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The quantum approximate optimization algorithm (QAOA) has the potential to approximately solve complex combinatorial optimization problems in polynomial time. However, current noisy quantum devices cannot solve large problems due to…

Given a graph $G$ with $n$ vertices and maximum degree $\Delta$, it is known that $G$ admits a vertex coloring with $\Delta + 1$ colors such that no edge of $G$ is monochromatic. This can be seen constructively by a simple greedy algorithm,…

Data Structures and Algorithms · Computer Science 2021-02-16 Jackson Morris , Fang Song

We improve the running time of the general algorithmic technique known as Baker's approach (1994) on H-minor-free graphs from O(n^{f(|H|)}) to O(f(|H|) n^{O(1)}). The numerous applications include e.g. a 2-approximation for coloring and…

Data Structures and Algorithms · Computer Science 2015-05-18 Siamak Tazari

The starting point of our work is a decade-old open question concerning the subexponential parameterized complexity of \textsc{2-Layer Crossing Minimization}. In this problem, the input is an $n$-vertex graph $G$ whose vertices are…

Data Structures and Algorithms · Computer Science 2025-10-16 Fedor V. Fomin , Petr A. Golovach , Tanmay Inamdar , Saket Saurabh , Meirav Zehavi

Large scale complex systems, such as social networks, electrical power grid, database structure, consumption pattern or brain connectivity, are often modeled using network graphs. Valuable insight can be gained by measuring the similarity…

Quantum Physics · Physics 2019-03-01 Callum Schofield , Jingbo B. Wang , Yuying Li

The problems of computing eccentricity, radius, and diameter are fundamental to graph theory. These parameters are intrinsically defined based on the distance metric of the graph. In this work, we propose quantum algorithms for the diameter…

Quantum Physics · Physics 2025-02-28 Adam Wesołowski , Jinge Bao

Graph kernel is a powerful tool measuring the similarity between graphs. Most of the existing graph kernels focused on node labels or attributes and ignored graph hierarchical structure information. In order to effectively utilize graph…

Machine Learning · Computer Science 2020-11-03 Kai Ma , Peng Wan , Daoqiang Zhang

We consider the quantum query complexity of local search as a function of graph geometry. Given a graph $G = (V,E)$ with $n$ vertices and black box access to a function $f : V \to \mathbb{R}$, the goal is find a vertex $v$ that is a local…

Computational Complexity · Computer Science 2024-12-19 Simina Brânzei , Nicholas J. Recker

In this work, we propose a novel approach for subgraph matching, the problem of finding a given query graph in a large source graph, based on the fused Gromov-Wasserstein distance. We formulate the subgraph matching problem as a partial…

Information Theory · Computer Science 2024-07-01 Wen-Xin Pan , Isabel Haasler , Pascal Frossard

How efficiently can we find an unknown graph using distance or shortest path queries between its vertices? Let $G = (V,E)$ be an unweighted, connected graph of bounded degree. The edge set $E$ is initially unknown, and the graph can be…

Data Structures and Algorithms · Computer Science 2015-02-19 Sampath Kannan , Claire Mathieu , Hang Zhou

A graph $H$ is {\em $p$-edge colorable} if there is a coloring $\psi: E(H) \rightarrow \{1,2,\dots,p\}$, such that for distinct $uv, vw \in E(H)$, we have $\psi(uv) \neq \psi(vw)$. The {\sc Maximum Edge-Colorable Subgraph} problem takes as…

Discrete Mathematics · Computer Science 2020-08-19 Akanksha Agrawal , Madhumita Kundu , Abhishek Sahu , Saket Saurabh , Prafullkumar Tale

Local Search problem, which finds a local minimum of a black-box function on a given graph, is of both practical and theoretical importance to combinatorial optimization, complexity theory and many other areas in theoretical computer…

Quantum Physics · Physics 2007-05-23 Shengyu Zhang

Can Grover's algorithm speed up search of a physical region - for example a 2-D grid of size sqrt(n) by sqrt(n)? The problem is that sqrt(n) time seems to be needed for each query, just to move amplitude across the grid. Here we show that…

Quantum Physics · Physics 2007-05-23 Scott Aaronson , Andris Ambainis

The notion of $\mathcal{H}$-treewidth, where $\mathcal{H}$ is a hereditary graph class, was recently introduced as a generalization of the treewidth of an undirected graph. Roughly speaking, a graph of $\mathcal{H}$-treewidth at most $k$…

Data Structures and Algorithms · Computer Science 2023-06-30 Bart M. P. Jansen , Jari J. H. de Kroon , Michal Wlodarczyk

The recently introduced graph parameter tree-cut width plays a similar role with respect to immersions as the graph parameter treewidth plays with respect to minors. In this paper, we provide the first algorithmic applications of tree-cut…

Data Structures and Algorithms · Computer Science 2022-06-03 Robert Ganian , Eun Jung Kim , Stefan Szeider

We study the problem of learning an unknown graph provided via an oracle using a quantum algorithm. We consider three query models. In the first model ("OR queries"), the oracle returns whether a given subset of the vertices contains any…

Quantum Physics · Physics 2021-01-26 Ashley Montanaro , Changpeng Shao

In this work, we unify several quantum algorithmic frameworks for boolean functions that are based on the quantum adversary bound. First, we show that the $st$-connectivity framework subsumes the (adaptive/extended) learning graph…

Quantum Physics · Physics 2026-02-10 Arjan Cornelissen

Let U be a universe on n elements, let k be a positive integer, and let F be a family of (implicitly defined) subsets of U. We consider the problems of partitioning U into k sets from F, covering U with k sets from F, and packing k…

Data Structures and Algorithms · Computer Science 2023-11-15 Serge Gaspers , Jerry Zirui Li

The Quantum CONGEST model is a variant of the CONGEST model, where messages consist of $O(\log(n))$ qubits. We give a general framework for implementing quantum query algorithms in Quantum CONGEST, using the concept of parallel-queries. We…

Quantum Physics · Physics 2022-06-20 Joran van Apeldoorn , Tijn de Vos

We present a novel framework based on optimal transport for the challenging problem of comparing graphs. Specifically, we exploit the probabilistic distribution of smooth graph signals defined with respect to the graph topology. This allows…

Machine Learning · Computer Science 2019-12-09 Hermina Petric Maretic , Mireille EL Gheche , Giovanni Chierchia , Pascal Frossard
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