arXiv subjects

Anand Srivastav

Publications and source records attributed to Anand Srivastav.

15 recordsLinked to original sources

arXiv2026

Faster Algorithms for Deciding the Unbiased Maker-Breaker Triangle Game on General Graphs

In this paper, we present new polynomial-time algorithms for determining the winner of the unbiased triangle game played on the edge set of general graphs. To that end, we propose to view the game through the edge-triangle incidence graph instead of the standard hypergraph model. We identify a necessary and sufficient winning condition for Maker in terms of the edge-triangle incidence graph and show that winning strategies achieving this condition as fast as possible play monotonically in the sense that they only consider monotonically decreasing connected subgraphs of the edge-triangle incidence graph. We give three different algorithms for different classes of graphs. For general graphs $G$, the outcome of the unbiased triangle game can be decided in time $\mathcal{O}(n+m^{3.5})=\mathcal{O}(n^7)$. This significantly improves on the $\mathcal{O}(n^{16})$ algorithm implied by the work of Galliot, Gravier and Sivignon (arXiv 2022). For graphs $G$ which contain $K_4$, the complete graph on four vertices, as a subgraph and whose edge-triangle incidence graph is connected, the winner can be decided in time $\mathcal{O}(n+\min\{n^{ω+1},m^2\})=\mathcal{O}(n^{ω+1})$, where $ω<2.372$ is the exponent of matrix multiplication (Alman et. al., SODA 2025). For graphs $G$ whose edge-triangle incidence graph is a cactus graph, i.e. all its cycles are edge-disjoint, the winner can be decided in time $\mathcal{O}(n+m^{1.5})=\mathcal{O}(n^3)$. Such $G$ are $K_4$-free. The algorithms for the special cases are based on novel structural characterizations of Maker's win for each graph class. We also give a linear time reduction from triangle detection to deciding the unbiased triangle game.

cs.CC↗

arXiv2026

Constructive Winning Breaker Strategies in the Maker-Breaker $C_k$-Game

Maker-Breaker subgraph games are among the most famous combinatorial games. For $n,q\in\mathbb{N}$ and a fixed subgraph $C$ of the complete graph $K_n$, the two players, called Maker and Breaker, alternately claim edges of $K_n$. Maker claims one unclaimed edge per round and Breaker may claim up to $q$ edges per round. If Maker is able to claim all edges of a copy of $C$, he wins the game. Otherwise Breaker wins. Bednarska and Łuczak (2000) determined in a landmark work the asymptotics of the treshold bias as $Θ(n^{1/m(C)})$ where $m(C)$ is the 2-density of $C$, analysing random strategies. Since then it has been a major open problem to determine the treshhold bias, if it exists, with corresponding strategies, leading to sharp constants in the $Θ$-notion. A famous case is the triangle game ($C=C_3$), studied by Chvatal and Erd"os (1978), who showed Maker wins if $q\le \sqrt{2n}$ and Breaker wins if $q\ge2\sqrt{n}$. Glazik and Srivastav (2022) improved this via a potential method, showing Breaker wins already for $q\ge\sqrt{8/3}\sqrt{n}$. Spencer (2019) conjectured generalizability to arbitrary subgraphs $C$. We confirm this conjecture, presenting a general winning strategy for Breaker if the potential function fullfils conditions depending on $C$. With this result we give the first constructive (polynomial-time) strategies for Breaker in the $k$-cycle Maker-Breaker game for arbitrary, but fixed $k \geq 4$: Breaker wins if $q>\sqrt[k-1]{(k-1)\big(\frac{2(k-1)}{k}\big)^{k-2}n^{k-2}}$. By Bednarska and Łuczak (2000) our bound is asymptotically optimal. However, our constants are better than those arising from their random strategies. More recently, Sowa and Srivastav (2025) gave the first constructive Maker strategy for $C_4$. Our work may motivate study of Maker strategies for $C_k, k \ge 5$, narrowing the gap towards the Breaker bounds presented.

