Quantum-centric supercomputing for materials science: A perspective on challenges and future directions

Yuri Alexeev, Maximilian Amsler, Marco Antonio Barroca, Sanzio Bassini, Torey Battelle, Daan Camps, David Casanova, Young Jay Choi, Frederic T. Chong, Charles Chung, Christopher Codella, Antonio D. Córcoles, James Cruise, Alberto Di Meglio, Ivan Duran, Thomas Eckl, Sophia Economou, Stephan Eidenbenz, Bruce Elmegreen, Clyde FareIsmael Faro, Cristina Sanz Fernández, Rodrigo Neumann Barros Ferreira, Keisuke Fuji, Bryce Fuller, Laura Gagliardi, Giulia Galli, Jennifer R. Glick, Isacco Gobbi, Pranav Gokhale, Salvador de la Puente Gonzalez, Johannes Greiner, Bill Gropp, Michele Grossi, Emanuel Gull, Burns Healy, Matthew R. Hermes, Benchen Huang, Travis S. Humble, Nobuyasu Ito, Artur F. Izmaylov, Ali Javadi-Abhari, Douglas Jennewein, Shantenu Jha, Liang Jiang, Barbara Jones, Wibe Albert de Jong, Petar Jurcevic, William Kirby, Stefan Kister, Masahiro Kitagawa, Joel Klassen, Katherine Klymko, Kwangwon Koh, Masaaki Kondo, Dog̃a Murat Kürkçüog̃lu, Krzysztof Kurowski, Teodoro Laino, Ryan Landfield, Matt Leininger, Vicente Leyton-Ortega, Ang Li, Meifeng Lin, Junyu Liu, Nicolas Lorente, Andre Luckow, Simon Martiel, Francisco Martin-Fernandez, Margaret Martonosi, Claire Marvinney, Arcesio Castaneda Medina, Dirk Merten, Antonio Mezzacapo, Kristel Michielsen, Abhishek Mitra, Tushar Mittal, Kyungsun Moon, Joel Moore, Sarah Mostame, Mario Motta, Young Hye Na, Yunseong Nam, Prineha Narang, Yu ya Ohnishi, Daniele Ottaviani, Matthew Otten, Scott Pakin, Vincent R. Pascuzzi, Edwin Pednault, Tomasz Piontek, Jed Pitera, Patrick Rall, Gokul Subramanian Ravi, Niall Robertson, Matteo A.C. Rossi, Piotr Rydlichowski, Hoon Ryu, Georgy Samsonidze, Mitsuhisa Sato, Nishant Saurabh, Vidushi Sharma, Kunal Sharma, Soyoung Shin, George Slessman, Mathias Steiner, Iskandar Sitdikov, In Saeng Suh, Eric D. Switzer, Wei Tang, Joel Thompson, Synge Todo, Minh C. Tran, Dimitar Trenev, Christian Trott, Huan Hsin Tseng, Norm M. Tubman, Esin Tureci, David García Valiñas, Sofia Vallecorsa, Christopher Wever, Konrad Wojciechowski, Xiaodi Wu, Shinjae Yoo, Nobuyuki Yoshioka, Victor Wen zhe Yu, Seiji Yunoki, Sergiy Zhuk, Dmitry Zubarev

Research output: Contribution to journalArticlepeer-review

8 Scopus citations

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 high-performance 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.

Original languageEnglish
Pages (from-to)666-710
Number of pages45
JournalFuture Generation Computer Systems
Volume160
DOIs
StatePublished - Nov 2024

Funding

Y.A. acknowledges support from the U.S. Department of Energy, Office of Science , under contract DE-AC02-06CH11357 at Argonne National Laboratory. A.D.M., M.G, and S.V. are supported by CERN through the CERN Quantum Technology Initiative (CERN QTI) . A.F.I. acknowledges financial support from the Natural Sciences and Engineering Council of Canada (NSERC) . The work at the DIPC was funded by the Gipuzkoa Provincial Council (project QUAN-000021-01 ), the European Union (project NextGenerationEU/PRTR-C17.I1) , as well as by the IKUR Strategy under the collaboration agreement between Ikerbasque Foundation and DIPC on behalf of the Department of Education of the Basque Government . Y.A., G.G., L.G., A.M. M.H. and B.H. acknowledge funding support from the Next Generation Quantum Science and Engineering (Q-NEXT), supported by the U.S. Department of Energy, Office of Science, National Quantum Information Science Research Centers . A.L. and T.S.H. acknowledge support from the U.S. Department of Energy, Office of Science, National Quantum Information Science Research Centers, Quantum Science Center (QSC) . W.A.d.J. acknowledges funding support from the Quantum Systems Accelerator (QSA) , supported by the U.S. Department of Energy, Office of Science, National Quantum Information Science Research Centers . N.M.T. acknowledges support from by U.S. Department of Energy, Office of Science, National Quantum Information Science Research Centers, Co-Design Center for Quantum Advantage under Contract No. DE-SC0012704 (C2QA). L.G., A.M. and M.H. acknowledge partial support from the NSF QuBBE Quantum Leap Challenge Institute (Grant No. NSF OMA-2121044 ). The work at the Oak Ridge National Laboratory used resources of the Oak Ridge Leadership Computing Facility which is supported by the Office of Science of the U.S. Department of Energy under Contract No. DE-AC05-00OR22725 . Y.A. acknowledges support from the U.S. Department of Energy, Office of Science, under contract DE-AC02-06CH11357 at Argonne National Laboratory. A.D.M. M.G, and S.V. are supported by CERN through the CERN Quantum Technology Initiative (CERN QTI). A.F.I. acknowledges financial support from the Natural Sciences and Engineering Council of Canada (NSERC). The work at the DIPC was funded by the Gipuzkoa Provincial Council (project QUAN-000021-01), the European Union (project NextGenerationEU/PRTR-C17.I1), as well as by the IKUR Strategy under the collaboration agreement between Ikerbasque Foundation and DIPC on behalf of the Department of Education of the Basque Government. Y.A. G.G. L.G. A.M. M.H. and B.H. acknowledge funding support from the Next Generation Quantum Science and Engineering (Q-NEXT), supported by the U.S. Department of Energy, Office of Science, National Quantum Information Science Research Centers. A.L. and T.S.H. acknowledge support from the U.S. Department of Energy, Office of Science, National Quantum Information Science Research Centers, Quantum Science Center (QSC). W.A.d.J. acknowledges funding support from the Quantum Systems Accelerator (QSA), supported by the U.S. Department of Energy, Office of Science, National Quantum Information Science Research Centers. N.M.T. acknowledges support from by U.S. Department of Energy, Office of Science, National Quantum Information Science Research Centers, Co-Design Center for Quantum Advantage under Contract No. DE-SC0012704 (C2QA). L.G. A.M. and M.H. acknowledge partial support from the NSF QuBBE Quantum Leap Challenge Institute (Grant No. NSF OMA-2121044). The work at the Oak Ridge National Laboratory used resources of the Oak Ridge Leadership Computing Facility which is supported by the Office of Science of the U.S. Department of Energy under Contract No. DE-AC05-00OR22725.

Keywords

  • High-performance computing
  • Materials science
  • Quantum computing
  • Quantum-centric supercomputing

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