In order to evaluate, validate, and refine the design of new quantum algorithms or quantum computers, researchers and developers need methods to assess their correctness and fidelity. This requires the capabilities of quantum circuit simulations. However, the number of quantum state amplitudes increases exponentially with the number of qubits, leading to the exponential growth of the memory requirement for the simulations. In this work, we present our memory-efficient quantum circuit simulation by using lossy data compression. Our empirical data shows that we reduce the memory requirement to 16.5% and 2.24E-06 of the original requirement for QFT and Grover's search, respectively. This finding further suggests that we can simulate deep quantum circuits up to 63 qubits with 0.8 petabytes memory.
@article{arxiv.1811.05630,
title = {Memory-Efficient Quantum Circuit Simulation by Using Lossy Data Compression},
author = {Xin-Chuan Wu and Sheng Di and Franck Cappello and Hal Finkel and Yuri Alexeev and Frederic T. Chong},
journal= {arXiv preprint arXiv:1811.05630},
year = {2018}
}
Comments
2 pages, 2 figures. The 3rd International Workshop on Post-Moore Era Supercomputing (PMES)