Non-Deterministic Exponential Time Has Two-Prover Interactive Protocols
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COMPLEXITY THEORY Review Lecture 13: Space Hierarchy and Gaps
COMPLEXITY THEORY Review Lecture 13: Space Hierarchy and Gaps Markus Krotzsch¨ Knowledge-Based Systems TU Dresden, 26th Dec 2018 Markus Krötzsch, 26th Dec 2018 Complexity Theory slide 2 of 19 Review: Time Hierarchy Theorems Time Hierarchy Theorem 12.12 If f , g : N N are such that f is time- → constructible, and g log g o(f ), then · ∈ DTime (g) ( DTime (f ) ∗ ∗ Nondeterministic Time Hierarchy Theorem 12.14 If f , g : N N are such that f → is time-constructible, and g(n + 1) o(f (n)), then A Hierarchy for Space ∈ NTime (g) ( NTime (f ) ∗ ∗ In particular, we find that P , ExpTime and NP , NExpTime: , L NL P NP PSpace ExpTime NExpTime ExpSpace ⊆ ⊆ ⊆ ⊆ ⊆ ⊆ ⊆ , Markus Krötzsch, 26th Dec 2018 Complexity Theory slide 3 of 19 Markus Krötzsch, 26th Dec 2018 Complexity Theory slide 4 of 19 Space Hierarchy Proving the Space Hierarchy Theorem (1) Space Hierarchy Theorem 13.1: If f , g : N N are such that f is space- → constructible, and g o(f ), then For space, we can always assume a single working tape: ∈ Tape reduction leads to a constant-factor increase in space • DSpace(g) ( DSpace(f ) Constant factors can be eliminated by space compression • Proof: Again, we construct a diagonalisation machine . We define a multi-tape TM Therefore, DSpacek(f ) = DSpace1(f ). D D for inputs of the form , w (other cases do not matter), assuming that , w = n hM i |hM i| Compute f (n) in unary to mark the available space on the working tape Space turns out to be easier to separate – we get: • Space Hierarchy Theorem 13.1: If f , g : N N are such that f is space- Initialise a separate countdown tape with the largest binary number that can be → • constructible, and g o(f ), then written in f (n) space ∈ Simulate on , w , making sure that only previously marked tape cells are • M hM i DSpace(g) ( DSpace(f ) used Time-bound the simulation using the content of the countdown tape by • Challenge: TMs can run forever even within bounded space. -
CS601 DTIME and DSPACE Lecture 5 Time and Space Functions: T, S
CS601 DTIME and DSPACE Lecture 5 Time and Space functions: t, s : N → N+ Definition 5.1 A set A ⊆ U is in DTIME[t(n)] iff there exists a deterministic, multi-tape TM, M, and a constant c, such that, 1. A = L(M) ≡ w ∈ U M(w)=1 , and 2. ∀w ∈ U, M(w) halts within c · t(|w|) steps. Definition 5.2 A set A ⊆ U is in DSPACE[s(n)] iff there exists a deterministic, multi-tape TM, M, and a constant c, such that, 1. A = L(M), and 2. ∀w ∈ U, M(w) uses at most c · s(|w|) work-tape cells. (Input tape is “read-only” and not counted as space used.) Example: PALINDROMES ∈ DTIME[n], DSPACE[n]. In fact, PALINDROMES ∈ DSPACE[log n]. [Exercise] 1 CS601 F(DTIME) and F(DSPACE) Lecture 5 Definition 5.3 f : U → U is in F (DTIME[t(n)]) iff there exists a deterministic, multi-tape TM, M, and a constant c, such that, 1. f = M(·); 2. ∀w ∈ U, M(w) halts within c · t(|w|) steps; 3. |f(w)|≤|w|O(1), i.e., f is polynomially bounded. Definition 5.4 f : U → U is in F (DSPACE[s(n)]) iff there exists a deterministic, multi-tape TM, M, and a constant c, such that, 1. f = M(·); 2. ∀w ∈ U, M(w) uses at most c · s(|w|) work-tape cells; 3. |f(w)|≤|w|O(1), i.e., f is polynomially bounded. (Input tape is “read-only”; Output tape is “write-only”. -
Interactive Proof Systems and Alternating Time-Space Complexity
Theoretical Computer Science 113 (1993) 55-73 55 Elsevier Interactive proof systems and alternating time-space complexity Lance Fortnow” and Carsten Lund** Department of Computer Science, Unicersity of Chicago. 1100 E. 58th Street, Chicago, IL 40637, USA Abstract Fortnow, L. and C. Lund, Interactive proof systems and alternating time-space complexity, Theoretical Computer Science 113 (1993) 55-73. We show a rough equivalence between alternating time-space complexity and a public-coin interactive proof system with the verifier having a polynomial-related time-space complexity. Special cases include the following: . All of NC has interactive proofs, with a log-space polynomial-time public-coin verifier vastly improving the best previous lower bound of LOGCFL for this model (Fortnow and Sipser, 1988). All languages in P have interactive proofs with a polynomial-time public-coin verifier using o(log’ n) space. l All exponential-time languages have interactive proof systems with public-coin polynomial-space exponential-time verifiers. To achieve better bounds, we show how to reduce a k-tape alternating Turing machine to a l-tape alternating Turing machine with only a constant factor increase in time and space. 