Book Image

Quantum Chemistry and Computing for the Curious

By : Alex Khan, Keeper L. Sharkey, Alain Chancé
Book Image

Quantum Chemistry and Computing for the Curious

By: Alex Khan, Keeper L. Sharkey, Alain Chancé

Overview of this book

Explore quantum chemical concepts and the postulates of quantum mechanics in a modern fashion, with the intent to see how chemistry and computing intertwine. Along the way you’ll relate these concepts to quantum information theory and computation. We build a framework of computational tools that lead you through traditional computational methods and straight to the forefront of exciting opportunities. These opportunities will rely on achieving next-generation accuracy by going further than the standard approximations such as beyond Born-Oppenheimer calculations. Discover how leveraging quantum chemistry and computing is a key enabler for overcoming major challenges in the broader chemical industry. The skills that you will learn can be utilized to solve new-age business needs that specifically hinge on quantum chemistry
Table of Contents (14 chapters)
8
Chapter 8: References
9
Chapter 9:Glossary
Appendix B: Leveraging Jupyter Notebooks on the Cloud
Appendix C: Trademarks

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