math.CO↗

arXiv2024

Chromatic number of randomly augmented graphs

An extension of the Erdős-Renyi random graph model $G_{n,p}$ is the model of perturbed graphs introduced by Bohman, Frieze and Martin (Bohman, Frieze, Martin 2003). This is a special case of the model of randomly augmented graphs studied in this paper. An augmented graph denoted by $pert_{H,p}$ is the union of a deterministic host graph and a random graph $G_{n,p}$. Among the first problems in perturbed graphs has been the question how many random edges are needed to ensure Hamiltonicity of the graph. This question was answered in the paper by Bohman, Frieze and Martin. The host graph is often chosen to be a dense graph. In recent years several papers on combinatorial problems in perturbed graphs were published, e.g. on the emergence of powers of Hamiltonian cycles (Dudek, Reiher, Ruciński, Schacht 2020), some positional games played on perturbed graphs (Clemens, Hamann, Mogge, Parczyk, 2020) and the behavior of multiple invariants e.g. fixed clique size (Bohman, Frieze, Krivelevich, Martin, 2004). In this paper we study the chromatic number of randomly augmented graphs. We concentrate on a host graph $H$ with chromatic number $o(n)$, augmented by a $G_{n,p}$ with $n^{-\frac{1}{3} + δ}\leq p(n) \leq 1-δ$ for some $δ\in (0,1)$. Our main result is an upper bound for the chromatic number: we show that asymptotically almost surely $χ(pert_{H,p}) \leq (1+o(1)) \cdot \frac{n \log(b)}{2 (\log(n) - \log(χ(H))}$ where $b = (1-p)^{-1}$. This result collapses to the famous theorem of Bollobás (1988), when $H$ is the empty host graph, thus our result can be regarded as a generalization of the latter. Our proof is not constructive. Further, we give a constructive coloring algorithm, when the chromatic number of the host graph is at most $\frac{n}{\log(n)^α},$ $α>\frac{1}{2}.$

math.CO↗

arXiv2024

A Constructive Winning Maker Strategy in the Maker-Breaker $C_4$-Game

Maker-Breaker subgraph games are among the most famous combinatorial games. For given $n,q \in \mathbb{N}$ and a subgraph $C$ of the complete graph $K_n$, the two players, called Maker and Breaker, alternately claim edges of $K_n$. In each round of the game Maker claims one edge and Breaker is allowed to claim up to $q$ edges. If Maker is able to claim all edges of a copy of $C$, he wins the game. Otherwise Breaker wins. In this work we introduce the first constructive strategy for Maker for the $C_4$-Maker-Breaker game and show that he can win the game if $q < 0.16 n^{2/3}$. According to the theorem of Bednarska and Luczak (2000) $n^{2/3}$ is asymptotically optimal for this game, but the constant given there for a random Maker strategy is magnitudes apart from our constant 0.16.

math.CO↗

arXiv2024

Asymptotically Optimal Threshold Bias for the $(a : b)$ Maker-Breaker Minimum Degree, Connectivity and Hamiltonicity Games

