Creating a quantum version of the classic Magic 8 Ball using PyQuil and Rigetti’s quantum computing framework offers a playful yet insightful way to explore quantum programming. This project can be an engaging introduction to quantum computing concepts, particularly for those interested in practical applications of quantum randomness.
Exploring Quantum Randomness
Introduction to PyQuil
PyQuil is a Python library for quantum programming developed by Rigetti Computing. It provides a convenient and powerful interface for writing and executing quantum algorithms on quantum simulators and quantum processors (quantum hardware). PyQuil is part of the broader quantum software stack provided by Rigetti, designed to facilitate the development of quantum applications.
Introduction to Quantum Computing
Quantum computing is an area focused on developing computer technology based on the principles of quantum theory, which explains the nature and behavior of energy and matter at the quantum (atomic and subatomic) level. This field represents a fundamental shift from classical computing, introducing new concepts and approaches to processing information.
This example highlights in a simple way how we can employ and deploy the Quantum Simulation Code from Rigetti to have some fun and create a magic eight ball. You might seen them; there is a photo below; it’s a sphere that resembles the black eight ball in the pool. Shaking the ball randomizes and highlights one of the surfaces (typically 8) with some text. The use case is to crack the stalemate when making decisions. Here, we will use the quantum equivalent of shaking to perform the randomization. You can pull the code from GitHub at github
How the Quantum Code works
Create several qubits; the exact number of qubits will depend on the number of options. The code takes advantage of the Quantum superposition, meaning we cannot know what state a qubit is in until we measure it. We have two possible measurement results for each qubit.
Quantum Random Number Generators
Quantum Random Number Generators (QRNGs) represent a significant advancement in the field of cryptography and secure communications, leveraging the inherent unpredictability of quantum mechanics to generate truly random numbers.
What are Qubits?
A qubit is somewhat akin to the quantum equivalent of a bit, but it can exist in a mixed state, a superposition of two states. Thus, we put a series of qubits into a superposition that, according to the Born rule, has equal probability of being in the states |0> and state |1>. We can perform this very quickly by taking an initial state |0> into a|0> + b|1> with a transformation called the Hadamard or H in the pyquil tool set.
You can create a Program with any number of qubits with the following code, but to create an empty program, you can use
p = Program()
For each qubit, we can append to p with the qubits we wish to add, in the state we want them in (i.e. transformed with a Hadamard)
for i in range(0, nQubits):
p += Program(H(i))
We can now state how we want to measure our qubits. We want to measure them all. And for that, we can use the .measure_all() and then convert our readout into an actual number that is effectively random. Note how we use the positional information and the qubit-measured state to generate an effectively random number up to N.
Running the Code
python magic8ball.py
Example Output
('Number of Qubits: ', 5)
('Number of Quantum possibilities: ', 32)
('Number of possibilities you chose: ', 20)
('Magic 8 ball response: ', 'Signs point to yes.', 9)
Summary
Learning to program a quantum computer can prove a great deal of fun. Other languages can also be used to program a quantum computer. See the article on the relative popularity of quantum computer programming languages and frameworks.