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Settling a conjecture of Shi and Zhang, we determine the unbounded-error communication complexity of the symmetric XOR functions up to a poly-logarithmic factor. Our proof is by a simple reduction to an earlier result of Sherstov.

Computational Complexity · Computer Science 2017-04-18 Hamed Hatami , Yingjie Qian

Representations of Boolean functions by real polynomials play an important role in complexity theory. Typically, one is interested in the least degree of a polynomial p(x_1,...,x_n) that approximates or sign-represents a given Boolean…

Computational Complexity · Computer Science 2008-05-15 Alexander A. Sherstov

Boolean function $F(x,y)$ for $x,y \in \{0,1\}^n$ is an XOR function if $F(x,y)=f(x\oplus y)$ for some function $f$ on $n$ input bits, where $\oplus$ is a bit-wise XOR. XOR functions are relevant in communication complexity, partially for…

Computational Complexity · Computer Science 2024-06-04 Vladimir V. Podolskii , Dmitrii Sluch

We study the communication complexity of symmetric XOR functions, namely functions $f: \{0,1\}^n \times \{0,1\}^n \rightarrow \{0,1\}$ that can be formulated as $f(x,y)=D(|x\oplus y|)$ for some predicate $D: \{0,1,...,n\} \rightarrow…

Computational Complexity · Computer Science 2011-11-01 Ming Lam Leung , Yang Li , Shengyu Zhang

In this paper, we prove a strong XOR lemma for bounded-round two-player randomized communication. For a function $f:\mathcal{X}\times \mathcal{Y}\rightarrow\{0,1\}$, the $n$-fold XOR function $f^{\oplus n}:\mathcal{X}^n\times…

Computational Complexity · Computer Science 2022-08-25 Huacheng Yu

$\newcommand{\sp}{\mathsf{sparsity}}\newcommand{\s}{\mathsf{s}}\newcommand{\al}{\mathsf{alt}}$ The well-known Sensitivity Conjecture states that for any Boolean function $f$, block sensitivity of $f$ is at most polynomial in sensitivity of…

Computational Complexity · Computer Science 2019-02-12 Krishnamoorthy Dinesh , Jayalal Sarma

We establish an explicit link between depth-3 formulas and one-sided approximation by depth-2 formulas, which were previously studied independently. Specifically, we show that the minimum size of depth-3 formulas is (up to a factor of n)…

Computational Complexity · Computer Science 2017-05-11 Shuichi Hirahara

An XOR function is a function of the form g(x,y) = f(x + y), for some boolean function f on n bits. We study the quantum and classical communication complexity of XOR functions. In the case of exact protocols, we completely characterise…

Computational Complexity · Computer Science 2010-02-10 Ashley Montanaro , Tobias Osborne

We show that for any Boolean function f on {0,1}^n, the bounded-error quantum communication complexity of XOR functions $f\circ \oplus$ satisfies that $Q_\epsilon(f\circ \oplus) = O(2^d (\log\|\hat f\|_{1,\epsilon} + \log…

Computational Complexity · Computer Science 2013-07-26 Shengyu Zhang

This paper provides the first general technique for proving information lower bounds on two-party unbounded-rounds communication problems. We show that the discrepancy lower bound, which applies to randomized communication complexity, also…

Computational Complexity · Computer Science 2012-06-13 Mark Braverman , Omri Weinstein

We show nearly quadratic separations between two pairs of complexity measures: 1. We show that there is a Boolean function $f$ with $D(f)=\Omega((D^{sc}(f))^{2-o(1)})$ where $D(f)$ is the deterministic query complexity of $f$ and $D^{sc}$…

Computational Complexity · Computer Science 2015-12-03 Andris Ambainis , Martins Kokainis

In this note, we study the relation between the parity decision tree complexity of a boolean function $f$, denoted by $\mathrm{D}_{\oplus}(f)$, and the $k$-party number-in-hand multiparty communication complexity of the XOR functions…

Computational Complexity · Computer Science 2015-06-30 Penghui Yao

We prove a lower bound on the communication complexity of computing the $n$-fold xor of an arbitrary function $f$, in terms of the communication complexity and rank of $f$. We prove that $D(f^{\oplus n}) \geq n \cdot…

Computational Complexity · Computer Science 2024-07-03 Siddharth Iyer , Anup Rao

We study Boolean functions with sparse Fourier coefficients or small spectral norm, and show their applications to the Log-rank Conjecture for XOR functions f(x\oplus y) --- a fairly large class of functions including well studied ones such…

Computational Complexity · Computer Science 2013-04-10 Hing Yin Tsang , Chung Hoi Wong , Ning Xie , Shengyu Zhang

The level-$k$ $\ell_1$-Fourier weight of a Boolean function refers to the sum of absolute values of its level-$k$ Fourier coefficients. Fourier growth refers to the growth of these weights as $k$ grows. It has been extensively studied for…

Computational Complexity · Computer Science 2023-07-27 Uma Girish , Makrand Sinha , Avishay Tal , Kewen Wu

We study parity decision trees for Boolean functions. The motivation of our study is the log-rank conjecture for XOR functions and its connection to Fourier analysis and parity decision tree complexity. Let f be a Boolean function with…

Computational Complexity · Computer Science 2020-08-04 Nikhil S. Mande , Swagato Sanyal

In this paper we provide new bounds on classical and quantum distributional communication complexity in the two-party, one-way model of communication. In the classical model, our bound extends the well known upper bound of Kremer, Nisan and…

Information Theory · Computer Science 2008-02-29 Rahul Jain , Shengyu Zhang

We study the two-party communication complexity of functions with large outputs, and show that the communication complexity can greatly vary depending on what output model is considered. We study a variety of output models, ranging from the…

Computational Complexity · Computer Science 2023-04-04 Lila Fontes , Sophie Laplante , Mathieu Lauriere , Alexandre Nolin

In this paper, we focus on the quantum communication complexity of functions of the form $f \circ G = f(G(X_1, Y_1), \ldots, G(X_n, Y_n))$ where $f: \{0, 1\}^n \to \{0, 1\}$ is a symmetric function, $G: \{0, 1\}^j \times \{0, 1\}^k \to \{0,…

Quantum Physics · Physics 2023-01-10 Daiki Suruga

For any $\{0,1\}$-valued function $f$, its \emph{$n$-folded XOR} is the function $f^{\oplus n}$ where $f^{\oplus n}(X_1, \ldots, X_n) = f(X_1) \oplus \cdots \oplus f(X_n)$. Given a procedure for computing the function $f$, one can apply a…

Computational Complexity · Computer Science 2025-06-17 Pachara Sawettamalya , Huacheng Yu
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