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 language | English |
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Pages (from-to) | 666-710 |
Number of pages | 45 |
Journal | Future Generation Computer Systems |
Volume | 160 |
DOIs | |
State | Published - 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