05435nas a2201621 4500008004100000245010800041210006900149260001500218520094500233100001801178700002301196700001601219700002801235700002001263700002001283700001601303700002001319700002101339700002401360700001901384700001901403700002601422700001801448700002301466700002101489700001601510700001701526700002101543700002301564700002101587700001601608700001701624700003101641700003401672700001801706700001801724700002101742700001801763700002401781700001801805700002001823700003501843700002201878700001601900700002001916700001901936700001701955700001901972700002301991700001802014700002402032700002302056700002302079700001802102700001702120700001902137700002602156700002002182700001902202700001902221700002302240700001802263700002202281700001802303700001902321700002802340700002402368700001902392700002002411700002002431700002702451700001202478700001702490700001502507700002102522700001802543700001902561700003202580700002402612700002202636700003102658700001702689700002302706700002402729700002002753700001902773700001902792700001602811700001702827700001802844700001802862700002002880700001902900700002302919700001902942700001702961700002602978700001603004700002003020700001603040700001803056700002803074700002103102700001803123700002403141700001403165700002303179700002003202700002103222700002003243700001803263700001803281700002103299700002103320700002303341700001803364700001803382700001403400700001903414700001603433700001503449700002003464700002103484700002103505700001703526700002803543700002203571700002303593700002603616700001503642700001703657700002303674700002403697700001803721700001703739700002003756856003703776 2023 eng d00aQuantum-centric Supercomputing for Materials Science: A Perspective on Challenges and Future Directions0 aQuantumcentric Supercomputing for Materials Science A Perspectiv c12/14/20233 a
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.
1 aAlexeev, Yuri1 aAmsler, Maximilian1 aBaity, Paul1 aBarroca, Marco, Antonio1 aBassini, Sanzio1 aBattelle, Torey1 aCamps, Daan1 aCasanova, David1 aChoi, Young, jai1 aChong, Frederic, T.1 aChung, Charles1 aCodella, Chris1 aCorcoles, Antonio, D.1 aCruise, James1 aDi Meglio, Alberto1 aDubois, Jonathan1 aDuran, Ivan1 aEckl, Thomas1 aEconomou, Sophia1 aEidenbenz, Stephan1 aElmegreen, Bruce1 aFare, Clyde1 aFaro, Ismael1 aFernández, Cristina, Sanz1 aFerreira, Rodrigo, Neumann Ba1 aFuji, Keisuke1 aFuller, Bryce1 aGagliardi, Laura1 aGalli, Giulia1 aGlick, Jennifer, R.1 aGobbi, Isacco1 aGokhale, Pranav1 aGonzalez, Salvador, de la Puen1 aGreiner, Johannes1 aGropp, Bill1 aGrossi, Michele1 aGull, Emmanuel1 aHealy, Burns1 aHuang, Benchen1 aHumble, Travis, S.1 aIto, Nobuyasu1 aIzmaylov, Artur, F.1 aJavadi-Abhari, Ali1 aJennewein, Douglas1 aJha, Shantenu1 aJiang, Liang1 aJones, Barbara1 ade Jong, Wibe, Albert1 aJurcevic, Petar1 aKirby, William1 aKister, Stefan1 aKitagawa, Masahiro1 aKlassen, Joel1 aKlymko, Katherine1 aKoh, Kwangwon1 aKondo, Masaaki1 aKurkcuoglu, Doga, Murat1 aKurowski, Krzysztof1 aLaino, Teodoro1 aLandfield, Ryan1 aLeininger, Matt1 aLeyton-Ortega, Vicente1 aLi, Ang1 aLin, Meifeng1 aLiu, Junyu1 aLorente, Nicolas1 aLuckow, Andre1 aMartiel, Simon1 aMartin-Fernandez, Francisco1 aMartonosi, Margaret1 aMarvinney, Claire1 aMedina, Arcesio, Castaneda1 aMerten, Dirk1 aMezzacapo, Antonio1 aMichielsen, Kristel1 aMitra, Abhishek1 aMittal, Tushar1 aMoon, Kyungsun1 aMoore, Joel1 aMotta, Mario1 aNa, Young-Hye1 aNam, Yunseong1 aNarang, Prineha1 aOhnishi, Yu-ya1 aOttaviani, Daniele1 aOtten, Matthew1 aPakin, Scott1 aPascuzzi, Vincent, R.1 aPenault, Ed1 aPiontek, Tomasz1 aPitera, Jed1 aRall, Patrick1 aRavi, Gokul, Subramania1 aRobertson, Niall1 aRossi, Matteo1 aRydlichowski, Piotr1 aRyu, Hoon1 aSamsonidze, Georgy1 aSato, Mitsuhisa1 aSaurabh, Nishant1 aSharma, Vidushi1 aSharma, Kunal1 aShin, Soyoung1 aSlessman, George1 aSteiner, Mathias1 aSitdikov, Iskandar1 aSuh, In-Saeng1 aSwitzer, Eric1 aTang, Wei1 aThompson, Joel1 aTodo, Synge1 aTran, Minh1 aTrenev, Dimitar1 aTrott, Christian1 aTseng, Huan-Hsin1 aTureci, Esin1 aValinas, David, García1 aVallecorsa, Sofia1 aWever, Christopher1 aWojciechowski, Konrad1 aWu, Xiaodi1 