Abstract
Quantum computers promise to perform certain computations exponentially faster than any classical device. Precise control over their physical implementation and proper shielding from unwanted interactions with the environment become more difficult as the space/time volume of the computation grows. Code optimization is thus crucial in order to reduce resource requirements to the greatest extent possible. Besides manual optimization, previous work has adapted classical methods such as constant-folding and common subexpression elimination to the quantum domain. However, such classically-inspired methods fail to exploit certain optimization opportunities across subroutine boundaries, limiting the effectiveness of software reuse. To address this insufficiency, we introduce an optimization methodology which employs annotations that describe how subsystems are entangled in order to exploit these optimization opportunities. We formalize our approach, prove its correctness, and present benchmarks: Without any prior manual optimization, our methodology is able to reduce, e.g., the qubit requirements of a 64-bit floating-point subroutine by 34×.
Supplemental Material
- M. Amy, D. Maslov, and M. Mosca. 2014. Polynomial-Time T-Depth Optimization of Cliford+T Circuits Via Matroid Partitioning. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems 33, 10 (Oct 2014 ), 1476-1489. https://doi.org/10.1109/TCAD. 2014.2341953 Google Scholar
Cross Ref
- Matthew Amy, Dmitri Maslov, Michele Mosca, and Martin Roetteler. 2013. A meet-in-the-middle algorithm for fast synthesis of depth-optimal quantum circuits. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems 32, 6 ( 2013 ), 818-830. https://doi.org/10.1109/TCAD. 2013.2244643 Google Scholar
Digital Library
- Ryan Babbush, Dominic W Berry, Ian D Kivlichan, Annie Y Wei, Peter J Love, and Alán Aspuru-Guzik. 2016. Exponentially more precise quantum simulation of fermions in second quantization. New Journal of Physics 18, 3 ( 2016 ), 033032. https://doi.org/10.1088/ 1367-2630/18/3/033032 Google Scholar
Cross Ref
- Yunseong Nam, Neil J Ross, Yuan Su, Andrew M Childs, and Dmitri Maslov. 2018. Automated optimization of large quantum circuits with continuous parameters. npj Quantum Information 4, 1 ( 2018 ), 23. https://doi.org/10.1038/s41534-018-0072-4 Google Scholar
Cross Ref
- Michael A Nielsen and Isaac Chuang. 2010. Quantum computation and quantum information.Google Scholar
- Jennifer Paykin, Robert Rand, and Steve Zdancewic. 2017. QWIRE: a core language for quantum circuits. ACM SIGPLAN Notices 52, 1 ( 2017 ), 846-858. https://doi.org/10.1145/3093333.3009894 Google Scholar
Digital Library
- Markus Reiher, Nathan Wiebe, Krysta M. Svore, Dave Wecker, and Matthias Troyer. 2017. Elucidating reaction mechanisms on quantum computers. Proceedings of the National Academy of Sciences 114, 29 ( 2017 ), 7555-7560. https://doi.org/10. 1073/pnas.1619152114 arXiv:https://www.pnas.org/content/114/29/7555.full.pdf Google Scholar
Cross Ref
- Peter W Shor. 1994. Algorithms for quantum computation: Discrete logarithms and factoring. In Foundations of Computer Science, 1994 Proceedings., 35th Annual Symposium on. IEEE, 124-134. https://doi.org/10.1109/SFCS. 1994.365700 Google Scholar
Digital Library
- Robert S. Smith, Michael J. Curtis, and William J. Zeng. 2016. A Practical Quantum Instruction Set Architecture. arXiv preprint arXiv:1608.03355 ( 2016 ).Google Scholar
- Damian S. Steiger, Thomas Häner, and Matthias Troyer. 2018. ProjectQ: an open source software framework for quantum computing. Quantum 2 ( 2018 ), 49. https://doi.org/10.22331/q-2018-01-31-49 Google Scholar
Cross Ref
- Krysta Svore, Alan Geller, Matthias Troyer, John Azariah, Christopher Granade, Bettina Heim, Vadym Kliuchnikov, Mariia Mykhailova, Andres Paz, and Martin Roetteler. 2018. Q#: Enabling Scalable Quantum Computing and Development with a High-level DSL. In Proceedings of the Real World Domain Specific Languages Workshop 2018 (Vienna, Austria) ( RWDSL2018 ). ACM, New York, NY, USA, Article 7, 10 pages. https://doi.org/10.1145/3183895.3183901 Google Scholar
Digital Library
- Yasuhiro Takahashi, Seiichiro Tani, and Noboru Kunihiro. 2010. Quantum Addition Circuits and Unbounded Fan-out. Quantum Info. Comput. 10, 9 (Sept. 2010 ), 872-890. http://dl.acm.org/citation.cfm?id= 2011464. 2011476Google Scholar
- Mingsheng Ying. 2012. Floyd-hoare Logic for Quantum Programs. ACM Trans. Program. Lang. Syst. 33, 6, Article 19 ( Jan. 2012 ), 49 pages. https://doi.org/10.1145/2049706.2049708 Google Scholar
Digital Library
Index Terms
Assertion-based optimization of Quantum programs
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