113 research outputs found

    More on a problem of Zarankiewicz

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    We show tight necessary and sufficient conditions on the sizes of small bipartite graphs whose union is a larger bipartite graph that has no large bipartite independent set. Our main result is a common generalization of two classical results in graph theory: the theorem of Kovari, Sos and Turan on the minimum number of edges in a bipartite graph that has no large independent set, and the theorem of Hansel (also Katona and Szemeredi and Krichevskii) on the sum of the sizes of bipartite graphs that can be used to construct a graph (non-necessarily bipartite) that has no large independent set. Our results unify the underlying combinatorial principles developed in the proof of tight lower bounds for depth-two superconcentrators

    Nullstellensatz Size-Degree Trade-offs from Reversible Pebbling

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    We establish an exactly tight relation between reversible pebblings of graphs and Nullstellensatz refutations of pebbling formulas, showing that a graph GG can be reversibly pebbled in time tt and space ss if and only if there is a Nullstellensatz refutation of the pebbling formula over GG in size t+1t+1 and degree ss (independently of the field in which the Nullstellensatz refutation is made). We use this correspondence to prove a number of strong size-degree trade-offs for Nullstellensatz, which to the best of our knowledge are the first such results for this proof system

    Lower Bounds for Matrix Factorization

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    We study the problem of constructing explicit families of matrices which cannot be expressed as a product of a few sparse matrices. In addition to being a natural mathematical question on its own, this problem appears in various incarnations in computer science; the most significant being in the context of lower bounds for algebraic circuits which compute linear transformations, matrix rigidity and data structure lower bounds. We first show, for every constant dd, a deterministic construction in subexponential time of a family {Mn}\{M_n\} of n×nn \times n matrices which cannot be expressed as a product Mn=A1AdM_n = A_1 \cdots A_d where the total sparsity of A1,,AdA_1,\ldots,A_d is less than n1+1/(2d)n^{1+1/(2d)}. In other words, any depth-dd linear circuit computing the linear transformation MnxM_n\cdot x has size at least n1+Ω(1/d)n^{1+\Omega(1/d)}. This improves upon the prior best lower bounds for this problem, which are barely super-linear, and were obtained by a long line of research based on the study of super-concentrators (albeit at the cost of a blow up in the time required to construct these matrices). We then outline an approach for proving improved lower bounds through a certain derandomization problem, and use this approach to prove asymptotically optimal quadratic lower bounds for natural special cases, which generalize many of the common matrix decompositions

    Approximating Cumulative Pebbling Cost Is Unique Games Hard

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    The cumulative pebbling complexity of a directed acyclic graph GG is defined as cc(G)=minPiPi\mathsf{cc}(G) = \min_P \sum_i |P_i|, where the minimum is taken over all legal (parallel) black pebblings of GG and Pi|P_i| denotes the number of pebbles on the graph during round ii. Intuitively, cc(G)\mathsf{cc}(G) captures the amortized Space-Time complexity of pebbling mm copies of GG in parallel. The cumulative pebbling complexity of a graph GG is of particular interest in the field of cryptography as cc(G)\mathsf{cc}(G) is tightly related to the amortized Area-Time complexity of the Data-Independent Memory-Hard Function (iMHF) fG,Hf_{G,H} [AS15] defined using a constant indegree directed acyclic graph (DAG) GG and a random oracle H()H(\cdot). A secure iMHF should have amortized Space-Time complexity as high as possible, e.g., to deter brute-force password attacker who wants to find xx such that fG,H(x)=hf_{G,H}(x) = h. Thus, to analyze the (in)security of a candidate iMHF fG,Hf_{G,H}, it is crucial to estimate the value cc(G)\mathsf{cc}(G) but currently, upper and lower bounds for leading iMHF candidates differ by several orders of magnitude. Blocki and Zhou recently showed that it is NP\mathsf{NP}-Hard to compute cc(G)\mathsf{cc}(G), but their techniques do not even rule out an efficient (1+ε)(1+\varepsilon)-approximation algorithm for any constant ε>0\varepsilon>0. We show that for any constant c>0c > 0, it is Unique Games hard to approximate cc(G)\mathsf{cc}(G) to within a factor of cc. (See the paper for the full abstract.)Comment: 28 pages, updated figures and corrected typo

    Understanding space in resolution: optimal lower bounds and exponential trade-offs

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    We continue the study of tradeoffs between space and length of resolution proofs and focus on two new results: begin{enumerate} item We show that length and space in resolution are uncorrelated. This is proved by exhibiting families of CNF formulas of size O(n)O(n) that have proofs of length O(n)O(n) but require space Omega(n/logn)Omega(n / log n). Our separation is the strongest possible since any proof of length O(n)O(n) can always be transformed into a proof in space O(n/logn)O(n / log n), and improves previous work reported in [Nordstr"{o}m 2006, Nordstr"{o}m and H{aa}stad 2008]. item We prove a number of trade-off results for space in the range from constant to O(n/logn)O(n / log n), most of them superpolynomial or even exponential. This is a dramatic improvement over previous results in [Ben-Sasson 2002, Hertel and Pitassi 2007, Nordstr"{o}m 2007]. end{enumerate} The key to our results is the following, somewhat surprising, theorem: Any CNF formula FF can be transformed by simple substitution transformation into a new formula F2˘7F\u27 such that if FF has the right properties, F2˘7F\u27 can be proven in resolution in essentially the same length as FF but the minimal space needed for F2˘7F\u27 is lower-bounded by the number of variables that have to be mentioned simultaneously in any proof for FF. Applying this theorem to so-called pebbling formulas defined in terms of pebble games over directed acyclic graphs and analyzing black-white pebbling on these graphs yields our results

    A New Connection Between Node and Edge Depth Robust Graphs

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    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

    RiffleScrambler - a memory-hard password storing function

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    We introduce RiffleScrambler: a new family of directed acyclic graphs and a corresponding data-independent memory hard function with password independent memory access. We prove its memory hardness in the random oracle model. RiffleScrambler is similar to Catena -- updates of hashes are determined by a graph (bit-reversal or double-butterfly graph in Catena). The advantage of the RiffleScrambler over Catena is that the underlying graphs are not predefined but are generated per salt, as in Balloon Hashing. Such an approach leads to higher immunity against practical parallel attacks. RiffleScrambler offers better efficiency than Balloon Hashing since the in-degree of the underlying graph is equal to 3 (and is much smaller than in Ballon Hashing). At the same time, because the underlying graph is an instance of a Superconcentrator, our construction achieves the same time-memory trade-offs.Comment: Accepted to ESORICS 201
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