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

Collections

Open Access logo

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