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Electronic Colloquium on Computational Complexity

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Reports tagged with Boolean circuits:
TR95-004 | 1st January 1995
Martin Dietzfelbinger, Miroslaw Kutylowski, Rüdiger Reischuk

Feasible Time-Optimal Algorithms for Boolean Functions on Exclusive-Write PRAMs

It was shown some years ago that the computation time for many important
Boolean functions of n arguments on concurrent-read exclusive-write
parallel random-access machines
(CREW PRAMs) of unlimited size is at least f(n) = 0.72 log n.
On the other hand, it ... more >>>

TR98-036 | 11th June 1998
Vince Grolmusz, Gábor Tardos

Lower Bounds for (MOD p -- MOD m) Circuits

Modular gates are known to be immune for the random
restriction techniques of Ajtai; Furst, Saxe, Sipser; and Yao and
Hastad. We demonstrate here a random clustering technique which
overcomes this difficulty and is capable to prove generalizations of
several known modular circuit lower bounds of Barrington, Straubing,
Therien; Krause ... more >>>

TR98-041 | 27th July 1998
Stasys Jukna

Combinatorics of Monotone Computations

We consider a general model of monotone circuits, which
we call d-local. In these circuits we allow as gates:
(i) arbitrary monotone Boolean functions whose minterms or
maxterms (or both) have length at most <i>d</i>, and
(ii) arbitrary real-valued non-decreasing functions on ... more >>>

TR02-067 | 5th October 2002
Marco Cadoli, Francesco Donini, Paolo Liberatore, Marco Schaerf

k-Approximating Circuits

In this paper we study the problem of approximating a boolean
function using the Hamming distance as the approximation measure.
Namely, given a boolean function f, its k-approximation is the
function f^k returning true on the same points in which f does,
plus all points whose Hamming distance from the ... more >>>

TR07-077 | 7th August 2007
Ilias Diakonikolas, Homin Lee, Kevin Matulef, Krzysztof Onak, Ronitt Rubinfeld, Rocco Servedio, Andrew Wan

Testing for Concise Representations

We describe a general method for testing whether a function on n input variables has a concise representation. The approach combines ideas from the junta test of Fischer et al. with ideas from learning theory, and yields property testers that make poly(s/epsilon) queries (independent of n) for Boolean function classes ... more >>>

TR09-008 | 15th January 2009
Stasys Jukna, Georg Schnitger

Min-Rank Conjecture for Log-Depth Circuits

A completion of an m-by-n matrix A with entries in {0,1,*} is obtained
by setting all *-entries to constants 0 or 1. A system of semi-linear
equations over GF(2) has the form Mx=f(x), where M is a completion of
A and f:{0,1}^n --> {0,1}^m is an operator, the i-th coordinate ... more >>>

TR09-084 | 24th September 2009
Arkadev Chattopadhyay, Avi Wigderson

Linear systems over composite moduli

We study solution sets to systems of generalized linear equations of the following form:
$\ell_i (x_1, x_2, \cdots , x_n)\, \in \,A_i \,\, (\text{mod } m)$,
where $\ell_1, \ldots ,\ell_t$ are linear forms in $n$ Boolean variables, each $A_i$ is an arbitrary subset of $\mathbb{Z}_m$, and $m$ is a composite ... more >>>

TR11-026 | 27th February 2011
Evgeny Demenkov, Alexander Kulikov

An Elementary Proof of $3n-o(n)$ Lower Bound on the Circuit Complexity of Affine Dispersers

A Boolean function $f \colon \mathbb{F}^n_2 \rightarrow \mathbb{F}_2$ is called an affine disperser for sources of dimension $d$, if $f$ is not constant on any affine subspace of $\mathbb{F}^n_2$ of dimension at least $d$. Recently Ben-Sasson and Kopparty gave an explicit construction of an affine disperser for $d=o(n)$. The main ... more >>>

TR13-093 | 21st June 2013
Anna Gal, Jing-Tang Jang

A Generalization of Spira's Theorem and Circuits with Small Segregators or Separators

Spira showed that any Boolean formula of size $s$ can be simulated in depth $O(\log s)$. We generalize Spira's theorem and show that any Boolean circuit of size $s$ with segregators of size $f(s)$ can be simulated in depth $O(f(s)\log s)$. If the segregator size is at least $s^{\varepsilon}$ for ... more >>>

