented games: circuit games, where the payoffs are computed by a given boolean circuit, and graph games, where each agent's payoff is a function of only the strategies played by its neighbors in a given graph. For these two models, we study the complexity of four questions: determining if a given strategy is a Nash equilibrium, finding a Nash equilibrium, determining if there exists a pure Nash equilibrium, and determining if there exists a Nash equilibrium in which the payoffs to a player meet some given guarantees. In many cases, we obtain tight results, showing that the problems are complete for various complexity classes. 1 Introduction In recent years, there has been a surge of interest at the interface between computer science and game theory. On one hand, game theory and its notions of equilibria provide a rich framework for modelling the behavior of selfish agents in the kinds of distributed or networked environments that often arise in computer science, and offer mechanisms to achieve efficient and desirable global outcomes in spite of the selfish behavior. -
Diffie and Hellman Receive 2015 Turing Award Rod Searcey/Stanford University
Diffie and Hellman Receive 2015 Turing Award Rod Searcey/Stanford University. Linda A. Cicero/Stanford News Service. Whitfield Diffie Martin E. Hellman ernment–private sector relations, and attracts billions of Whitfield Diffie, former chief security officer of Sun Mi- dollars in research and development,” said ACM President crosystems, and Martin E. Hellman, professor emeritus Alexander L. Wolf. “In 1976, Diffie and Hellman imagined of electrical engineering at Stanford University, have been a future where people would regularly communicate awarded the 2015 A. M. Turing Award of the Association through electronic networks and be vulnerable to having for Computing Machinery for their critical contributions their communications stolen or altered. Now, after nearly to modern cryptography. forty years, we see that their forecasts were remarkably Citation prescient.” The ability for two parties to use encryption to commu- “Public-key cryptography is fundamental for our indus- nicate privately over an otherwise insecure channel is try,” said Andrei Broder, Google Distinguished Scientist. fundamental for billions of people around the world. On “The ability to protect private data rests on protocols for a daily basis, individuals establish secure online connec- confirming an owner’s identity and for ensuring the integ- tions with banks, e-commerce sites, email servers, and the rity and confidentiality of communications. These widely cloud. Diffie and Hellman’s groundbreaking 1976 paper, used protocols were made possible through the ideas and “New Directions in Cryptography,” introduced the ideas of methods pioneered by Diffie and Hellman.” public-key cryptography and digital signatures, which are Cryptography is a practice that facilitates communi- the foundation for most regularly used security protocols cation between two parties so that the communication on the Internet today. -
Curriculum Vitae
Massachusetts Institute of Technology School of Engineering Faculty Personnel Record Date: April 1, 2020 Full Name: Charles E. Leiserson Department: Electrical Engineering and Computer Science 1. Date of Birth November 10, 1953 2. Citizenship U.S.A. 3. Education School Degree Date Yale University B. S. (cum laude) May 1975 Carnegie-Mellon University Ph.D. Dec. 1981 4. Title of Thesis for Most Advanced Degree Area-Efficient VLSI Computation 5. Principal Fields of Interest Analysis of algorithms Caching Compilers and runtime systems Computer chess Computer-aided design Computer network architecture Digital hardware and computing machinery Distance education and interaction Fast artificial intelligence Leadership skills for engineering and science faculty Multicore computing Parallel algorithms, architectures, and languages Parallel and distributed computing Performance engineering Scalable computing systems Software performance engineering Supercomputing Theoretical computer science MIT School of Engineering Faculty Personnel Record — Charles E. Leiserson 2 6. Non-MIT Experience Position Date Founder, Chairman of the Board, and Chief Technology Officer, Cilk Arts, 2006 – 2009 Burlington, Massachusetts Director of System Architecture, Akamai Technologies, Cambridge, 1999 – 2001 Massachusetts Shaw Visiting Professor, National University of Singapore, Republic of 1995 – 1996 Singapore Network Architect for Connection Machine Model CM-5 Supercomputer, 1989 – 1990 Thinking Machines Programmer, Computervision Corporation, Bedford, Massachusetts 1975 -
Towards Non-Black-Box Lower Bounds in Cryptography
Towards Non-Black-Box Lower Bounds in Cryptography Rafael Pass?, Wei-Lung Dustin Tseng, and Muthuramakrishnan Venkitasubramaniam Cornell University, {rafael,wdtseng,vmuthu}@cs.cornell.edu Abstract. We consider average-case strengthenings of the traditional assumption that coNP is not contained in AM. Under these assumptions, we rule out generic and potentially non-black-box constructions of various cryptographic primitives (e.g., one-way permutations, collision-resistant hash-functions, constant-round statistically hiding commitments, and constant-round black-box zero-knowledge proofs for NP) from one-way functions, assuming the security reductions are black-box. 1 Introduction In the past four decades, many cryptographic tasks have been put under rigorous treatment in an eort to realize these tasks under minimal assumptions. In par- ticular, one-way functions are widely regarded as the most basic cryptographic primitive; their existence is implied by most other cryptographic tasks. Presently, one-way functions are known to imply schemes such as private-key encryp- tion [GM84,GGM86,HILL99], pseudo-random generators [HILL99], statistically- binding commitments [Nao91], statistically-hiding commitments [NOVY98,HR07] and zero-knowledge proofs [GMW91]. At the same time, some other tasks still have no known constructions based on one-way functions (e.g., key agreement schemes or collision-resistant hash functions). Following the seminal paper by Impagliazzo and Rudich [IR88], many works have addressed this phenomenon by demonstrating black-box separations, which rules out constructions of a cryptographic task using the underlying primitive as a black-box. For instance, Impagliazzo and Rudich rule out black-box con- structions of key-agreement protocols (and thus also trapdoor predicates) from one-way functions; Simon [Sim98] rules out black-box constructions of collision- resistant hash functions from one-way functions. -
