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arXiv · 1907.11217

Alibaba Cloud Quantum Development Platform: Large-Scale Classical Simulation of Quantum Circuits

Fang Zhang·Cupjin Huang·Michael Newman·Junjie Cai·Huanjun Yu·Zhengxiong Tian·Bo Yuan·Haihong Xu·Junyin Wu·Xun Gao·Jianxin Chen·Mario Szegedy·Yaoyun Shi
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Abstract

We report, in a sequence of notes, our work on the Alibaba Cloud Quantum Development Platform(AC-QDP). AC-QDP provides a set of tools for aiding the development of both quantum computing algorithms and quantum processors, and is powered by a large-scale classical simulator deployed on Alibaba Cloud. In this note, we report the computational experiments demonstrating the classical simulation capability of AC-QDP. We use as a benchmark the random quantum circuits designed for Google's Bristlecone QPU {\cite{GRCS}}. We simulate Bristlecone-70 circuits with depth $1 + 32 + 1$ in $0.43$ second per amplitude, using $1449$ Alibaba Cloud Elastic Computing Service (ECS) instances, each with $88$ Intel Xeon(Skylake) Platinum 8163 vCPU cores @ 2.5 GHz and $160$ gigabytes of memory. By comparison, the previously best reported results for the same tasks are $104$ and $135$ seconds, using NASA's HPC Pleiades and Electra systems, respectively ({arXiv:1811.09599}). Furthermore, we report simulations of Bristlecone-70 with depth $1+36+1$ and depth $1+40+1$ in $5.6$ and $580.7$ seconds per amplitude, respectively. To the best of our knowledge, these are the first successful simulations of instances at these depths.

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Fang Zhang, Cupjin Huang, Michael Newman, Junjie Cai, Huanjun Yu, Zhengxiong Tian, Bo Yuan, Haihong Xu, Junyin Wu, Xun Gao, Jianxin Chen, Mario Szegedy, Yaoyun Shi. 2019-07-25. Alibaba Cloud Quantum Development Platform: Large-Scale Classical Simulation of Quantum Circuits. https://arxiv.org/abs/1907.11217

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