On the impact of quantum computing technology on future developments in high-performance scientific computing

Article, Preprint English OPEN
Möller, M.; Vuik, C.;
  • Related identifiers: doi: 10.1007/s10676-017-9438-0
  • Subject: Applied mathematics | Scientific computing | Quantum computing | Computer Science - Computational Engineering, Finance, and Science | Accelerated computing | 65Y10 | Computer Science - Computers and Society | Quantum algorithms | High-performance computing | Mathematics - Numerical Analysis

<p>Quantum computing technologies have become a hot topic in academia and industry receiving much attention and financial support from all sides. Building a quantum computer that can be used practically is in itself an outstanding challenge that has become the ‘new race... View more
  • References (72)
    72 references, page 1 of 8

    Ambainis, A. (2010) Variable time amplitude amplification and a faster quantum algorithm for solving systems of linear equations. arXiv:1010.4458v2.

    American National Standards Institute (ed.). (1986). American National Standard for Information Systems Coded Character Sets 7-Bit American Standard Code for Information Interchange (7-Bit ASCII) ANSI X3.4-1986. (ANSI INCITS 4-1986 (R2002)).

    Ashby, S., Beckman, P., Chen, J., Colella, P., Collins, B., Crawford, D., Dongarra, J., Kothe, D., Lusk, R., Messina, P., Mezzacappa, T., Moin, P., Norman, M., Rosner, R., Sarkar, V., Siegel, A., Streitz, F., White, A. & Wright, M. (2010). The opportunities and challenges of exascale computing, summary report of the Advanced Scientic Computing Advisory Committee (ASCAC) Subcommittee, Fall 2010. Retrieved from https://science.energy.gov/~/media/ ascr/ascac/pdf/reports/Exascale_subcommittee_report.pdf.

    Aspuru-Guzik, A., Van Dam, W., Farhi, E., Gaitan, F., Humble, T., Jordan, S., et al. (2015). In ASCR workshop on quantum computing for science. doi:10.2172/1194404.

    Balensiefer, S., Kregor-Stickles, L., & Oskin, M. (2005). An evaluation framework and instruction set architecture for ion-trap based quantum micro-architectures. ACM SIGARCH Computer Architecture News, 33(2), 186-196. doi:10.1145/1080695.1069986.

    Bennett, C. H. (1973). Logical reversibility of computation. IBM Journal of Research and Development Archive, 17(6), 525-532. doi:10.1147/rd.176.0525.

    Bergmann, K., Borkar, S., Campbell, D., Carlson, W., Dally, W., Denneau, M., Franzon, P., Harrod, W., Hill, K., Hiller, J., Karp, S., Keckler, S., Klein, D., Lucas, R., Richards, M., Scarpelli, A., Scott, S., Snavely, A., Sterling, T., Stanley, R. & Yelick, W. K. (2008). Exascale computing study: Technology challenges in achieving exascale systems. Retrieved from http://www.sdsc. edu/~allans/Exascale_final_report.pdf.

    Berry, D.W., Childs, A.M., Ostrander, A. & Wang, G. (2017). Quantum algorithm for linear diferential equations with exponentially improved dependence on precision. arXiv:1701.03684.

    Berry, D. W. (2014). High-order quantum algorithm for solving linear diferential equations. Journal of Physics A: Mathematical and Theoretical, 47, 105301. doi:10.1088/1751-8113/47/10/105301.

    Brandl, M.F. (2017) A quantum von Neumann architecture for largescale quantum computing in systems with long coherence times, such as trapped ions. arXiv:1702.02583.

  • Related Research Results (1)
  • Metrics
Share - Bookmark