1. Introduction In 1981, Chandra et al. [4] introduced alternating Turing machines, an extension of nondeterministic computation where the Turing machine can make both existential and universal moves. In 1985, Goldwasser et al. [lo] and Babai [l] introduced interactive proof systems, an extension of nondeterministic computation consisting of two players, an infinitely powerful prover and a probabilistic polynomial-time verifier. The prover will try to convince the verifier of the validity of some statement. -
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/. -
Delegating Computation: Interactive Proofs for Muggles∗
Electronic Colloquium on Computational Complexity, Revision 1 of Report No. 108 (2017) Delegating Computation: Interactive Proofs for Muggles∗ Shafi Goldwasser Yael Tauman Kalai Guy N. Rothblum MIT and Weizmann Institute Microsoft Research Weizmann Institute [email protected] [email protected] [email protected] Abstract In this work we study interactive proofs for tractable languages. The (honest) prover should be efficient and run in polynomial time, or in other words a \muggle".1 The verifier should be super-efficient and run in nearly-linear time. These proof systems can be used for delegating computation: a server can run a computation for a client and interactively prove the correctness of the result. The client can verify the result's correctness in nearly-linear time (instead of running the entire computation itself). Previously, related questions were considered in the Holographic Proof setting by Babai, Fortnow, Levin and Szegedy, in the argument setting under computational assumptions by Kilian, and in the random oracle model by Micali. Our focus, however, is on the original inter- active proof model where no assumptions are made on the computational power or adaptiveness of dishonest provers. Our main technical theorem gives a public coin interactive proof for any language computable by a log-space uniform boolean circuit with depth d and input length n. The verifier runs in time n · poly(d; log(n)) and space O(log(n)), the communication complexity is poly(d; log(n)), and the prover runs in time poly(n). In particular, for languages computable by log-space uniform NC (circuits of polylog(n) depth), the prover is efficient, the verifier runs in time n · polylog(n) and space O(log(n)), and the communication complexity is polylog(n). -
Interactive Proofs
Interactive proofs April 12, 2014 [72] L´aszl´oBabai. Trading group theory for randomness. In Proc. 17th STOC, pages 421{429. ACM Press, 1985. doi:10.1145/22145.22192. [89] L´aszl´oBabai and Shlomo Moran. Arthur-Merlin games: A randomized proof system and a hierarchy of complexity classes. J. Comput. System Sci., 36(2):254{276, 1988. doi:10.1016/0022-0000(88)90028-1. [99] L´aszl´oBabai, Lance Fortnow, and Carsten Lund. Nondeterministic ex- ponential time has two-prover interactive protocols. In Proc. 31st FOCS, pages 16{25. IEEE Comp. Soc. Press, 1990. doi:10.1109/FSCS.1990.89520. See item 1991.108. [108] L´aszl´oBabai, Lance Fortnow, and Carsten Lund. Nondeterministic expo- nential time has two-prover interactive protocols. Comput. Complexity, 1 (1):3{40, 1991. doi:10.1007/BF01200056. Full version of 1990.99. [136] Sanjeev Arora, L´aszl´oBabai, Jacques Stern, and Z. (Elizabeth) Sweedyk. The hardness of approximate optima in lattices, codes, and systems of linear equations. In Proc. 34th FOCS, pages 724{733, Palo Alto CA, 1993. IEEE Comp. Soc. Press. doi:10.1109/SFCS.1993.366815. Conference version of item 1997:160. [160] Sanjeev Arora, L´aszl´oBabai, Jacques Stern, and Z. (Elizabeth) Sweedyk. The hardness of approximate optima in lattices, codes, and systems of linear equations. J. Comput. System Sci., 54(2):317{331, 1997. doi:10.1006/jcss.1997.1472. Full version of 1993.136. [111] L´aszl´oBabai, Lance Fortnow, Noam Nisan, and Avi Wigderson. BPP has subexponential time simulations unless EXPTIME has publishable proofs. In Proc. -
