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. Corcoles; James Cruise; Alberto Di Meglio; Ivan Duran; Thomas Eckl; Sophia Economou; Stephan Eidenbenz; Bruce Elmegreen; Clyde Fare; Ismael Faro; Cristina Sanz Fernandez; 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; Doga Murat Kurkcuoglu; 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 Garcia Valinas; Sofia Vallecorsa; Christopher Wever; Konrad Wojciechowski; Xiaodi Wu; Shinjae Yoo; Nobuyuki Yoshioka; Victor Wen-zhe Yu; Seiji Yunoki; Sergiy Zhuk; Dmitry Zubarev

doi:10.1016/j.future.2024.04.060

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. Corcoles, James Cruise, Alberto Di Meglio, Ivan Duran, Thomas Eckl, Sophia Economou, Stephan Eidenbenz, Bruce Elmegreen, Clyde FareIsmael Faro, Cristina Sanz Fernandez, 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, Doga Murat Kurkcuoglu, 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 Garcia Valinas, Sofia Vallecorsa, Christopher Wever, Konrad Wojciechowski, Xiaodi Wu, Shinjae Yoo, Nobuyuki Yoshioka, Victor Wen-zhe Yu, Seiji Yunoki, Sergiy Zhuk, Dmitry Zubarev

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Research output: Contribution to journal › Article › Academic › peer-review

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.

Original language	English
Pages (from-to)	666-710
Number of pages	45
Journal	Future Generation Computer Systems
Volume	160
Early online date	26 Jun 2024
DOIs	https://doi.org/10.1016/j.future.2024.04.060
Publication status	Published - Nov 2024

Bibliographical note

Publisher Copyright:
© 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.

Funders	Funder number
CERN Quantum Technology Initiative
Quantum Science Center
NSF QuBBE Quantum Leap Challenge Institute
Department of Education of the Basque Government
IKUR
European Commission
U.S. Department of Energy
Argonne National Laboratory
Ikerbasque Foundation
Natural Sciences and Engineering Research Council of Canada
Q-NEXT
National Quantum Information Science Research Centers
Next Generation Quantum Science and Engineering
CERN
Diputación Foral de Gipuzkoa	QUAN-000021-01
Co-Design Center for Quantum Advantage	DE-SC0012704
National Science Foundation	DE-AC05-00OR22725, OMA-2121044
Office of Science	DE-AC02-06CH11357

Keywords

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

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10.1016/j.future.2024.04.060

1-s2.0-S0167739X24002012-mainFinal published version, 3.17 MBLicence: Taverne

Cite this

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., ... Zubarev, D. (2024). Quantum-centric supercomputing for materials science: A perspective on challenges and future directions. Future Generation Computer Systems, 160, 666-710. https://doi.org/10.1016/j.future.2024.04.060

@article{35551c8e6aa24a17bc38a0924588dd7a,

title = "Quantum-centric supercomputing for materials science: A perspective on challenges and future directions",

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",

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

note = "Publisher Copyright: {\textcopyright} 2024",

year = "2024",

month = nov,

doi = "10.1016/j.future.2024.04.060",

language = "English",

volume = "160",

pages = "666--710",

journal = "Future Generation Computer Systems",

issn = "0167-739X",

publisher = "Elsevier BV",

}

Alexeev, Y, Amsler, M, Barroca, MA, Bassini, S, Battelle, T, Camps, D, Casanova, D, Choi, YJ, Chong, FT, Chung, C, Codella, C, Corcoles, AD, Cruise, J, Di Meglio, A, Duran, I, Eckl, T, Economou, S, Eidenbenz, S, Elmegreen, B, Fare, C, Faro, I, Fernandez, CS, Ferreira, RNB, Fuji, K, Fuller, B, Gagliardi, L, Galli, G, Glick, JR, Gobbi, I, Gokhale, P, Gonzalez, SDLP, Greiner, J, Gropp, B, Grossi, M, Gull, E, Healy, B, Hermes, MR, Huang, B, Humble, TS, Ito, N, Izmaylov, AF, Javadi-Abhari, A, Jennewein, D, Jha, S, Jiang, L, Jones, B, de Jong, WA, Jurcevic, P, Kirby, W, Kister, S, Kitagawa, M, Klassen, J, Klymko, K, Koh, K, Kondo, M, Kurkcuoglu, DM, 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, AC, 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, VR, Pednault, E, Piontek, T, Pitera, J, Rall, P, Ravi, GS, Robertson, N, Rossi, MAC, 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, ED, Tang, W, Thompson, J, Todo, S, Tran, MC, Trenev, D, Trott, C, Tseng, H-H, Tubman, NM, Tureci, E, Valinas, DG, Vallecorsa, S, Wever, C, Wojciechowski, K, Wu, X, Yoo, S, Yoshioka, N, Yu, VW, 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

TY - JOUR

T1 - Quantum-centric supercomputing for materials science

T2 - A perspective on challenges and future directions

AU - Alexeev, Yuri

AU - Amsler, Maximilian

AU - Barroca, Marco Antonio

AU - Bassini, Sanzio

AU - Battelle, Torey

AU - Camps, Daan

AU - Casanova, David

AU - Choi, Young Jay

AU - Chong, Frederic T.

