



@article {3397,
	title = {Quantum-centric Supercomputing for Materials Science: A Perspective on Challenges and Future Directions},
	year = {2023},
	month = {12/14/2023},
	abstract = {<p>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.</p>},
	url = {https://arxiv.org/abs/2312.09733},
	author = {Yuri Alexeev and Maximilian Amsler and Paul Baity and Marco Antonio Barroca and Sanzio Bassini and Torey Battelle and Daan Camps and David Casanova and Young jai Choi and Frederic T. Chong and Charles Chung and Chris Codella and Antonio D. Corcoles and James Cruise and Alberto Di Meglio and Jonathan Dubois and Ivan Duran and Thomas Eckl and Sophia Economou and Stephan Eidenbenz and Bruce Elmegreen and Clyde Fare and Ismael Faro and Cristina Sanz Fern{\'a}ndez and Rodrigo Neumann Barros Ferreira and Keisuke Fuji and Bryce Fuller and Laura Gagliardi and Giulia Galli and Jennifer R. Glick and Isacco Gobbi and Pranav Gokhale and Salvador de la Puente Gonzalez and Johannes Greiner and Bill Gropp and Michele Grossi and Emmanuel Gull and Burns Healy and Benchen Huang and Travis S. Humble and Nobuyasu Ito and Artur F. Izmaylov and Ali Javadi-Abhari and Douglas Jennewein and Shantenu Jha and Liang Jiang and Barbara Jones and Wibe Albert de Jong 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 Doga Murat Kurkcuoglu 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 Arcesio Castaneda Medina and Dirk Merten and Antonio Mezzacapo and Kristel Michielsen and Abhishek Mitra and Tushar Mittal and Kyungsun Moon and Joel Moore 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 Vincent R. Pascuzzi and Ed Penault and Tomasz Piontek and Jed Pitera and Patrick Rall and Gokul Subramanian Ravi and Niall Robertson and Matteo Rossi 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 Eric Switzer and Wei Tang and Joel Thompson and Synge Todo and Minh Tran and Dimitar Trenev and Christian Trott and Huan-Hsin Tseng and Esin Tureci and David Garc{\'\i}a Valinas and Sofia Vallecorsa and Christopher Wever and Konrad Wojciechowski and Xiaodi Wu and Shinjae Yoo and Nobuyuki Yoshioka and Victor Wen-zhe Yu and Seiji Yunoki and Sergiy Zhuk and Dmitry Zubarev}
}
@article {2530,
	title = {Quantum Computer Systems for Scientific Discovery},
	year = {2019},
	month = {12/16/2019},
	abstract = {<p>The great promise of quantum computers comes with the dual challenges of building them and finding their useful applications. We argue that these two challenges should be considered together, by co-designing full stack quantum computer systems along with their applications in order to hasten their development and potential for scientific discovery. In this context, we identify scientific and community needs, opportunities, and significant challenges for the development of quantum computers for science over the next 2-10 years. This document is written by a community of university, national laboratory, and industrial researchers in the field of Quantum Information Science and Technology, and is based on a summary from a U.S. National Science Foundation workshop on Quantum Computing held on October 21-22, 2019 in Alexandria, VA.</p>},
	url = {https://arxiv.org/abs/1912.07577},
	author = {Yuri Alexeev and Dave Bacon and Kenneth R. Brown and Robert Calderbank and Lincoln D. Carr and Frederic T. Chong and Brian DeMarco and Dirk Englund and Edward Farhi and Bill Fefferman and Alexey V. Gorshkov and Andrew Houck and Jungsang Kim and Shelby Kimmel and Michael Lange and Seth Lloyd and Mikhail D. Lukin and Dmitri Maslov and Peter Maunz and Christopher Monroe and John Preskill and Martin Roetteler and Martin Savage and Jeff Thompson and Umesh Vazirani}
}
