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

• DOI: 10.1016/j.future.2024.04.060
• Publication Date: 2024-05-31T16:50:29Z
• Authors: Yuri Alexeev; Maximilian Amsler; Marco Antonio Bar...; 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 Fare; Ismael Faro; Cristina Sanz Fer...; Rodrigo Neumann B...; Keisuke Fuji; Bryce Fuller; Laura Gagliardi; Giulia Galli; Jennifer R. Glick; Isacco Gobbi; Pranav Gokhale; Salvador de la Pu...; 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 Kürkç...; Krzysztof Kurowski; Teodoro Laino; Ryan Landfield; Matt Leininger; Vicente Leyton-Or...; Ang Li; Meifeng Lin; Junyu Liu; Nicolas Lorente; Andre Luckow; Simon Martiel; Francisco Martin-...; Margaret Martonosi; Claire Marvinney; Arcesio Castaneda...; 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...; 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
• Keywords: Distributed Computing and Systems Software; Quantum Physics; Condensed Matter - Materials Science; Data Management and Data Science; Data management and data science; Distributed computing and systems software; Quantum-centric supercomputing; Materials Science (cond-mat.mtrl-sci); FOS: Physical sciences; Quantum computing; Materials science; 620; 004; Computer Software; Networking and Information Technology R&D (NITRD); Information and Computing Sciences; Information systems; Distributed Computing; Quantum Physics (quant-ph); High-performance computing; info:eu-repo/classification/ddc/004; Information Systems

Computational models are an essential tool for the design, characterization, and discovery of novel materials. Hard computational tasks in materials science stretch the limits of existing high-performance supercomputing centers, consuming much of their simulation, analysis, and data resources. 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.<br/>65 pages, 15 figures; comments welcome<br/>