Quantum-centric supercomputing for materials science: A perspective on challenges and future directions
Publication date
2024-11
Authors
Alexeev, Yuri
Amsler, Maximilian
Barroca, Marco Antonio
Bassini, Sanzio
Battelle, Torey
Camps, Daan
Casanova, David
Choi, Young Jay
Chong, Frederic T.
Chung, Charles
Editors
Advisors
Supervisors
Document Type
Article
Metadata
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License
taverne
Abstract
Computational models are an essential tool for the design, characterization, and discovery of novel materials. Computationally hard tasks in materials science stretch the limits of existing high-performance supercomputing centers, consuming much of their resources for simulation, analysis, and data processing. Quantum computing, on the other hand, is an emerging technology with the potential to accelerate many of the computational tasks needed for materials science. In order to do that, the quantum technology must interact with conventional highperformance computing in several ways: approximate results validation, identification of hard problems, and synergies in quantum-centric supercomputing. In this paper, we provide a perspective on how quantum-centric supercomputing can help address critical computational problems in materials science, the challenges to face in order to solve representative use cases, and new suggested directions.
Keywords
High-performance computing, Materials science, Quantum computing, Quantum-centric supercomputing, Taverne, Software, Hardware and Architecture, Computer Networks and Communications
Citation
Alexeev, Y, Amsler, M, Barroca, M A, Bassini, S, Battelle, T, Camps, D, Casanova, D, Choi, Y J, Chong, F T, Chung, C, Codella, C, Corcoles, A D, Cruise, J, Di Meglio, A, Duran, I, Eckl, T, Economou, S, Eidenbenz, S, Elmegreen, B, Fare, C, Faro, I, Fernandez, C S, Ferreira, R N B, Fuji, K, Fuller, B, Gagliardi, L, Galli, G, Glick, J R, Gobbi, I, Gokhale, P, Gonzalez, S D L P, Greiner, J, Gropp, B, Grossi, M, Gull, E, Healy, B, Hermes, M R, Huang, B, Humble, T S, Ito, N, Izmaylov, A F, Javadi-Abhari, A, Jennewein, D, Jha, S, Jiang, L, Jones, B, de Jong, W A, Jurcevic, P, Kirby, W, Kister, S, Kitagawa, M, Klassen, J, Klymko, K, Koh, K, Kondo, M, Kurkcuoglu, D M, Kurowski, K, Laino, T, Landfield, R, Leininger, M, Leyton-Ortega, V, Li, A, Lin, M, Liu, J, Lorente, N, Luckow, A, Martiel, S, Martin-Fernandez, F, Martonosi, M, Marvinney, C, Medina, A C, Merten, D, Mezzacapo, A, Michielsen, K, Mitra, A, Mittal, T, Moon, K, Moore, J, Mostame, S, Motta, M, Na, Y-H, Nam, Y, Narang, P, Ohnishi, Y, Ottaviani, D, Otten, M, Pakin, S, Pascuzzi, V R, Pednault, E, Piontek, T, Pitera, J, Rall, P, Ravi, G S, Robertson, N, Rossi, M A C, Rydlichowski, P, Ryu, H, Samsonidze, G, Sato, M, Saurabh, N, Sharma, V, Sharma, K, Shin, S, Slessman, G, Steiner, M, Sitdikov, I, Suh, I-S, Switzer, E D, Tang, W, Thompson, J, Todo, S, Tran, M C, Trenev, D, Trott, C, Tseng, H-H, Tubman, N M, Tureci, E, Valinas, D G, Vallecorsa, S, Wever, C, Wojciechowski, K, Wu, X, Yoo, S, Yoshioka, N, Yu, V W, Yunoki, S, Zhuk, S & Zubarev, D 2024, 'Quantum-centric supercomputing for materials science : A perspective on challenges and future directions', Future Generation Computer Systems, vol. 160, pp. 666-710. https://doi.org/10.1016/j.future.2024.04.060