We study the $(a:b)$ Maker-Breaker subgraph game played on the edges of the complete graph $K_n$ on $n$ vertices, $n,a,b \in \mathbb{N}$ where the goal of Maker is to build a copy of a specific fixed subgraph $H$. In our work this is a spanning graph with minimum degree $k=k(n)$, a connected spanning subgraph or a Hamiltonian subgraph. In the $(a:b)$ game in each round Maker chooses $a$ unclaimed edges of $K_n$ and Breaker chooses $b$ unclaimed edges. Maker wins, if he succeeds to build a copy of the subgraph under consideration, otherwise Breaker wins. For the $k$-minimum-degree, we present a winning strategy for Maker leading to a bound that generalizes a bound of Gebauer and Szab{ó} for the $(1:b)$ case. Moreover, we give an explicit strategy for Breaker for $b >(1+o(1)) \frac{an}{a+\ln(n)}$ in case of $a=o\left(\sqrt{\frac{n}{\ln(n)}}\right)$ and $k=o(\ln(n))$. Note that this bound is the same as the Maker bound presented by Hefetz et al. (2012) for the $(a:b)$ connectivity game, which implies that the asymptotic optimal bias for this game is $\frac{an}{a+\ln(n)}$. This resolves the open problem stated by these authors. We also study the $(a:b)$ Hamiltonicity game in which Maker's goal is to create a Hamiltonian subgraph. For the $(1:b)$ variant Krivelevich proved that $\left(1+o(1) \right)\frac{n}{\ln n}$ is the exact threshold bias. Controlling Breaker's vertex degree in the $(a:b)$ Maker-Breaker minimum degree game enables us to the asymptotic optimal generalized threshold bias for the $(a:b)$-game, both for $a=o\left(\sqrt{\frac{n}{\ln n}} \right)$ and $a=Ω\left(\sqrt{\frac{n}{\ln n}} \right)$.

math.CO↗

arXiv2021

Hemivariational Inequalities on Graphs

In this paper, a new class of hemivariational inequalities is introduced. It concerns Laplace operator on locally finite graphs together with multivalued nonmonotone nonlinearities expressed in terms of Clarke's subdifferential. First of all, we state and prove some results on the subdifferentiability of nonconvex functionals defined on graphs. Thereafter, an elliptic hemivariational inequality on locally finite graphs is considered and the existence and uniqueness of its weak solutions are proved by means of the well-known surjectivity result for pseudomonotone mappings. In the end of this paper, we tackle the problem of hemivariational inequalities of parabolic type on locally finite graphs and we prove the existence of its weak solutions.

math.AP↗

arXiv2021

Repeated randomized algorithm for the Multicovering Problem

Let $\mathcal{H}=(V,\mathcal{E})$ be a hypergraph with maximum edge size $\ell$ and maximum degree $Δ$. For given numbers $b_v\in \mathbb{N}_{\geq 2}$, $v\in V$, a set multicover in $\mathcal{H}$ is a set of edges $C \subseteq \mathcal{E}$ such that every vertex $v$ in $V$ belongs to at least $b_v$ edges in $C$. Set multicover is the problem of finding a minimum-cardinality set multicover. Peleg, Schechtman and Wool conjectured that unless $\cal{P} =\cal{NP}$, for any fixed $Δ$ and $b:=\min_{v\in V}b_{v}$, no polynomial-time approximation algorithm for the Set multicover problem has an approximation ratio less than $δ:=Δ-b+1$. Hence, it's a challenge to know whether the problem of set multicover is not approximable within a ratio of $βδ$ with a constant $β<1$. This paper proposes a repeated randomized algorithm for the Set multicover problem combined with an initial deterministic threshold step. Boosting success by repeated trials, our algorithm yields an approximation ratio of $ \max\left\{ \frac{15}{16}δ, \left(1- \frac{(b-1)\exp\left(\frac{ 3δ+1}{8}\right)}{72 \ell} \right)δ\right\}$. The crucial fact is not only that our result improves over the approximation ratio presented by Srivastav et al (Algorithmica 2016) for any $δ\geq 13$, but it's more general since we set no restriction on the parameter $\ell$. Furthermore, we prove that it is NP-hard to approximate the Set multicover problem on $Δ$-regular hypergraphs within a factor of $(δ-1-ε)$. Moreover we show that the integrality gap for the Set multicover problem is at least $\frac{\ln_{2}(n+1)}{2b}$, which for constant $b$ is $Ω(\ln n )$.

