We show how graph neural networks can be used to solve the canonical graph coloring
problem. We frame graph coloring as a multiclass node classification problem and utilize an …

These are the lecture notes of the master's course" Quantum Computing", taught at
Chalmers University of Technology every fall since 2020, with participation of students from …

Prior work showed the efficacy of pausing midanneal: such a pause improved the probability
of success by orders of magnitude in a class of native problem instances and improved the …

Quantum computing is one of the most enticing computational paradigms with the potential
to revolutionize diverse areas of future-generation computational systems. While quantum …

Recently, in light of the success of quantum computers, research teams have actively
developed quantum-inspired computers using classical computing technology. One notable …

We benchmark Quantum Annealing (QA) vs. Simulated Annealing (SA) with a focus on the
impact of the embedding of problems onto the different topologies of the D-Wave quantum …

We introduce a quantum-inspired algorithm for Graph Coloring Problems (GCPs) that
utilizes qudits in a product state, with each qudit representing a node in the graph and …