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. -
Simple Doubly-Efficient Interactive Proof Systems for Locally
Electronic Colloquium on Computational Complexity, Revision 3 of Report No. 18 (2017) Simple doubly-efficient interactive proof systems for locally-characterizable sets Oded Goldreich∗ Guy N. Rothblumy September 8, 2017 Abstract A proof system is called doubly-efficient if the prescribed prover strategy can be implemented in polynomial-time and the verifier’s strategy can be implemented in almost-linear-time. We present direct constructions of doubly-efficient interactive proof systems for problems in P that are believed to have relatively high complexity. Specifically, such constructions are presented for t-CLIQUE and t-SUM. In addition, we present a generic construction of such proof systems for a natural class that contains both problems and is in NC (and also in SC). The proof systems presented by us are significantly simpler than the proof systems presented by Goldwasser, Kalai and Rothblum (JACM, 2015), let alone those presented by Reingold, Roth- blum, and Rothblum (STOC, 2016), and can be implemented using a smaller number of rounds. Contents 1 Introduction 1 1.1 The current work . 1 1.2 Relation to prior work . 3 1.3 Organization and conventions . 4 2 Preliminaries: The sum-check protocol 5 3 The case of t-CLIQUE 5 4 The general result 7 4.1 A natural class: locally-characterizable sets . 7 4.2 Proof of Theorem 1 . 8 4.3 Generalization: round versus computation trade-off . 9 4.4 Extension to a wider class . 10 5 The case of t-SUM 13 References 15 Appendix: An MA proof system for locally-chracterizable sets 18 ∗Department of Computer Science, Weizmann Institute of Science, Rehovot, Israel. -
Input-Oblivious Proof Systems and a Uniform Complexity Perspective on P/Poly
Electronic Colloquium on Computational Complexity, Report No. 23 (2011) Input-Oblivious Proof Systems and a Uniform Complexity Perspective on P/poly Oded Goldreich∗ and Or Meir† Department of Computer Science Weizmann Institute of Science Rehovot, Israel. February 16, 2011 Abstract We initiate a study of input-oblivious proof systems, and present a few preliminary results regarding such systems. Our results offer a perspective on the intersection of the non-uniform complexity class P/poly with uniform complexity classes such as NP and IP. In particular, we provide a uniform complexity formulation of the conjecture N P 6⊂ P/poly and a uniform com- plexity characterization of the class IP∩P/poly. These (and similar) results offer a perspective on the attempt to prove circuit lower bounds for complexity classes such as NP, PSPACE, EXP, and NEXP. Keywords: NP, IP, PCP, ZK, P/poly, MA, BPP, RP, E, NE, EXP, NEXP. Contents 1 Introduction 1 1.1 The case of NP ....................................... 1 1.2 Connection to circuit lower bounds ............................ 2 1.3 Organization and a piece of notation ........................... 3 2 Input-Oblivious NP-Proof Systems (ONP) 3 3 Input-Oblivious Interactive Proof Systems (OIP) 5 4 Input-Oblivious Versions of PCP and ZK 6 4.1 Input-Oblivious PCP .................................... 6 4.2 Input-Oblivious ZK ..................................... 7 Bibliography 10 ∗Partially supported by the Israel Science Foundation (grant No. 1041/08). †Research supported by the Adams Fellowship Program of the Israel Academy of Sciences and Humanities. ISSN 1433-8092 1 Introduction Various types of proof systems play a central role in the theory of computation. -
Spring 2020 (Provide Proofs for All Answers) (120 Points Total)
