Chapter 2: Quantum Computing and Qubits with Python

Quantum computing is a fairly new and fairly old field at the same time. The ideas and concepts used to achieve quantum computing (such as quantum mechanical superposition and entanglement) have been around for almost a century and the field of quantum information science was founded almost 40 years ago. Early explorers, such as Peter Shor and Lov Grover, produced quantum computing algorithms (Shor's algorithm and Grover's algorithm) that are now starting to become as well known as foundational physics concepts such as E=mc2. For details, see the references at the end of the chapter.

At the same time, real quantum computers that utilize these effects are a relatively recent invention. The requirements for building one were outlined by DiVincenzo in the 1990, and IBM opened up its IBM Quantum Experience® and Qiskit® in 2016, effectively the first time anyone outside of a research lab could start exploring this nascent field for real.

So, what is the difference between classical computing and quantum computing? One way to start exploring is by taking a look at the basic computational elements used by each—the classical bits and the quantum qubits.

In this chapter, we will contrast bits and qubits, play with some generic linear algebra to explore them in more detail, and contrast deterministic (classical) computation and probabilistic (quantum) computation. We will even take a quick look at some basic Qiskit® presentation methods to visualize a qubit.

In this chapter, we will cover the following recipes:

• Comparing a bit and a qubit
• Visualizing a qubit in Python
• A quick introduction to quantum gates