Find Paper, Faster
Example:10.1021/acsami.1c06204 or Chem. Rev., 2007, 107, 2411-2502
Automatic design of quantum feature maps
Quantum Science and Technology  (IF5.994),  Pub Date : 2021-08-25, DOI: 10.1088/2058-9565/ac1ab1
Sergio Altares-Lpez, Angela Ribeiro, Juan Jos Garca-Ripoll

We propose a new technique for the automatic generation of optimal ad-hoc anstze for classification by using quantum support vector machine. This efficient method is based on non-sorted genetic algorithm II multiobjective genetic algorithms which allow both maximize the accuracy and minimize the ansatz size. It is demonstrated the validity of the technique by a practical example with a non-linear dataset, interpreting the resulting circuit and its outputs. We also show other application fields of the technique that reinforce the validity of the method, and a comparison with classical classifiers in order to understand the advantages of using quantum machine learning.