aYoo, Shinjae1 aYoshioka, Nobuyuki1 aYu, Victor, Wen-zhe1 aYunoki, Seiji1 aZhuk, Sergiy1 aZubarev, Dmitry uhttps://arxiv.org/abs/2312.0973301493nas a2200193 4500008004100000245007800041210006900119260001400188490000600202520090100208100002201109700001401131700002101145700002401166700002301190700002401213700002501237856003701262 2020 eng d00aEntanglement Bounds on the Performance of Quantum Computing Architectures0 aEntanglement Bounds on the Performance of Quantum Computing Arch c9/22/20200 v23 aThere are many possible architectures for future quantum computers that designers will need to choose between. However, the process of evaluating a particular connectivity graph's performance as a quantum architecture can be difficult. In this paper, we establish a connection between a quantity known as the isoperimetric number and a lower bound on the time required to create highly entangled states. The metric we propose counts resources based on the use of two-qubit unitary operations, while allowing for arbitrarily fast measurements and classical feedback. We describe how these results can be applied to the evaluation of the hierarchical architecture proposed in Phys. Rev. A 98, 062328 (2018). We also show that the time-complexity bound we place on the creation of highly-entangled states can be saturated up to a multiplicative factor logarithmic in the number of qubits.
1 aEldredge, Zachary1 aZhou, Leo1 aBapat, Aniruddha1 aGarrison, James, R.1 aDeshpande, Abhinav1 aChong, Frederic, T.1 aGorshkov, Alexey, V. uhttps://arxiv.org/abs/1908.0480201947nas a2200397 4500008004100000245005400041210005400095260001500149520085000164100001801014700001601032700002301048700002301071700002201094700002401116700001901140700001801159700001801177700002001195700002501215700001801240700001801258700001901276700001901295700001601314700002301330700001901353700001701372700002401389700001901413700002201432700001901454700001901473700002001492856003701512 2019 eng d00aQuantum Computer Systems for Scientific Discovery0 aQuantum Computer Systems for Scientific Discovery c12/16/20193 aThe 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.
1 aAlexeev, Yuri1 aBacon, Dave1 aBrown, Kenneth, R.1 aCalderbank, Robert1 aCarr, Lincoln, D.1 aChong, Frederic, T.1 aDeMarco, Brian1 aEnglund, Dirk1 aFarhi, Edward1 aFefferman, Bill1 aGorshkov, Alexey, V.1 aHouck, Andrew1 aKim, Jungsang1 aKimmel, Shelby1 aLange, Michael1 aLloyd, Seth1 aLukin, Mikhail, D.1 aMaslov, Dmitri1 aMaunz, Peter1 aMonroe, Christopher1 aPreskill, John1 aRoetteler, Martin1 aSavage, Martin1 aThompson, Jeff1 aVazirani, Umesh uhttps://arxiv.org/abs/1912.0757701556nas a2200157 4500008004100000245006300041210006300104520105500167100002101222700002201243700002401265700002301289700002401312700002501336856003701361 2018 eng d00aUnitary Entanglement Construction in Hierarchical Networks0 aUnitary Entanglement Construction in Hierarchical Networks3 aThe construction of large-scale quantum computers will require modular architectures that allow physical resources to be localized in easy-to-manage packages. In this work, we examine the impact of different graph structures on the preparation of entangled states. We begin by explaining a formal framework, the hierarchical product, in which modular graphs can be easily constructed. This framework naturally leads us to suggest a class of graphs, which we dub hierarchies. We argue that such graphs have favorable properties for quantum information processing, such as a small diameter and small total edge weight, and use the concept of Pareto efficiency to identify promising quantum graph architectures. We present numerical and analytical results on the speed at which large entangled states can be created on nearest-neighbor grids and hierarchy graphs. We also present a scheme for performing circuit placement--the translation from circuit diagrams to machine qubits--on quantum systems whose connectivity is described by hierarchies.
1 aBapat, Aniruddha1 aEldredge, Zachary1 aGarrison, James, R.1 aDesphande, Abhinav1 aChong, Frederic, T.1 aGorshkov, Alexey, V. uhttps://arxiv.org/abs/1808.07876