181 citations · 334 across the 27 of their papers we have counts for
4 papers · 2 filters
Scaling Quantum Optimization to the Thousand-Qubit Scale with Distributed Quantum Sampling
Amana Liaqat, Ahmed Darwish, Stephen DiAdamo +6
The Minimum Birkhoff Decomposition (MBD) seeks a sparse weighted sum of matchings and is a challenging optimization problem with applications in network scheduling and energy tradi…
Hybrid Quantum-Classical Machine Learning Algorithms for Multi-Output Time-Series Forecasting at Utility Scale
Mackenson Polché, Varun Puram, Aditi Lal +6
Multi-output time-series forecasting in energy systems is challenging because of nonlinear dynamics, multi-scale seasonality, and strong dependencies across correlated series. In t…
Breaking concentration barriers for quantum extreme learning on digital quantum processors
Timothée Dao, Ege Yilmaz, Ibrahim Shehzad +8
Reservoir computing leverages rich, non-linear dynamics to process temporal data. Quantum variants promise enhanced expressivity from high-dimensional Hilbert spaces, yet their pra…
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…