Technical requirements

A companion Jupyter notebook for this chapter can be downloaded from GitHub at https://github.com/PacktPublishing/Quantum-Chemistry-and-Computing-for-the-Curious, which has been tested in the Google Colab environment, which is free and runs entirely in the cloud, and in the IBM Quantum Lab environment. Please refer to Appendix B – Leveraging Jupyter Notebooks in the Cloud, for more information. The companion Jupyter notebook automatically installs the following list of libraries:

• Numerical Python (NumPy) [NumPy], an open-source Python library that is used in almost every field of science and engineering
• SymPy, [SymPy] a Python library for symbolic mathematics
• Qiskit [Qiskit], an open-source SDK for working with quantum computers at the level of pulses, circuits, and application modules
• Qiskit visualization support to enable the use of its visualization functionality and Jupyter notebooks

Install NumPy using the following command:

pip install numpy

Install SymPy using the following command:

pip install sympy

Install Qiskit using the following command:

pip install qiskit

Install Qiskit visualization support using the following command:

pip install 'qiskit[visualization]'

Import math libraries using the following commands:

import cmath
import math