Lower Bounds on the Bounded Coefficient Complexity of Bilinear Maps

We prove lower bounds of order $n\log n$ for both the problem to multiply polynomials of degree $n$, and to divide polynomials with remainder, in the model of bounded coefficient arithmetic circuits over the complex numbers. These lower bounds are optimal up to order of magnitude. The proof uses a recent idea of R. Raz [Proc. 34th STOC 2002] proposed for matrix multiplication. It reduces the linear problem to multiply a random circulant matrix with a vector to the bilinear problem of cyclic convolution. We treat the arising linear problem by extending J. Morgenstern's bound [J. ACM 20, pp. 305-306, 1973] in a unitarily invariant way. This establishes a new lower bound on the bounded coefficient complexity of linear forms in terms of the singular values of the corresponding matrix. In addition, we extend these lower bounds for linear and bilinear maps to a model of circuits that allows a restricted number of unbounded scalar multiplications.Comment: 19 page

Reductions for monotone Boolean circuits

AbstractThe large class, say NLOG, of Boolean functions, including 0-1 Sort and 0-1 Merge, have an upper bound of O(nlogn) for their monotone circuit size, i.e., they have circuits with O(nlogn) AND/OR gates of fan-in two. Suppose that we can use, besides such normal AND/OR gates, any number of more powerful “F-gates” which realize a monotone Boolean function F with r(≥2) inputs and r′(≥1) outputs. Note that the cost of each AND/OR gate is one and we assume that the cost of each F-gate is r. Now we define: A Boolean function f in NLOG is said to be F-Easy if f can be constructed by a circuit with AND/OR/F gates whose total cost is o(nlogn). In this paper we show that 0-1 Merge is not F-Easy for an arbitrary monotone function F such that r′≤r/logr

On 3-Pushdown Graphs With Large Separators

For an integer s let ZS(n), the s-iterated logarithm function, be defined inductively: [O(n) = n, [8+1(n) = log2(l8(n)) for s 2:: o. We show that for every fixed s and all n large enough, there is an n-vertex 3-pushdown graph whose smallest separator contains at least n(n/[8(n)) vertices

On Nontrivial Separators for k-Page Graphs and Simulations by Nondeterministic One-Tape Turing Machines

We show that the following statements are equivalent: 1. Statement 1. 3-pushdown graphs have sublinear separators. 2. Statement 1∗. k-page graphs have sublinear separators. 3. Statement 2. A one-tape nondeterministic Turing machine can simulate a two-tape machine in subquadratic time. None of the statements is known to be true or false at present. However, our proof of equivalence is quantitative-it relates exactly the separator size of the two kinds of graphs to the running time of the simulation in Statement 2. Using this equivalence we derive several graph-theoretic corollaries. There are known examples where upper bounds on graph properties imply upper bounds on computation time or space. There are other examples where lower bounds on graph properties are used to derive lower bounds on computation time in restricted settings. However, our results may constitute the first example where a graph problem is shown to be equivalent to a problem in computational complexity. In a companion paper we construct graphs and prove a lower bound or their separators. Using the equivalence we prove an almost linear lower bound for the size of separators for 3-pushdown graphs and an almost quadratic lower bound for simulating two-tape nondeterministic Turing machines by one-tape machines. Specifically, for an integers s let ls(n), the s-iterated logarithm function, be defined inductively: l°(n)=n, ls+1(n)=log2(ls(n)) for s⩾0. Then: 1. For every fixed s and all n, there is an n-vertex 3-pushdown graph whose smallest separator contains at least ω(n/ls(n)) vertices.2. There is a language L recognizable in real time by a two-tape nondeterministic Turing machine, but every on-line one-tape nondeterministic Turing machine that recognizes L requires ω(n2/ls(n)) time for any positive integer

Spectral Expanding Expanders

Dinitz, Schapira, and Valadarsky [Dinitz et al., 2017] introduced the intriguing notion of expanding expanders - a family of expander graphs with the property that every two consecutive graphs in the family differ only on a small number of edges. Such a family allows one to add and remove vertices with only few edge updates, making them useful in dynamic settings such as for datacenter network topologies and for the design of distributed algorithms for self-healing expanders. [Dinitz et al., 2017] constructed explicit expanding-expanders based on the Bilu-Linial construction of spectral expanders [Bilu and Linial, 2006]. The construction of expanding expanders, however, ends up being of edge expanders, thus, an open problem raised by [Dinitz et al., 2017] is to construct spectral expanding expanders (SEE). In this work, we resolve this question by constructing SEE with spectral expansion which, like [Bilu and Linial, 2006], is optimal up to a poly-logarithmic factor, and the number of edge updates is optimal up to a constant. We further give a simple proof for the existence of SEE that are close to Ramanujan up to a small additive term. As in [Dinitz et al., 2017], our construction is based on interpolating between a graph and its lift. However, to establish spectral expansion, we carefully weigh the interpolated graphs, dubbed partial lifts, in a way that enables us to conduct a delicate analysis of their spectrum. In particular, at a crucial point in the analysis, we consider the eigenvectors structure of the partial lifts