Implementation of Elliptic Curve Cryptography in DNA Computing
International Journal of Scientific & Engineering Research Volume 8, Issue 6, June-2017 49 ISSN 2229-5518 Implementation of Elliptic Curve Cryptography in DNA computing 1Sourav Sinha, 2Shubhi Gupta 1Student: Department of Computer Science, 2Assistant Professor Amity University (dit school of Engineering) Greater Noida, India Abstract— DNA computing is the recent and powerful aspect of computer science Iin near future DNA computing is going to replace today’s silicon-based computing. In this paper, we are going to propose a method to implement Elliptic Curve Cryptography in DNA computing. Keywords—DNA computing; Elliptic Curve Cryptography 1. INTRODUCTION (HEADING 1) 2.2 DNA computer The hardware limitation of today’s computer is a barrier The DNA computer is different from Modern day’s in a development in technology. DNA computers, also classic computers. The DNA computer is nothing just a test known as molecular computer, have proven beneficial in tube containing a DNA and solvents for better mobility. such cases. Recent developments have seen massive The operations are done by chemical process and protein progress in technologies that enables a DNA computer to synthesis. DNA does not have any operational capacities, solve Hamiltonian Path Problem [1]. Cryptography and but it can be used as a hard drive to store and transfer data. network security is the most important section in development. Data Encryption Standard(DES) can also be 3. DNA-BASED ELLIPTIC CURVE ALGORITHM broken in a DNA computer, due to its ability to process The Elliptic curve cryptography makes use of an Elliptic parallel[2]. Curve to get the value of Its variable coefficients. -
Toward a Mathematical Semantics for Computer Languages
(! 1 J TOWARD A MATHEMATICAL SEMANTICS FOR COMPUTER LANGUAGES by Dana Scott and - Christopher Strachey Oxford University Computing Laboratory Programming Research Group-Library 8-11 Keble Road Oxford OX, 3QD Oxford (0865) 54141 Oxford University Computing Laboratory Programming Research Group tI. cr• "';' """, ":.\ ' OXFORD UNIVERSITY COMPUTING LABORATORY PROGRAMMING RESEARCH GROUP ~ 4S BANBURY ROAD \LJ OXFORD ~ .. 4 OCT 1971 ~In (UY'Y L TOWARD A ~ATHEMATICAL SEMANTICS FOR COMPUTER LANGUAGES by Dana Scott Princeton University and Christopher Strachey Oxford University Technical Monograph PRG-6 August 1971 Oxford University Computing Laboratory. Programming Research Group, 45 Banbury Road, Oxford. ~ 1971 Dana Scott and Christopher Strachey Department of Philosophy, Oxford University Computing Laboratory. 1879 lIall, Programming Research Group. Princeton University, 45 Banbury Road. Princeton. New Jersey 08540. Oxford OX2 6PE. This pape r is also to appear in Fl'(.'ceedinBs 0;- the .';y-,;;;o:illT:: on ComputeT's and AutoJ7'ata. lo-licroloo'ave Research Institute Symposia Series Volume 21. Polytechnic Institute of Brooklyn. and appears as a Technical Monograph by special aJ"rangement ...·ith the publishers. RefeJ"~nces in the Ii terature should be:- made to the _"!'OL·,-,',~;r:gs, as the texts are identical and the Symposia Sl?ries is gcaerally available in libraries. ABSTRACT Compilers for high-level languages aTe generally constructed to give the complete translation of the programs into machme language. As machines merely juggle bit patterns, the concepts of the original language may be lost or at least obscured during this passage. The purpose of a mathematical semantics is to give a correct and meaningful correspondence between programs and mathematical entities in a way that is entirely independent of an implementation. -
Why Mathematical Proof?
Why Mathematical Proof? Dana S. Scott, FBA, FNAS University Professor Emeritus Carnegie Mellon University Visiting Scholar University of California, Berkeley NOTICE! The author has plagiarized text and graphics from innumerable publications and sites, and he has failed to record attributions! But, as this lecture is intended as an entertainment and is not intended for publication, he regards such copying, therefore, as “fair use”. Keep this quiet, and do please forgive him. A Timeline for Geometry Some Greek Geometers Thales of Miletus (ca. 624 – 548 BC). Pythagoras of Samos (ca. 580 – 500 BC). Plato (428 – 347 BC). Archytas (428 – 347 BC). Theaetetus (ca. 417 – 369 BC). Eudoxus of Cnidus (ca. 408 – 347 BC). Aristotle (384 – 322 BC). Euclid (ca. 325 – ca. 265 BC). Archimedes of Syracuse (ca. 287 – ca. 212 BC). Apollonius of Perga (ca. 262 – ca. 190 BC). Claudius Ptolemaeus (Ptolemy)(ca. 90 AD – ca. 168 AD). Diophantus of Alexandria (ca. 200 – 298 AD). Pappus of Alexandria (ca. 290 – ca. 350 AD). Proclus Lycaeus (412 – 485 AD). There is no Royal Road to Geometry Euclid of Alexandria ca. 325 — ca. 265 BC Euclid taught at Alexandria in the time of Ptolemy I Soter, who reigned over Egypt from 323 to 285 BC. He authored the most successful textbook ever produced — and put his sources into obscurity! Moreover, he made us struggle with proofs ever since. Why Has Euclidean Geometry Been So Successful? • Our naive feeling for space is Euclidean. • Its methods have been very useful. • Euclid also shows us a mysterious connection between (visual) intuition and proof. The Pythagorean Theorem Euclid's Elements: Proposition 47 of Book 1 The Pythagorean Theorem Generalized If it holds for one Three triple, Similar it holds Figures for all.