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Amplitude-Aware Lossy Compression for Quantum Circuit Simulation

Quantum Physics 2018-11-16 v3 Emerging Technologies

Abstract

Classical simulation of quantum circuits is crucial for evaluating and validating the design of new quantum algorithms. 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 paper, we present a new data reduction technique to reduce the memory requirement of quantum circuit simulations. We apply our amplitude-aware lossy compression technique to the quantum state amplitude vector to trade the computation time and fidelity for memory space. The experimental results show that our simulator only needs 1/16 of the original memory requirement to simulate Quantum Fourier Transform circuits with 99.95% fidelity. The reduction amount of memory requirement suggests that we could increase 4 qubits in the quantum circuit simulation comparing to the simulation without our technique. Additionally, for some specific circuits, like Grover's search, we could increase the simulation size by 18 qubits.

Keywords

Cite

@article{arxiv.1811.05140,
  title  = {Amplitude-Aware Lossy Compression for Quantum Circuit Simulation},
  author = {Xin-Chuan Wu and Sheng Di and Franck Cappello and Hal Finkel and Yuri Alexeev and Frederic T. Chong},
  journal= {arXiv preprint arXiv:1811.05140},
  year   = {2018}
}

Comments

6pages, 6 figures. The 4th International Workshop on Data Reduction for Big Scientific Data (DRBSD-4)

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