TR14-058 | 20th April 2014
Ilya Volkovich

On Learning, Lower Bounds and (un)Keeping Promises

We extend the line of research initiated by Fortnow and Klivans \cite{FortnowKlivans09} that studies the relationship between efficient learning algorithms and circuit lower bounds. In \cite{FortnowKlivans09}, it was shown that if a Boolean circuit class $\mathcal{C}$ has an efficient \emph{deterministic} exact learning algorithm, (i.e. an algorithm that uses membership and ... more >>>

TR14-173 | 13th December 2014
Igor Carboni Oliveira, Rahul Santhanam

Majority is incompressible by AC$^0[p]$ circuits

Revisions: 1

We consider $\cal C$-compression games, a hybrid model between computational and communication complexity. A $\cal C$-compression game for a function $f \colon \{0,1\}^n \to \{0,1\}$ is a two-party communication game, where the first party Alice knows the entire input $x$ but is restricted to use strategies computed by $\cal C$-circuits, ... more >>>

TR15-065 | 18th April 2015
Benjamin Rossman, Rocco Servedio, Li-Yang Tan

An average-case depth hierarchy theorem for Boolean circuits

We prove an average-case depth hierarchy theorem for Boolean circuits over the standard basis of AND, OR, and NOT gates. Our hierarchy theorem says that for every $d \geq 2$, there is an explicit $n$-variable Boolean function $f$, computed by a linear-size depth-$d$ formula, which is such that any depth-$(d-1)$ ... more >>>

TR15-123 | 31st July 2015
Xi Chen, Igor Carboni Oliveira, Rocco Servedio

Addition is exponentially harder than counting for shallow monotone circuits

Let $U_{k,N}$ denote the Boolean function which takes as input $k$ strings of $N$ bits each, representing $k$ numbers $a^{(1)},\dots,a^{(k)}$ in $\{0,1,\dots,2^{N}-1\}$, and outputs 1 if and only if $a^{(1)} + \cdots + a^{(k)} \geq 2^N.$ Let THR$_{t,n}$ denote a monotone unweighted threshold gate, i.e., the Boolean function which takes ... more >>>

TR15-166 | 17th October 2015
Magnus Gausdal Find, Alexander Golovnev, Edward Hirsch, Alexander Kulikov

A better-than-$3n$ lower bound for the circuit complexity of an explicit function

Revisions: 1

We consider Boolean circuits over the full binary basis. We prove a $(3+\frac{1}{86})n-o(n)$ lower bound on the size of such a circuit for an explicitly defined predicate, namely an affine disperser for sublinear dimension. This improves the $3n-o(n)$ bound of Norbert Blum (1984). The proof is based on the gate ... more >>>

TR15-170 | 26th October 2015
Alexander Golovnev, Alexander Kulikov

Weighted gate elimination: Boolean dispersers for quadratic varieties imply improved circuit lower bounds

In this paper we motivate the study of Boolean dispersers for quadratic varieties by showing that an explicit construction of such objects gives improved circuit lower bounds. An $(n,k,s)$-quadratic disperser is a function on $n$ variables that is not constant on any subset of $\mathbb{F}_2^n$ of size at least $s$ ... more >>>

TR18-030 | 9th February 2018
Shuichi Hirahara, Igor Carboni Oliveira, Rahul Santhanam

NP-hardness of Minimum Circuit Size Problem for OR-AND-MOD Circuits

The Minimum Circuit Size Problem (MCSP) asks for the size of the smallest boolean circuit that computes a given truth table. It is a prominent problem in NP that is believed to be hard, but for which no proof of NP-hardness has been found. A significant number of works have ... more >>>

TR18-153 | 22nd August 2018
Krishnamoorthy Dinesh, Samir Otiv, Jayalal Sarma

New Bounds for Energy Complexity of Boolean Functions

For a Boolean function $f:\{0,1\}^n \to \{0,1\}$ computed by a circuit $C$ over a finite basis $\cal{B}$, the energy complexity of $C$ (denoted by $\mathbf{EC}_{{\cal B}}(C)$) is the maximum over all inputs $\{0,1\}^n$ the numbers of gates of the circuit $C$ (excluding the inputs) that output a one. Energy Complexity ... more >>>

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