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Quantum Simulation
Memory-Efficient Quantum Circuit Simulation by Using Lossy Data Compression
arXiv
Authors: Xin-Chuan Wu, Sheng Di, Franck Cappello, Hal Finkel, Yuri Alexeev, Frederic T. Chong
Year
2018
Paper ID
23361
Status
Preprint
Abstract Read
~2 min
Abstract Words
116
Citations
N/A
Abstract
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.
Why This Paper Matters
- This paper contributes to the Quantum Simulation research area in the Quantum Articles archive.
- It adds a 2018 reference point for readers tracking recent quantum research.
- 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...
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