Introduction

Cellular Neural Networks (CelNN) are among a dozen candidates for quantum Neural Network architectures. This project is constructing an elementary cell of (CelNN) in an IBM physical quantum computer.

CellNN has high locality and cell functions that can use low amount of qubits, which may enable them in a Noise-Intermediate State Quantum (NISQ) device.

CelNN are among a dozen candidates for quantum NN.

Objectives

The principal objective is to design, construct and evaluate an elementary cell of Cellular Neural Networks (CelNN) in an IBM physical quantum computer. An elementary cell works as a Full Adder in a digital computers.

First this project investigates the performance of a NISQ for Adder, evaluating the use of qbits, its robustness to noise according to some of the quantum device architectures available.

Applications

The current application (a Python notebook) enables you to run an Digital Adder (the fundamental circuit for the calculus in a conventional digital computer) in a physical quantum device and evaluate its performance in terms of accuracy, runtime and robustness to noise.

Next step is a similar notebook for testing an elementary quantum cell for a CelNN.