3 papers
quant-ph2025
Non-Perturbative Topological Gadgets for Many-Body Coupling
David Headley, Nicholas Chancellor
Continuous-time quantum hardware implementations generally lack the native capability to implement high-order terms that would facilitate efficient compilation of quantum algorithm…
cs.ET2025
Implementing Large Quantum Boltzmann Machines as Generative AI Models for Dataset Balancing
Salvatore Sinno, Markus Bertl, Arati Sahoo +3
This study explores the implementation of large Quantum Restricted Boltzmann Machines (QRBMs), a key advancement in Quantum Machine Learning (QML), as generative models on D-Wave's…
quant-ph2025
Optimized Quantum Embedding: A Universal Minor-Embedding Framework for Large Complete Bipartite Graph
Salvatore Sinno, Thomas GroÃ, Nicholas Chancellor +2
Minor embedding is essential for mapping largescale combinatorial problems onto quantum annealers, particularly in quantum machine learning and optimization. This work presents an…