math.CO↗

arXiv2020

Approximation algorithm for the Multicovering Problem

Let $\mathcal{H}=(V,\mathcal{E})$ be a hypergraph with maximum edge size $\ell$ and maximum degree $Δ$. For given numbers $b_v\in \mathbb{N}_{\geq 2}$, $v\in V$, a set multicover in $\mathcal{H}$ is a set of edges $C \subseteq \mathcal{E}$ such that every vertex $v$ in $V$ belongs to at least $b_v$ edges in $C$. Set Multicover is the problem of finding a minimum-cardinality set multicover. Peleg, Schechtman and Wool conjectured that for any fixed $Δ$ and $b:=\min_{v\in V}b_{v}$, the problem of \sbmultcov is not approximable within a ratio less than $δ:=Δ-b+1$, unless $\mathcal{P} =\mathcal{NP}$. Hence it's a challenge to explore for which classes of hypergraph the conjecture doesn't hold. We present a polynomial time algorithm for the Set Multicover problem which combines a deterministic threshold algorithm with conditioned randomized rounding steps. Our algorithm yields an approximation ratio of $ \max\left\{ \frac{148}{149}δ, \left(1- \frac{ (b-1)e^{\fracδ{4}}}{94\ell} \right)δ\right\}$. Our result not only improves over the approximation ratio presented by Srivastav et al (Algorithmica 2016) but it's more general since we set no restriction on the parameter $\ell$. Moreover we present a further polynomial time algorithm with an approximation ratio of $\frac{5}{6}δ$ for hypergraphs with $\ell\leq (1+ε)\bar{\ell}$ for any fixed $ε\in [0,\frac{1}{2}]$, where $\bar{\ell}$ is the average edge size. The analysis of this algorithm relies on matching/covering duality due to Ray-Chaudhuri (1960), which we convert into an approximative form. The second performance disprove the conjecture of peleg et al for a large subclass of hypergraphs.

math.CO↗

arXiv2018

A new Bound for the Maker-Breaker Triangle Game

The triangle game introduced by Chvátal and Erdős (1978) is one of the most famous combinatorial games. For $n,q\in\mathbb{N}$, the $(n,q)$-triangle game is played by two players, called Maker and Breaker, on the complete graph $K_n$. Alternately Maker claims one edge and thereafter Breaker claims $q$ edges of the graph. Maker wins the game if he can claim all three edges of a triangle, otherwise Breaker wins. Chvátal and Erdős (1978) proved that for $q<\sqrt{2n+2}-5/2\approx 1.414\sqrt{n}$ Maker has a winning strategy, and for $q\geq 2\sqrt{n}$ Breaker has a winning strategy. Since then, the problem of finding the exact leading constant for the threshold bias of the triangle game has been one of the famous open problems in combinatorial game theory. In fact, the constant is not known for any graph with a cycle and we do not even know if such a constant exists. Balogh and Samotij (2011) slightly improved the Chvátal-Erdős constant for Breaker's winning strategy from $2$ to $1.935$ with a randomized approach. Since then no progress was made. In this work, we present a new deterministic strategy for Breaker's win whenever $n$ is sufficiently large and $q\geq\sqrt{(8/3+o(1))n}\approx 1.633\sqrt{n}$, significantly reducing the gap towards the lower bound. In previous strategies Breaker chooses his edges such that one node is part of the last edge chosen by Maker, whereas the remaining node is chosen more or less arbitrarily. In contrast, we introduce a suitable potential function on the set of nodes. This allows Breaker to pick edges that connect the most `dangerous' nodes. The total potential of the game may still increase, even for several turns, but finally Breaker's strategy prevents the total potential of the game from exceeding a critical level and leads to Breaker's win.

