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Register a new userMonotone Complexity of Spanning Tree Polynomial Re-visited
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Arkadev Chattopadhyay
Publication date
2021
fields
Informatics Engineering
and research's language is
English
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We prove two results that shed new light on the monotone complexity of the spanning tree polynomial, a classic polynomial in algebraic complexity and beyond. First, we show that the spanning tree polynomials having $n$ variables and defined over constant-degree expander graphs, have monotone arithmetic complexity $2^{Omega(n)}$. This yields the first strongly exponential lower bound on the monotone arithmetic circuit complexity for a polynomial in VP. Before this result, strongly exponential size monotone lower bounds were known only for explicit polynomials in VNP (Gashkov-Sergeev12, Raz-Yehudayoff11, Srinivasan20, Cavalar-Kumar-Rossman20, Hrubes-Yehudayoff21). Recently, Hrubes20 initiated a program to prove lower bounds against general arithmetic circuits by proving $epsilon$-sensitive lower bounds for monotone arithmetic circuits for a specific range of values for $epsilon in (0,1)$. We consider the spanning tree polynomial $ST_{n}$ defined over the complete graph on $n$ vertices and show that the polynomials $F_{n-1,n} - epsilon cdot ST_{n}$ and $F_{n-1,n} + epsilon cdot ST_{n}$ defined over $n^2$ variables, have monotone circuit complexity $2^{Omega(n)}$ if $epsilon geq 2^{-Omega(n)}$ and $F_{n-1,n} = prod_{i=2}^n (x_{i,1} +cdots + x_{i,n})$ is the complete set-multilinear polynomial. This provides the first $epsilon$-sensitive exponential lower bound for a family of polynomials inside VP. En-route, we consider a problem in 2-party, best partition communication complexity of deciding whether two sets of oriented edges distributed among Alice and Bob form a spanning tree or not. We prove that there exists a fixed distribution, under which the problem has low discrepancy with respect to every nearly-balanced partition. This result could be of interest beyond algebraic complexity.
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We introduce a new algebraic proof system, which has tight connections to (algebraic) circuit complexity. In particular, we show that any super-polynomial lower bound on any Boolean tautology in our proof system implies that the permanent does not have polynomial-size algebraic circuits (VNP is not equal to VP). As a corollary to the proof, we also show that super-polynomial lower bounds on the number of lines in Polynomial Calculus proofs (as opposed to the usual measure of number of monomials) imply the Permanent versus Determinant Conjecture. Note that, prior to our work, there was no proof system for which lower bounds on an arbitrary tautology implied any computational lower bound. Our proof system helps clarify the relationships between previous algebraic proof systems, and begins to shed light on why proof complexity lower bounds for various proof systems have been so much harder than lower bounds on the corresponding circuit classes. In doing so, we highlight the importance of polynomial identity testing (PIT) for understanding proof complexity. More specifically, we introduce certain propositional axioms satisfied by any Boolean circuit computing PIT. We use these PIT axioms to shed light on AC^0[p]-Frege lower bounds, which have been open for nearly 30 years, with no satisfactory explanation as to their apparent difficulty. We show that either: a) Proving super-polynomial lower bounds on AC^0[p]-Frege implies VNP does not have polynomial-size circuits of depth d - a notoriously open question for d at least 4 - thus explaining the difficulty of lower bounds on AC^0[p]-Frege, or b) AC^0[p]-Frege cannot efficiently prove the depth d PIT axioms, and hence we have a lower bound on AC^0[p]-Frege. Using the algebraic structure of our proof system, we propose a novel way to extend techniques from algebraic circuit complexity to prove lower bounds in proof complexity.
This is a survey on the exact complexity of computing the Tutte polynomial. It is the longer 2017 version of Chapter 25 of the CRC Handbook on the Tutte polynomial and related topics, edited by J. Ellis-Monaghan and I. Moffatt, which is due to appear in the first quarter of 2020. In the version to be published in the Handbook the Sections 5 and 6 are shortened and made into a single section.
We prove a new lower bound on the parity decision tree complexity $mathsf{D}_{oplus}(f)$ of a Boolean function $f$. Namely, granularity of the Boolean function $f$ is the smallest $k$ such that all Fourier coefficients of $f$ are integer multiples of $1/2^k$. We show that $mathsf{D}_{oplus}(f)geq k+1$. This lower bound is an improvement of lower bounds through the sparsity of $f$ and through the degree of $f$ over $mathbb{F}_2$. Using our lower bound we determine the exact parity decision tree complexity of several important Boolean functions including majority and recursive majority. For majority the complexity is $n - mathsf{B}(n)+1$, where $mathsf{B}(n)$ is the number of ones in the binary representation of $n$. For recursive majority the complexity is $frac{n+1}{2}$. Finally, we provide an example of a function for which our lower bound is not tight. Our results imply new lower bound of $n - mathsf{B}(n)$ on the multiplicative complexity of majority.
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 $F(x_1,ldots, x_k)= f(x_1opluscdotsoplus x_k)$, denoted by $mathrm{CC}^{(k)}(F)$. It is known that $mathrm{CC}^{(k)}(F)leq kcdotmathrm{D}_{oplus}(f)$ because the players can simulate the parity decision tree that computes $f$. In this note, we show that [mathrm{D}_{oplus}(f)leq Obig(mathrm{CC}^{(4)}(F)^5big).] Our main tool is a recent result from additive combinatorics due to Sanders. As $mathrm{CC}^{(k)}(F)$ is non-decreasing as $k$ grows, the parity decision tree complexity of $f$ and the communication complexity of the corresponding $k$-argument XOR functions are polynomially equivalent whenever $kgeq 4$. Remark: After the first version of this paper was finished, we discovered that Hatami and Lovett had already discovered the same result a few years ago, without writing it up.
The complexity class PPA consists of NP-search problems which are reducible to the parity principle in undirected graphs. It contains a wide variety of interesting problems from graph theory, combinatorics, algebra and number theory, but only a few of these are known to be complete in the class. Before this work, the known complete problems were all discretizations or combinatorial analogues of topological fixed point theorems. Here we prove the PPA-completeness of two problems of radically different style. They are PPA-Circuit CNSS and PPA-Circuit Chevalley, related respectively to the Combinatorial Nullstellensatz and to the Chevalley-Warning Theorem over the two elements field GF(2). The input of these problems contain PPA-circuits which are arithmetic circuits with special symmetric properties that assure that the polynomials computed by them have always an even number of zeros. In the proof of the result we relate the multilinear degree of the polynomials to the parity of the maximal parse subcircuits that compute monomials with maximal multilinear degree, and we show that the maximal parse subcircuits of a PPA-circuit can be paired in polynomial time.
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