Francesco Tudisco

Publications · Keyword

Graph Partitioning

5 publications with this keyword.

Drone delivery packing problem on a neutral-atom quantum computer

Sara Tarquini, Matteo Vandelli, Francesco Ferrari, Daniele Dragoni, Francesco Tudisco

Advanced Quantum Technologies, 2026

Quantum architectures based on neutral atoms have gained significant attention in recent years as specialized computational machines due to their ability to directly encode the independent set constraint on graphs, exploiting the Rydberg blockade mechanism. In this work, we address the Drone Delivery Packing Problem …

The graph $\infty$-Laplacian eigenvalue problem

Piero Deidda, Martin Burger, Mario Putti, Francesco Tudisco

SIAM Journal on Mathematical Analysis, 2026

We analyze various formulations of the $\infty$-Laplacian eigenvalue problem on graphs, comparing their properties and highlighting their respective advantages and limitations. First, we investigate the graph $\infty$-eigenpairs arising as limits of $p$-Laplacian eigenpairs, extending key results from the continuous …

Core-periphery partitioning and quantum annealing

Catherine F. Higham, Desmond J. Higham, Francesco Tudisco

ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2022

We propose a new kernel that quantifies success for the task of computing a core-periphery partition for an undirected network. Finding the associated optimal partitioning may be expressed in the form of a quadratic unconstrained binary optimization (QUBO) problem, to which a state-of-the-art quantum annealer may be …

Nodal domain count for the generalized graph $p$-Laplacian

Piero Deidda, Mario Putti, Francesco Tudisco

Applied and Computational Harmonic Analysis, vol. 64, pp. 1–32, 2023

Inspired by the linear Schrödinger operator, we consider a generalized $p$-Laplacian operator on discrete graphs and present new results that characterize several spectral properties of this operator with particular attention to the nodal domain count of its eigenfunctions. Just like the one-dimensional continuous …

An algebraic analysis of the graph modularity

Dario Fasino, Francesco Tudisco

SIAM Journal on Matrix Analysis and Applications, vol. 35, pp. 997–1018, 2014

One of the most relevant tasks in network analysis is the detection of community structures, or clustering. Most popular techniques for community detection are based on the maximization of a quality function called modularity, which in turn is based upon particular quadratic forms associated to a real symmetric …