math.CO↗

arXiv2017

Finding Euler Tours in One Pass in the W-Streaming Model with O(n log(n)) RAM

We study the problem of finding an Euler tour in an undirected graph G in the W-Streaming model with O(n polylog(n)) RAM, where n resp. m is the number of nodes resp. edges of G. Our main result is the first one pass W-Streaming algorithm computing an Euler tour of G in the form of an edge successor function with only O(n log(n)) RAM which is optimal for this setting (e.g., Sun and Woodruff (2015)). The previously best-known result in this model is implicitly given by Demetrescu et al. (2010) with the parallel algorithm of Atallah and Vishkin (1984) using O(m/n) passes under the same RAM limitation. For graphs with ω(n) edges this is non-constant. Our overall approach is to partition the edges into edge-disjoint cycles and to merge the cycles until a single Euler tour is achieved. Note that in the W-Streaming model such a merging is far from being obvious as the limited RAM allows the processing of only a constant number of cycles at once. This enforces us to merge cycles that partially are no longer present in RAM. Furthermore, the successor of an edge cannot be changed after the edge has left RAM. So, we steadily have to output edges and their designated successors, not knowing the appearance of edges and cycles yet to come. We solve this problem with a special edge swapping technique, for which two certain edges per node are sufficient to merge tours without having all of their edges in RAM. Mathematically, this is controlled by structural results on the space of certain equivalence classes corresponding to cycles and the characterization of associated successor functions. For example, we give conditions under which the swapping of edge successors leads to a merging of equivalence classes.

cs.DS↗

arXiv2016

Swap Equilibria under Link and Vertex Destruction

We initiate the study of the \emph{destruction model} (\aka \emph{adversary model}) introduced by Kliemann (2010), using the stability concept of \emph{swap equilibrium} introduced by Alon et. al (2010). The destruction model is a network formation game incorporating the robustness of a network under a more or less targeted attack. In addition to bringing in the swap equilibrium (SE) concept, we extend the model from an attack on the edges of the network to an attack on its vertices. Vertex destruction can generally cause more harm and tends to be more difficult to analyze. We prove structural results and linear upper bounds or super-linear lower bounds on the social cost of SE under different attack scenarios. The most complex case is when the vertex to be destroyed is chosen uniformly at random from the set of those vertices where each causes a maximum number of player pairs to be separated (called a max-sep vertex). We prove a lower bound on the social cost of $Ω(n^{3/2})$ for this case and initiate an understanding of the structural properties of SE in this scenario. Namely, we prove that there is no SE that is a tree and has only one max-sep vertex. We conjecture that this result can be generalized, in particular we conjecture that there is no SE that is a tree. On the other hand, we prove that if the vertex to be destroyed is chosen uniformly at random from the set of \emph{all} vertices, then each SE is a tree (unless it is two-connected). Our conjecture would imply that moving from the uniform probability measure to a measure concentrated on the max-sep vertices, means moving from no SE having a cycle (unless two-connected) to each SE having a cycle. This would ask for a more detailed study of this transition in future work.

cs.GT↗

arXiv2016

On the Query Complexity of Black-Peg AB-Mastermind

Mastermind game is a two players zero sum game of imperfect information. The first player, called codemaker, chooses a secret code and the second player, called codebreaker, tries to break the secret code by making as few guesses as possible, exploiting information that is given by the codemaker after each guess. In this paper, we consider the so called Black-Peg variant of Mastermind, where the only information concerning a guess is the number of positions in which the guess coincides with the secret code. More precisely, we deal with a special version of the Black-Peg game with n holes and k<=n colors where no repetition of colors is allowed. We present upper and lower bounds on the number of guesses necessary to break the secret code. We first come back to the upper bound results introduced by El Ouali and Sauerland (2013). For the case k=n the secret code can be algorithmically identified within less than (n-3)*ld(n)+5n/2 queries. That result improves the result of Ker-I Ko and Shia-Chung Teng (1985) by almost a factor of 2. For the case k>n we prove an upper bound for the problem of (n-1)*ld(n)+k+1. Furthermore we prove a new lower bound for (a generalization of) the case k=n that improves the recent result of Berger et al. (2016) from n-log(log(n)) to n. We also give a lower bound of k queries for the case k>n.

