152 research outputs found

    On monotone circuits with local oracles and clique lower bounds

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    We investigate monotone circuits with local oracles [K., 2016], i.e., circuits containing additional inputs yi=yi(x⃗)y_i = y_i(\vec{x}) that can perform unstructured computations on the input string x⃗\vec{x}. Let Ό∈[0,1]\mu \in [0,1] be the locality of the circuit, a parameter that bounds the combined strength of the oracle functions yi(x⃗)y_i(\vec{x}), and Un,k,Vn,k⊆{0,1}mU_{n,k}, V_{n,k} \subseteq \{0,1\}^m be the set of kk-cliques and the set of complete (k−1)(k-1)-partite graphs, respectively (similarly to [Razborov, 1985]). Our results can be informally stated as follows. 1. For an appropriate extension of depth-22 monotone circuits with local oracles, we show that the size of the smallest circuits separating Un,3U_{n,3} (triangles) and Vn,3V_{n,3} (complete bipartite graphs) undergoes two phase transitions according to ÎŒ\mu. 2. For 5≀k(n)≀n1/45 \leq k(n) \leq n^{1/4}, arbitrary depth, and Ό≀1/50\mu \leq 1/50, we prove that the monotone circuit size complexity of separating the sets Un,kU_{n,k} and Vn,kV_{n,k} is nΘ(k)n^{\Theta(\sqrt{k})}, under a certain restrictive assumption on the local oracle gates. The second result, which concerns monotone circuits with restricted oracles, extends and provides a matching upper bound for the exponential lower bounds on the monotone circuit size complexity of kk-clique obtained by Alon and Boppana (1987).Comment: Updated acknowledgements and funding informatio

    Complexity Theory, Game Theory, and Economics: The Barbados Lectures

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    This document collects the lecture notes from my mini-course "Complexity Theory, Game Theory, and Economics," taught at the Bellairs Research Institute of McGill University, Holetown, Barbados, February 19--23, 2017, as the 29th McGill Invitational Workshop on Computational Complexity. The goal of this mini-course is twofold: (i) to explain how complexity theory has helped illuminate several barriers in economics and game theory; and (ii) to illustrate how game-theoretic questions have led to new and interesting complexity theory, including recent several breakthroughs. It consists of two five-lecture sequences: the Solar Lectures, focusing on the communication and computational complexity of computing equilibria; and the Lunar Lectures, focusing on applications of complexity theory in game theory and economics. No background in game theory is assumed.Comment: Revised v2 from December 2019 corrects some errors in and adds some recent citations to v1 Revised v3 corrects a few typos in v

    Proof Complexity of Natural Formulas via Communication Arguments

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    Non-Malleable Codes for Small-Depth Circuits

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    We construct efficient, unconditional non-malleable codes that are secure against tampering functions computed by small-depth circuits. For constant-depth circuits of polynomial size (i.e. AC0\mathsf{AC^0} tampering functions), our codes have codeword length n=k1+o(1)n = k^{1+o(1)} for a kk-bit message. This is an exponential improvement of the previous best construction due to Chattopadhyay and Li (STOC 2017), which had codeword length 2O(k)2^{O(\sqrt{k})}. Our construction remains efficient for circuit depths as large as Θ(log⁥(n)/log⁥log⁥(n))\Theta(\log(n)/\log\log(n)) (indeed, our codeword length remains n≀k1+Ï”)n\leq k^{1+\epsilon}), and extending our result beyond this would require separating P\mathsf{P} from NC1\mathsf{NC^1}. We obtain our codes via a new efficient non-malleable reduction from small-depth tampering to split-state tampering. A novel aspect of our work is the incorporation of techniques from unconditional derandomization into the framework of non-malleable reductions. In particular, a key ingredient in our analysis is a recent pseudorandom switching lemma of Trevisan and Xue (CCC 2013), a derandomization of the influential switching lemma from circuit complexity; the randomness-efficiency of this switching lemma translates into the rate-efficiency of our codes via our non-malleable reduction.Comment: 26 pages, 4 figure

    Complexity Theory

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    Computational Complexity Theory is the mathematical study of the intrinsic power and limitations of computational resources like time, space, or randomness. The current workshop focused on recent developments in various sub-areas including arithmetic complexity, Boolean complexity, communication complexity, cryptography, probabilistic proof systems, pseudorandomness, and quantum computation. Many of the developements are related to diverse mathematical ïŹelds such as algebraic geometry, combinatorial number theory, probability theory, quantum mechanics, representation theory, and the theory of error-correcting codes

    LIPIcs, Volume 251, ITCS 2023, Complete Volume

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    LIPIcs, Volume 251, ITCS 2023, Complete Volum

    TFNP Characterizations of Proof Systems and Monotone Circuits

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    Mathematical Logic: Proof theory, Constructive Mathematics

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    The workshop “Mathematical Logic: Proof Theory, Constructive Mathematics” was centered around proof-theoretic aspects of current mathematics, constructive mathematics and logical aspects of computational complexit

    35th Symposium on Theoretical Aspects of Computer Science: STACS 2018, February 28-March 3, 2018, Caen, France

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