Applications of Quantum Annealing in Statistics

TL;DR

This paper explores the potential of quantum annealing, using D-Wave quantum computers, for statistical tasks like maximum likelihood estimation, experimental design, and matrix inversion, highlighting current limitations and future promise.

Contribution

It provides a comprehensive overview of applying quantum annealing to statistical problems and discusses technical challenges and future prospects.

Findings

Quantum annealing can perform statistical tasks but is not yet superior to classical methods.

Current quantum hardware faces technical limitations.

Future developments may enhance quantum computing's role in statistics.

Abstract

Quantum computation offers exciting new possibilities for statistics. This paper explores the use of the D-Wave machine, a specialized type of quantum computer, which performs quantum annealing. A general description of quantum annealing through the use of the D-Wave is given, along with technical issues to be encountered. Quantum annealing is used to perform maximum likelihood estimation, generate an experimental design, and perform matrix inversion. Though the results show that quantum computing is still at an early stage which is not yet superior to classical computation, there is promise for quantum computation in the future.