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