cs.DS↗

arXiv2016

Finding Euler Tours in the StrSort Model

We present a first algorithm for finding Euler tours in undirected graphs in the StrSort model. This model is a relaxation of the semi streaming model. The graph is given as a stream of its edges and can only be read sequentially, but while doing a pass over the stream we are allowed to write out another stream which will be the input for the next pass. In addition, items in the stream are sorted between passes. This model was introduced by Aggarwal et al. in 2004. Here we apply this model to the problem of finding an Euler tour in a graph (or to decide that the graph does not admit an Euler tour). The algorithm works in two steps. In the first step, a single pass is conducted while a linear (in the number of vertices $n$) amount of RAM is required. In the second step, $\mathcal O(\log(n))$ passes are conducted while only $\mathcal O(\log(n))$ RAM is required. We use an alteration of the algorithm of Atallah and Vishkin from 1984 for finding Euler tours in parallel. It finds a partition of edge-disjoint circuits and arranges them in a tree expressing their connectivity. Then the circuits are merged according to this tree. In order to minimize the needed amount of RAM, we evade the need to store the entire tree and use techniques suggested by Aggarwal et al. to exchange information concerning the merging of circuits.

cs.DS↗

arXiv2016

An Improved Filtering Algorithm for Big Read Datasets

For single-cell or metagenomic sequencing projects, it is necessary to sequence with a very high mean coverage in order to make sure that all parts of the sample DNA get covered by the reads produced. This leads to huge datasets with lots of redundant data. A filtering of this data prior to assembly is advisable. Titus Brown et al. (2012) presented the algorithm Diginorm for this purpose, which filters reads based on the abundance of their $k$-mers. We present Bignorm, a faster and quality-conscious read filtering algorithm. An important new feature is the use of phred quality scores together with a detailed analysis of the $k$-mer counts to decide which reads to keep. With recommended parameters, in terms of median we remove 97.15% of the reads while keeping the mean phred score of the filtered dataset high. Using the SDAdes assembler, we produce assemblies of high quality from these filtered datasets in a fraction of the time needed for an assembly from the datasets filtered with Diginorm. We conclude that read filtering is a practical method for reducing read data and for speeding up the assembly process. Our Bignorm algorithm allows assemblies of competitive quality in comparison to Diginorm, while being much faster. Bignorm is available for download at https://git.informatik.uni-kiel.de/axw/Bignorm.git

q-bio.GN↗

arXiv2015

Price of Anarchy for Graph Coloring Games with Concave Payoff

We study the price of anarchy in a class of graph coloring games (a subclass of polymatrix common-payoff games). In those games, players are vertices of an undirected, simple graph, and the strategy space of each player is the set of colors from $1$ to $k$. A tight bound on the price of anarchy of $\frac{k}{k-1}$ is known (Hoefer 2007, Kun et al. 2013), for the case that each player's payoff is the number of her neighbors with different color than herself. The study of more complex payoff functions was left as an open problem. We compute payoff for a player by determining the distance of her color to the color of each of her neighbors, applying a non-negative, real-valued, concave function $f$ to each of those distances, and then summing up the resulting values. This includes the payoff functions suggested by Kun et al. (2013) for future work as special cases. Denote $f^*$ the maximum value that $f$ attains on the possible distances $0,\dots,k-1$. We prove an upper bound of $2$ on the price of anarchy for concave functions $f$ that are non-decreasing or which assume $f^*$ at a distance on or below $\lfloor\frac{k}{2}\rfloor$. Matching lower bounds are given for the monotone case and for the case that $f^*$ is assumed in $\frac{k}{2}$ for even $k$. For general concave functions, we prove an upper bound of $3$. We use a simple but powerful technique: we obtain an upper bound of $λ\geq 1$ on the price of anarchy if we manage to give a splitting $λ_1 + \dots + λ_k = λ$ such that $\sum_{s=1}^k λ_s \cdot f(|s-p|) \geq f^*$ for all $p \in \{1,\dots,k\}$. The discovery of working splittings can be supported by computer experiments. We show how, once we have an idea what kind of splittings work, this technique helps in giving simple proofs, which mainly work by case distinctions, algebraic manipulations, and real calculus.

cs.GT↗