12 papers
Constrained Quantum Optimization at Utility Scale: Application to the Knapsack Problem
Naeimeh Mohseni, Julien-Pierre Houle, Ibrahim Shehzad +3
Constrained combinatorial optimization problems are challenging for quantum computing, particularly at utility-relevant scales and on near-term hardware. At the same time, these pr…
Hierarchical divide and conquer quantum approach to combinatorial optimization problems with tunable reduction
Mathias Schmid, Naeimeh Mohseni, Michael J. Hartmann
Combinatorial optimization is considered a promising class of problems in which quantum computers can show significant advantages. However, problems of practical relevance typicall…
Boosting Sparsity in Graph Decompositions with QAOA Sampling
George Pennington, Naeimeh Mohseni, Oscar Wallis +5
We study the problem of decomposing a graph into a weighted sum of a small number of matchings, a task that arises in network resource allocation problems such as peer-to-peer ener…
Demonstrating Quantum Scaling Advantage in Approximate Optimization for Energy Coalition Formation with 100+ Agents
Naeimeh Mohseni, Thomas Morstyn, Corey O'Meara +3
The formation of energy communities is pivotal for advancing decentralized and sustainable energy management. Within this context, Coalition Structure Generation (CSG) emerges as a…
Quantum Optimization Benchmarking Library - The Intractable Decathlon
Thorsten Koch, David E. Bernal Neira, Ying Chen +24
Through recent progress in hardware development, quantum computers have advanced to the point where benchmarking of (heuristic) quantum algorithms at scale is within reach. Particu…
Mitigating exponential concentration in covariant quantum kernels for subspace and real-world data
Gabriele Agliardi, Giorgio Cortiana, Anton Dekusar +6
Fidelity quantum kernels have shown promise in classification tasks, particularly when a group structure in the data can be identified and exploited through a covariant feature map…