Complexity Qual Spring 2020 (provide proofs for all answers) (120 Points Total) 1 Problem 1: Formal Languages (30 Points Total): For each of the following languages, state and prove whether: (i) the lan- guage is regular, (ii) the language is context-free but not regular, or (iii) the language is non-context-free. n n Problem 1a (10 Points): La = f0 1 jn ≥ 0g (that is, the set of all binary strings consisting of 0's and then 1's where the number of 0's and 1's are equal). ∗ Problem 1b (10 Points): Lb = fw 2 f0; 1g jw has an even number of 0's and at least two 1'sg (that is, the set of all binary strings with an even number, including zero, of 0's and at least two 1's). n 2n 3n Problem 1c (10 Points): Lc = f0 #0 #0 jn ≥ 0g (that is, the set of all strings of the form 0 repeated n times, followed by the # symbol, followed by 0 repeated 2n times, followed by the # symbol, followed by 0 repeated 3n times). Problem 2: NP-Hardness (30 Points Total): There are a set of n people who are the vertices of an undirected graph G. There's an undirected edge between two people if they are enemies. Problem 2a (15 Points): The people must be assigned to the seats around a single large circular table. There are exactly as many seats as people (both n). We would like to make sure that nobody ever sits next to one of their enemies. -
A Study of the NEXP Vs. P/Poly Problem and Its Variants by Barıs
A Study of the NEXP vs. P/poly Problem and Its Variants by Barı¸sAydınlıoglu˘ A dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy (Computer Sciences) at the UNIVERSITY OF WISCONSIN–MADISON 2017 Date of final oral examination: August 15, 2017 This dissertation is approved by the following members of the Final Oral Committee: Eric Bach, Professor, Computer Sciences Jin-Yi Cai, Professor, Computer Sciences Shuchi Chawla, Associate Professor, Computer Sciences Loris D’Antoni, Asssistant Professor, Computer Sciences Joseph S. Miller, Professor, Mathematics © Copyright by Barı¸sAydınlıoglu˘ 2017 All Rights Reserved i To Azadeh ii acknowledgments I am grateful to my advisor Eric Bach, for taking me on as his student, for being a constant source of inspiration and guidance, for his patience, time, and for our collaboration in [9]. I have a story to tell about that last one, the paper [9]. It was a late Monday night, 9:46 PM to be exact, when I e-mailed Eric this: Subject: question Eric, I am attaching two lemmas. They seem simple enough. Do they seem plausible to you? Do you see a proof/counterexample? Five minutes past midnight, Eric responded, Subject: one down, one to go. I think the first result is just linear algebra. and proceeded to give a proof from The Book. I was ecstatic, though only for fifteen minutes because then he sent a counterexample refuting the other lemma. But a third lemma, inspired by his counterexample, tied everything together. All within three hours. On a Monday midnight. I only wish that I had asked to work with him sooner. -
A Short History of Computational Complexity
The Computational Complexity Column by Lance FORTNOW NEC Laboratories America 4 Independence Way, Princeton, NJ 08540, USA [email protected] http://www.neci.nj.nec.com/homepages/fortnow/beatcs Every third year the Conference on Computational Complexity is held in Europe and this summer the University of Aarhus (Denmark) will host the meeting July 7-10. More details at the conference web page http://www.computationalcomplexity.org This month we present a historical view of computational complexity written by Steve Homer and myself. This is a preliminary version of a chapter to be included in an upcoming North-Holland Handbook of the History of Mathematical Logic edited by Dirk van Dalen, John Dawson and Aki Kanamori. A Short History of Computational Complexity Lance Fortnow1 Steve Homer2 NEC Research Institute Computer Science Department 4 Independence Way Boston University Princeton, NJ 08540 111 Cummington Street Boston, MA 02215 1 Introduction It all started with a machine. In 1936, Turing developed his theoretical com- putational model. He based his model on how he perceived mathematicians think. As digital computers were developed in the 40's and 50's, the Turing machine proved itself as the right theoretical model for computation. Quickly though we discovered that the basic Turing machine model fails to account for the amount of time or memory needed by a computer, a critical issue today but even more so in those early days of computing. The key idea to measure time and space as a function of the length of the input came in the early 1960's by Hartmanis and Stearns.