Logical abstractions for noisy variational Quantum algorithm simulation

Yipeng Huang, Steven Holtzen, Todd Millstein, Guy Van Den Broeck, Margaret Martonosi

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

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 66× reduction in sampling cost versus quantum circuit simulation techniques based on tensor network contraction.

Original languageEnglish (US)
Title of host publicationProceedings of the 26th ACM International Conference on Architectural Support for Programming Languages and Operating Systems, ASPLOS 2021
PublisherAssociation for Computing Machinery
Pages456-472
Number of pages17
ISBN (Electronic)9781450383172
DOIs
StatePublished - Apr 19 2021
Event26th ACM International Conference on Architectural Support for Programming Languages and Operating Systems, ASPLOS 2021 - Virtual, Online, United States
Duration: Apr 19 2021Apr 23 2021

Publication series

NameInternational Conference on Architectural Support for Programming Languages and Operating Systems - ASPLOS

Conference

Conference26th ACM International Conference on Architectural Support for Programming Languages and Operating Systems, ASPLOS 2021
Country/TerritoryUnited States
CityVirtual, Online
Period4/19/214/23/21

All Science Journal Classification (ASJC) codes

  • Software
  • Information Systems
  • Hardware and Architecture

Keywords

  • Bayesian networks
  • conjunctive normal form
  • exact inference
  • knowledge compilation
  • quantum circuits
  • simulation

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