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.
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Full State Quantum Circuit Simulation by Using Lossy Data Compression
In order to evaluate, validate, and refine the design of a new quantum algorithm or a quantum computer, researchers and developers need methods to assess their correctness and fidelity. This requires the capabilities of simulation for full quantum state amplitudes. However, the number of quantum state amplitudes increases exponentially with the number of qubits, leading to the exponential growth of the memory requirement. In this work, we present our technique to simulate more qubits than previously reported by using lossy data compression. Our empirical data suggests that we can simulate full state quantum circuits up to 63 qubits with 0.8 petabytes memory.
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- Award ID(s):
- 1730449
- NSF-PAR ID:
- 10084837
- Date Published:
- Journal Name:
- IEEE/ACM 29th The International Conference for High Performance computing, Networking, Storage and Analysis (SC2018)
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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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.more » « less
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Accepted Manuscript1.0
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