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Book ChapterDOI

Limiting negations in bounded treewidth and upward planar circuits

Jing He, +2 more
- Vol. 6281, pp 417-428
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TLDR
In this paper, it was shown that 8k/2k negation gates are sufficient and sufficient for any Boolean function f to be computed by a monotone one-input-face upward planar circuit.
Abstract
The decrease of a Boolean function f: {0, 1}n → {0, 1}, denoted by d(f) is the maximum number of inverse indices in any increasing chain of inputs x1,..., xl ∈ {0,1}n, where i is an inverse index if f(xi) > f(xi+1). It follows from a theorem of Markov (JACM 1958) that the minimum number of negation gates in a circuit necessary and sufficient to compute any Boolean function f is ⌈log(d(f) + 1)⌉. A recent result due to Morizumi (ICALP 2009) proves that d(f) negations are necessary and sufficient when the computation is done by formulas. We explore the situation in between formulas (directed trees) and general circuits (DAGs), and related models. We obtain the following results: 1. We argue that for any Boolean function f, there is a circuit computing f, that uses ⌈log(d(f) + 1)⌉ negations and has treewidth at most ⌈log(d(f)+1)⌉ + 1. For 1 ≤ k ≤ ⌈log(d(f)+1)⌉, we prove that d(f). 8k/2k negations are sufficient to compute any Boolean function f by circuits of treewidth at most k. Moreover, if there is a circuit family of size s = s(n) and treewidth k = k(n) computing {fn}, then there exists a circuit family of size sċnO(1)ċ2O(min{k, log n}) and treewidth at most 2k which computes {fn} and contains O(max{nk/22k, log n}) negation gates. 2. We obtain tight bounds on the number of negation gates required to compute specific functions such as PARITYn, PARITYn and INVERTERn by one-input-face upward planar circuits. We extend these lower bounds to a larger class of functions (which also includes natural functions like ADD and SUBTRACT) and we show a direct sum theorem for this class with respect to the number of negations. 3. We demonstrate the limitations of the one-input-face constraint in the upward planar circuits by showing the explicit function which can be computed by a monotone upward planar circuit, but cannot be computed by any montone one-input-face upward planar circuit. 4. We prove that for every Boolean function f, there exists a multi-lective upward planar circuit which uses at most ⌈d(f)+1/2⌉ negation gates for computing f.

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Citations
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Journal ArticleDOI

Size-Treewidth Tradeoffs for Circuits Computing the Element Distinctness Function

TL;DR: This work shows that for each n, any circuit of treewidth t computing the element distinctness function δ n must have size at least Ω ( n 2 2 O ( t ) log n ) $\Omega (\frac {n^{2}}{2^{O(t)} \log n})$ .
Proceedings ArticleDOI

Size-Treewidth Tradeoffs for Circuits Computing the Element Distinctness Function

TL;DR: This work shows that for each n, any circuit of treewidth t computing the element distinctness function delta_n must have size at least Omega((n^2)/(2^{O(t)}*log(n))).
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A near-quadratic lower bound for the size of quantum circuits of constant treewidth

TL;DR: In this article, it was shown that any quantum circuit of treewidth t, built from r-qubit gates, requires at least [Equation] gates to compute the element distinctness function.
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A Near-Quadratic Lower Bound for the Size of Quantum Circuits of Constant Treewidth

TL;DR: It is shown that any quantum circuit of treewidth $t, built from $r$-qubit gates, requires at least $\Omega(\frac{n^{2}}{2^{O(r\cdot t)}\cdot \log^4 n})$ gates to compute the element distinctness function.
References
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Book

Introduction to Circuit Complexity : A Uniform Approach

TL;DR: This advanced handbook presents a broad and up-to-date view of the computational complexity theory of Boolean circuits that combines the algorithmic and the automata-theoretic approaches and includes an extensive discussion of the literature to facilitate future research.
Journal ArticleDOI

Simulating Quantum Computation by Contracting Tensor Networks

TL;DR: It is proved that a quantum circuit with T gates whose underlying graph has a treewidth d can be simulated deterministically in T^{O(1)}\exp[O(d)]$ time, which, in particular, is polynomial in $T$ if d=O(\log T)$.
Proceedings ArticleDOI

Monotone circuits for connectivity require super-logarithmic depth

TL;DR: It is proved that every monotone circuit which tests st-connectivity of an undirected graph on n nodes has depth and this implies a superpolynomial lower bound on the size of any monotones formula for st-Connectivity.
Journal ArticleDOI

Short monotone formulae for the majority function

TL;DR: It is shown that the monotone formula-size complexity of themonotone symmetric functions on n variables can be bounded above by a function of order O ( n 5.3 ).
Journal ArticleDOI

The gap between monotone and non-monotone circuit complexity is exponential

TL;DR: The proof is immediate by combining the Alon—Boppana version of another argument of Razborov with results of Grötschel—Lovász—Schrijver on the Lovász — capacity of a graph.
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