collaborators

6 papers

math.OC2026

Anderson Accelerated Primal-Dual Hybrid Gradient for solving LP

Yingxin Zhou, Stefano Cipolla, Phan Tu Vuong

We present the Anderson Accelerated Primal--Dual Hybrid Gradient (AA-PDHG), a fixed-point-based framework that integrates Anderson Acceleration into the PDHG method for solving lin…

quant-ph2026

Pauli-Sparse regularised Counterdiabatic Shortcuts for Linear-Ramp QAOA

Stefano Cipolla, Fabio Durastante

Combinatorial optimization is a leading target for quantum algorithms, but finite-depth QAOA can suffer from strong diabatic errors when the interpolation Hamiltonian has small, or…

math.NA2026

Nearest Reversible Markov Chains with Sparsity Constraints: An Optimization Approach

Stefano Cipolla, Fabio Durastante, Miryam Gnazzo +1

Reversibility is a key property of Markov chains, central to algorithms such as Metropolis-Hastings and other MCMC methods. Yet many applications yield non-reversible chains, motiv…

math.OC2026

A column generation approach to exact experimental design

Selin Ahipasaoglu, Stefano Cipolla, Jacek Gondzio

In this work, we address the exact D-optimal experimental design problem by proposing an efficient algorithm that rapidly identifies the support of its continuous relaxation. Our m…

quant-ph2025

Quantum Approaches to Urban Logistics: From Core QAOA to Clustered Scalability

F. Picariello, G. Turati, R. Antonelli +10

The Traveling Salesman Problem (TSP) is a fundamental challenge in combinatorial optimization, widely applied in logistics and transportation. As the size of TSP instances grows, t…

physics.soc-ph2025

Enforcing Katz and PageRank Centrality Measures in Complex Networks

Stefano Cipolla, Fabio Durastante, Beatrice Meini

We investigate the problem of enforcing a desired centrality measure in complex networks, while still keeping the original pattern of the network. Specifically, by representing the…