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DTSTAMP:20260522T150116Z
LOCATION:D175
DTSTART;TZID=America/Chicago:20181111T165800
DTEND;TZID=America/Chicago:20181111T171400
UID:submissions.supercomputing.org_SC18_sess143_ws_drbsd112@linklings.com
SUMMARY:Amplitude-Aware Lossy Compression for Quantum Circuit Simulation
DESCRIPTION:Xin-Chuan Wu (University of Chicago); Sheng Di, Franck Cappell
 o, Hal Finkel, and Yuri Alexeev (Argonne National Laboratory); and Frederi
 c T. Chong (University of Chicago)\n\nClassical simulation of quantum circ
 uits is crucial for evaluating and validating the design of new quantum al
 gorithms. However, the number of quantum state amplitudes increases expone
 ntially with the number of qubits, leading to the exponential growth of th
 e memory requirement for the simulations. In this paper, we present a new 
 data reduction technique to reduce the memory requirement of quantum circu
 it simulations. We apply our amplitude-aware lossy compression technique t
 o the quantum state amplitude vector to trade the computation time and fid
 elity for memory space. The experimental results show that our simulator o
 nly needs 1/16 of the original memory requirement to simulate Quantum Four
 ier Transform circuits with 99.95% fidelity. The reduction amount of memor
 y requirement suggests that we could increase 4 qubits in the quantum circ
 uit simulation comparing to the simulation without our technique. Addition
 ally, for some specific circuits, like Grover's search, we could increase 
 the simulation size by 18 qubits.\n\nTag: Data Management, Hot Topics, Sci
 entific Computing\n\nRegistration Category: Workshop Reg Pass\n\n
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