IQC Lab - Qiskit, QFT, QPE and beyond!

The following repository is intended to store all the materials required to fully implement the QFT (Quantum Fourier Transform) and the QPE (Quantum Phase Estimation) algorithms.

Our simulator of choice is Qiskit, since it provides a great API and easy-to-use features.

Authors

This lecture was kindly brought to you by:

Cătălin-Alexandru RÎPANU (@CatalinACS);
Valentin-Ioan VINTILĂ (@w1bb).

All the resources were created entirely by us or were properly credited in the subsection below.

A quick history lesson

According to JustPaste.it, Qiskit has a rich history of development and evolution that can be traced back to 2017's IBM first release. Back then, the simulator was nothing more than a Python library based on the matrix product state (MPS) and the time-evolving block decimation method (TEBD).

In 2018, IBM introduces noisy quantum circuits using the quantum process tomography (QPT) technique. This allowed for realistic simulations that took into account the effect of noise and errors in the real quantum hardware.

Once again, in 2019, IBM introduced a new feature, the Aer quantum simulator, a high-performance program that can simulate large-scale quantum circuits with millions of qubits and gates.

In recent years, that is in 2020, IBM made public Qiskit Runtime, which allows users to run quantum circuits on real quantum hardware using IBM's API.

Environment setup

While a detailed overview of the installation is provided by Qiskit themselves, we've outlined the most important steps in this subsection. Please follow the tutorial that is right for your platform.

Windows

First, install Python 3 by clicking on the yellow "Download Python 3.X.X" button and following the wizard's instructions. Once that is done, you can check that both Python and its package manager, PiP, were properly installed. To do this, open up a command prompt and type:

python --version
pip3 --version

You should not get an error. If everything went alright, open up a command prompt with administrator rights (Start -> search for CMD -> right click -> Run as administrator) and type in:

pip3 install jupyter jupyterlab qiskit[visualization]

This command will automatically install everything we need in order to correctly run Qiskit inside a Jupyter lab environment.

You can now move on to the next section.

Linux

Install Python, PiP, Jupyter and VSCode. For Ubuntu, you can type in the following in a terminal window:

sudo apt update
sudo apt install python3 python3-pip
pip install jupyter jupyterlab qiskit[visualization]

Alternatively, Arch provides a different method:

sudo pacman -Syu
sudo pacman -S python python-pip
pip install jupyter jupyterlab qiskit[visualization]

If you are a ZSH user, you should place qiskit[visualization] in single quotes, as in pip install jupyter jupyterlab 'qiskit[visualization]'.

Running the lab

To get started, you should clone/download this repository, open up a command line/terminal, navigate to the parent folder and run jupyter-lab. In case something goes wrong and an error pops up, you might need to first log out and log back in before continuing; on Linux, you can skip this step by simply running ~/.local/bin/jupyter-lab instead.

A browser should get launched alongside a locally hosted server. In the left panel, please navigate to the folder in which you have downloaded/cloned this repository. Now click on the lab-QFT.ipynb to load it and follow the instructions provided in that notebook.

If, at any point, you get a little stuck, ask for help and/or take a look at the proposed solution (see lab-QFT-solution.ipynb). Once you are done with that notebook, you can move on to lab-QPE.ipynb.