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20122026
most citedQuantum-centric Supercomputing for Materials Science: A Perspective on Challenges and Future Directions

85 citations · 321 across the 25 of their papers we have counts for

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Showing 2023 · quant-phShow all

5 papers · 2 filters

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★ 2 cited

A Conceptual Architecture for a Quantum-HPC Middleware

Nishant Saurabh, Shantenu Jha, Andre Luckow

Quantum computing promises potential for science and industry by solving certain computationally complex problems faster than classical computers. Quantum computing systems evolved…

quant-ph2023★ 6 cited

Application-Oriented Benchmarking of Quantum Generative Learning Using QUARK

Florian J. Kiwit, Marwa Marso, Philipp Ross +3

Benchmarking of quantum machine learning (QML) algorithms is challenging due to the complexity and variability of QML systems, e.g., regarding model ansatzes, data sets, training t…

quant-ph2023★ 28 cited

A performance characterization of quantum generative models

Carlos A. Riofrío, Oliver Mitevski, Caitlin Jones +6

Quantum generative modeling is a growing area of interest for industry-relevant applications. With the field still in its infancy, there are many competing techniques. This work is…

quant-ph2023★ 28 cited

Quantum Computing Techniques for Multi-Knapsack Problems

Abhishek Awasthi, Francesco Bär, Joseph Doetsch +16

Optimization problems are ubiquitous in various industrial settings, and multi-knapsack optimization is one recurrent task faced daily by several industries. The advent of quantum…