93 citations · 392 across the 26 of their papers we have counts for
21 papers · 1 filter
Cluster-based Message-Passing (CluMP) Optimization for Complex QUBO Problems
Paolo Rissone, Stefan Boettcher, Alfonso Amendola +2
Quadratic Unconstrained Boolean Optimization (QUBO) problems are widespread in both industrial applications and scientific studies. A QUBO problem corresponds to the optimization o…
Physics of the Edwards-Anderson Spin Glass in Dimensions from Heuristic Ground State Optimization
Stefan Boettcher
We present a collection of simulations of the Edwards-Anderson lattice spin glass at to elucidate the nature of low-energy excitations over a range of dimensions that reach f…
Deep reinforced learning heuristic tested on spin-glass ground states: The larger picture
Stefan Boettcher
In Changjun Fan et al. [Nature Communications https://doi.org/10.1038/s41467-023-36363-w (2023)], the authors present a deep reinforced learning approach to augment combinatorial o…
Inability of a graph neural network heuristic to outperform greedy algorithms in solving combinatorial optimization problems like Max-Cut
Stefan Boettcher
In Nature Machine Intelligence 4, 367 (2022), Schuetz et al provide a scheme to employ graph neural networks (GNN) as a heuristic to solve a variety of classical, NP-hard combinato…
Analysis of landscape hierarchy during coarsening and aging in Ising spin glasses
Stefan Boettcher, Mahajabin Rahman
We use record dynamics (RD), a coarse-grained description of the ubiquitous relaxation phenomenology known as "aging", as a diagnostic tool to find universal features that distingu…
Ground State Properties of the Diluted Sherrington-Kirkpatrick Spin Glass
Stefan Boettcher
We present a numerical study of ground states of the dilute versions of the Sherrington-Kirkpatrick (SK) mean-field spin glass. In contrast to so-called "sparse" mean-field spin gl…