4 papers
Classical Combinatorial Optimization Scaling for Random Ising Models on 2D Heavy-Hex Graphs
Elijah Pelofske, Andreas Bärtschi, Stephan Eidenbenz
Motivated by near term quantum computing hardware limitations, combinatorial optimization problems that can be addressed by current quantum algorithms and noisy hardware with littl…
Quantum Graph Transformer for NLP Sentiment Classification
Shamminuj Aktar, Andreas Bärtschi, Abdel-Hameed A. Badawy +1
Quantum machine learning is a promising direction for building more efficient and expressive models, particularly in domains where understanding complex, structured data is critica…
Scaling Whole-Chip QAOA for Higher-Order Ising Spin Glass Models on Heavy-Hex Graphs
Elijah Pelofske, Andreas Bärtschi, Lukasz Cincio +2
We show through numerical simulation that the Quantum Approximate Optimization Algorithm (QAOA) for higher-order, random-coefficient, heavy-hex compatible spin glass Ising models h…
Trainability Barriers in Low-Depth QAOA Landscapes
Joel Rajakumar, John Golden, Andreas Bärtschi +1
The Quantum Alternating Operator Ansatz (QAOA) is a prominent variational quantum algorithm for solving combinatorial optimization problems. Its effectiveness depends on identifyin…