QPlex

Hackathon Qiskit IBM 2019

License

MIT License

Pre-requisites

Clone or download repo

Go to the repo and use conda to create a virtual environment:

conda env create -f environment.yml

then, activate your environment

conda activate Qiskitenv

How does this work

This software is prepared to minimize functions like θ_o x + θ₁y, applying the inequality x + y ≤ β, where you can choose your θ₀, θ₁ and β

API

A function called wrapper_optimiza_f will launch the optimization process, you need to provide:

1. precision -> the number of qbits used for each variable
2. coefs_param -> A list with the coeficients of each variable
3. beta -> β for the inequality constraint

You will get a dictionary with the value of each variable

from qplex_core import *

precision = 6
coefs_param = [2, -3]
beta = 7
a = wrapper_optimiza_f(precision, coefs_param, beta)
print(a)

You will get the desired value this way

{0: 0, 1: 7}

API - REST

• URL

  http://127.0.0.1:3333/api/optimize

• Method:

  POST

• Data:

  application/json

{
  "variables": [2, -3],
  "restriction": 7,
  "precision": 6
}

• Success Response:

  Code: 200

{
  "results": {
      "x": 0,
      "y": 7
  },
  "status": "OK"
}