Small space analogues of Valiant\u27s classes and the limitations of skew formula

In the uniform circuit model of computation, the width of a boolean circuit exactly characterises the ``space\u27\u27 complexity of the computed function. Looking for a similar relationship in Valiant\u27s algebraic model of computation, we propose width of an arithmetic circuit as a possible measure of space. We introduce the class VL as an algebraic variant of deterministic log-space L. In the uniform setting, we show that our definition coincides with that of VPSPACE at polynomial width. Further, to define algebraic variants of non-deterministic space-bounded classes, we introduce the notion of ``read-once\u27\u27 certificates for arithmetic circuits. We show that polynomial-size algebraic branching programs can be expressed as a read-once exponential sum over polynomials in VL, ie $mbox{VBP}inSigma^R cdotmbox{VL}$. We also show that $Sigma^R cdot mbox{VBP} =mbox{VBP}$, ie VBPs are stable under read-once exponential sums. Further, we show that read-once exponential sums over a restricted class of constant-width arithmetic circuits are within VQP, and this is the largest known such subclass of poly-log-width circuits with this property. We also study the power of skew formulas and show that exponential sums of a skew formula cannot represent the determinant polynomial

A New Connection Between Node and Edge Depth Robust Graphs

Given a directed acyclic graph (DAG) G = (V,E), we say that G is (e,d)-depth-robust (resp. (e,d)-edge-depth-robust) if for any set S ? V (resp. S ? E) of at most |S| ? e nodes (resp. edges) the graph G-S contains a directed path of length d. While edge-depth-robust graphs are potentially easier to construct many applications in cryptography require node depth-robust graphs with small indegree. We create a graph reduction that transforms an (e, d)-edge-depth-robust graph with m edges into a (e/2,d)-depth-robust graph with O(m) nodes and constant indegree. One immediate consequence of this result is the first construction of a provably ((n log log n)/log n, n/{(log n)^{1 + log log n}})-depth-robust graph with constant indegree, where previous constructions for e = (n log log n)/log n had d = O(n^{1-?}). Our reduction crucially relies on ST-Robust graphs, a new graph property we introduce which may be of independent interest. We say that a directed, acyclic graph with n inputs and n outputs is (k?, k?)-ST-Robust if we can remove any k? nodes and there exists a subgraph containing at least k? inputs and k? outputs such that each of the k? inputs is connected to all of the k? outputs. If the graph if (k?,n-k?)-ST-Robust for all k? ? n we say that the graph is maximally ST-robust. We show how to construct maximally ST-robust graphs with constant indegree and O(n) nodes. Given a family ? of ST-robust graphs and an arbitrary (e, d)-edge-depth-robust graph G we construct a new constant-indegree graph Reduce(G, ?) by replacing each node in G with an ST-robust graph from ?. We also show that ST-robust graphs can be used to construct (tight) proofs-of-space and (asymptotically) improved wide-block labeling functions

Augmenting the algebraic connectivity of graphs

For any undirected graph G=(V,E) and a set EW of candidate edges with E∩EW=∅, the (k,γ)-spectral augmentability problem is to find a set F of k edges from EW with appropriate weighting, such that the algebraic connectivity of the resulting graph H=(V,E∪F) is least γ. Because of a tight connection between the algebraic connectivity and many other graph parameters, including the graph's conductance and the mixing time of random walks in a graph, maximising the resulting graph's algebraic connectivity by adding a small number of edges has been studied over the past 15 years. In this work we present an approximate and efficient algorithm for the (k,γ)-spectral augmentability problem, and our algorithm runs in almost-linear time under a wide regime of parameters. Our main algorithm is based on the following two novel techniques developed in the paper, which might have applications beyond the (k,γ)-spectral augmentability problem. (1) We present a fast algorithm for solving a feasibility version of an SDP for the algebraic connectivity maximisation problem from [GB06]. Our algorithm is based on the classic primal-dual framework for solving SDP, which in turn uses the multiplicative weight update algorithm. We present a novel approach of unifying SDP constraints of different matrix and vector variables and give a good separation oracle accordingly. (2) We present an efficient algorithm for the subgraph sparsification problem, and for a wide range of parameters our algorithm runs in almost-linear time, in contrast to the previously best known algorithm running in at least Ω(n2mk) time [KMST10]. Our analysis shows how the randomised BSS framework can be generalised in the setting of subgraph sparsification, and how the potential functions can be applied to approximately keep track of different subspaces