AU - Chung, Charles

AU - Codella, Christopher

AU - Corcoles, Antonio D.

AU - Cruise, James

AU - Di Meglio, Alberto

AU - Duran, Ivan

AU - Eckl, Thomas

AU - Economou, Sophia

AU - Eidenbenz, Stephan

AU - Elmegreen, Bruce

AU - Fare, Clyde

AU - Faro, Ismael

AU - Fernandez, Cristina Sanz

AU - Ferreira, Rodrigo Neumann Barros

AU - Fuji, Keisuke

AU - Fuller, Bryce

AU - Gagliardi, Laura

AU - Galli, Giulia

AU - Glick, Jennifer R.

AU - Gobbi, Isacco

AU - Gokhale, Pranav

AU - Gonzalez, Salvador de la Puente

AU - Greiner, Johannes

AU - Gropp, Bill

AU - Grossi, Michele

AU - Gull, Emanuel

AU - Healy, Burns

AU - Hermes, Matthew R.

AU - Huang, Benchen

AU - Humble, Travis S.

AU - Ito, Nobuyasu

AU - Izmaylov, Artur F.

AU - Javadi-Abhari, Ali

AU - Jennewein, Douglas

AU - Jha, Shantenu

AU - Jiang, Liang

AU - Jones, Barbara

AU - de Jong, Wibe Albert

AU - Jurcevic, Petar

AU - Kirby, William

AU - Kister, Stefan

AU - Kitagawa, Masahiro

AU - Klassen, Joel

AU - Klymko, Katherine

AU - Koh, Kwangwon

AU - Kondo, Masaaki

AU - Kurkcuoglu, Doga Murat

AU - Kurowski, Krzysztof

AU - Laino, Teodoro

AU - Landfield, Ryan

AU - Leininger, Matt

AU - Leyton-Ortega, Vicente

AU - Li, Ang

AU - Lin, Meifeng

AU - Liu, Junyu

AU - Lorente, Nicolas

AU - Luckow, Andre

AU - Martiel, Simon

AU - Martin-Fernandez, Francisco

AU - Martonosi, Margaret

AU - Marvinney, Claire

AU - Medina, Arcesio Castaneda

AU - Merten, Dirk

AU - Mezzacapo, Antonio

AU - Michielsen, Kristel

AU - Mitra, Abhishek

AU - Mittal, Tushar

AU - Moon, Kyungsun

AU - Moore, Joel

AU - Mostame, Sarah

AU - Motta, Mario

AU - Na, Young-Hye

AU - Nam, Yunseong

AU - Narang, Prineha

AU - Ohnishi, Yu-ya

AU - Ottaviani, Daniele

AU - Otten, Matthew

AU - Pakin, Scott

AU - Pascuzzi, Vincent R.

AU - Pednault, Edwin

AU - Piontek, Tomasz

AU - Pitera, Jed

AU - Rall, Patrick

AU - Ravi, Gokul Subramanian

AU - Robertson, Niall

AU - Rossi, Matteo A. C.

AU - Rydlichowski, Piotr

AU - Ryu, Hoon

AU - Samsonidze, Georgy

AU - Sato, Mitsuhisa

AU - Saurabh, Nishant

AU - Sharma, Vidushi

AU - Sharma, Kunal

AU - Shin, Soyoung

AU - Slessman, George

AU - Steiner, Mathias

AU - Sitdikov, Iskandar

AU - Suh, In-Saeng

AU - Switzer, Eric D.

AU - Tang, Wei

AU - Thompson, Joel

AU - Todo, Synge

AU - Tran, Minh C.

AU - Trenev, Dimitar

AU - Trott, Christian

AU - Tseng, Huan-Hsin

AU - Tubman, Norm M.

AU - Tureci, Esin

AU - Valinas, David Garcia

AU - Vallecorsa, Sofia

AU - Wever, Christopher

AU - Wojciechowski, Konrad

AU - Wu, Xiaodi

AU - Yoo, Shinjae

AU - Yoshioka, Nobuyuki

AU - Yu, Victor Wen-zhe

AU - Yunoki, Seiji

AU - Zhuk, Sergiy

AU - Zubarev, Dmitry

PY - 2024/11

Y1 - 2024/11

N2 - 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.

AB - 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.

KW - High-performance computing

KW - Materials science

KW - Quantum computing

KW - Quantum-centric supercomputing

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U2 - 10.1016/j.future.2024.04.060

DO - 10.1016/j.future.2024.04.060

M3 - Article

SN - 0167-739X

VL - 160

SP - 666

EP - 710

JO - Future Generation Computer Systems

JF - Future Generation Computer Systems

ER -

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

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