Example library
Select one of the items below to learn more about some basic quantum algorithms or examine some cool Jupyter notebook examples.
Basic examples

DeutschJozsa algorithm
The DeutschJosza algorithm is a simple example of a quantum algorithm that can be used to speed up a search

Quantum full adder
In this example we show how a quantum full adder is created and how this adder acts on superposition states.

Grover's algorithm
Grover's algorithm solves the problem of an unstructured search. It is a quantum algorithm for finding the input value of an oracle function.

Repetition code
In this example we will give a simple example of quantum error correction, where we encode one logical qubit using three physical qubits. Note that the proposed encoding is not sufficient to correct all single qubit errors: this specific example only allows for correction of socalled single bitflip errors.

Quantum classification
Classification is a form of machine learning in which labels are assigned to data, often with respect to other data. Here we show a basic example of classification based on quantum algorithms.
Jupyter notebook examples

Quantum distancebased classifier (part 1)
This notebook is part 1 in a series of 3 notebooks on classification of data using quantum algorithms.

Quantum distancebased classifier (part 2)
This notebook is part 2 in a series of 3 notebooks on classification of data using quantum algorithms.

Quantum distancebased classifier (part 3)
This notebook is part 3 in a series of 3 notebooks on classification of data using quantum algorithms.

Introduction to Inspire API
Step by step explanation how to use the API and SDK.

Measurement error mitigation
For quantum devices the measurement error is significant with respect to other sources of errors. We can reduce the effect of measurement errors using measurement error mitigation.

Grover's search
This notebook explains how to perform the Grover Search algorithm on a quantum computer.

Midcircuit measurement Tools
In this notebook, we showcase different tools to improve the qubits' readout fidelity, using midcircuit measurement tools (MCMs).

Superdense coding
In this notebook, we use the Starmon5 backend in Quantum Inspire to implement the superdense coding algorithm.