Variational quantum algorithms

Cambridge University Press eBooks, pp. 281–285

Abstract

This chapter covers variational quantum algorithms, which act as a primitive ingredient for larger quantum algorithms in several application areas, including quantum chemistry, combinatorial optimization, and machine learning. Variational quantum algorithms are parameterized quantum circuits where the parameters are trained to optimize a certain cost function. They are often shallow circuits, which potentially makes them suitable for near-term devices that are not error corrected.

Authors 4

1. Sam McArdle
   Affiliation as printed

   AWS Center for Quantum Computing

2. Connor T. Hann
   Affiliation as printed

   AWS Center for Quantum Computing

3. Aleksander Kubica

   Yale University

   Affiliation as printed

   Yale University

4. Fernando G. S. L. Brandão
   Affiliation as printed

   AWS Center for Quantum Computing