Logical Abstractions for Noisy Variational Quantum Algorithm Simulation
26th International Conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS 2021), April 12-23, 2021.
IEEE Micro Top Picks Honorable Mention
Yipeng Huang, Steven Holtzen, Todd Millstein, Guy Van den Broeck, Margaret Martonosi
Due to the unreliability and limited capacity of existing quantum
computer prototypes, quantum circuit simulation continues to be a
vital tool for validating next generation quantum computers and
for studying variational quantum algorithms, which are among
the leading candidates for useful quantum computation. Existing
quantum circuit simulators do not address the common traits of
variational algorithms, namely: 1) their ability to work with noisy
qubits and operations, 2) their repeated execution of the same
circuits but with different parameters, and 3) the fact that they sample
from circuit final wavefunctions to drive a classical optimization
routine. We present a quantum circuit simulation toolchain based
on logical abstractions targeted for simulating variational algorithms.
Our proposed toolchain encodes quantum amplitudes and
noise probabilities in a probabilistic graphical model, and it
compiles the circuits to logical formulas that support efficient repeated
simulation of and sampling from quantum circuits for different
parameters. Compared to state-of-the-art state vector and density
matrix quantum circuit simulators, our simulation approach offers
greater performance when sampling from noisy circuits with at
least eight to 20 qubits and with around 12 operations on each
qubit, making the approach ideal for simulating near-term variational quantum algorithms. And for simulating noise-free shallow
quantum circuits with 32 qubits, our simulation approach offers a
66x reduction in sampling cost versus quantum circuit simulation
techniques based on tensor network contraction.
[PDF]