91 citations · 262 across the 7 of their papers we have counts for
Showing 2023Show all
2 papers · 1 filter
quant-ph2023★ 85 cited
Quantum-centric Supercomputing for Materials Science: A Perspective on Challenges and Future Directions
Yuri Alexeev, Maximilian Amsler, Paul Baity +124
Computational models are an essential tool for the design, characterization, and discovery of novel materials. Hard computational tasks in materials science stretch the limits of e…
quant-ph2023★ 63 cited
Machine Learning for Practical Quantum Error Mitigation
Haoran Liao, Derek S. Wang, Iskandar Sitdikov +3
Quantum computers progress toward outperforming classical supercomputers, but quantum errors remain their primary obstacle. The key to overcoming errors on near-term devices has em…