🔴 Using a Mobile Simulator to Learn Quantum Computing
Professor Aleksandar Radovanovic of the University of the Western Cape has published the following book as a resource for learning the fundamentals of quantum computing:
Quantum Computing: Problems and Solutions—Exercises with Detailed Solutions for Students and Educators (October 2025)
Qiskit code is available for 23 of the book’s key exercises and can be run using IBM’s Qiskit simulator. I have confirmed that many of these exercises can also be run on the mobile quantum circuit simulator I developed. Although support for some of them is still a work in progress, I would like to introduce one example here. The images below show the book and the mobile simulator.
🔴 Running an Exercise on the Mobile Quantum Circuit Simulator
Let us take a look at an example. The image on the left below shows some brief documentation. From the list of exercises on the right, I selected “Lab 13—Grover Search Algorithm.”
The image on the left below shows the quantum circuit description for Grover’s search algorithm, the corresponding circuit diagram, and an example run. The circuit description can, of course, be edited.
The image on the right shows the result after running only the first Oracle–Diffusion iteration. Even at this stage, the result suggests that the target state, “1101,” can already be found with high probability.
🔴 Why Use a Mobile Simulator?
As noted above, all these exercises can be run successfully using IBM’s Qiskit simulator. My simulator, however, offers a different kind of value: you can take your mobile device out of your pocket and start using it anytime and anywhere, without an internet connection or any environment setup.
I believe that being able to read the textbook and immediately test its concepts on a mobile device makes quantum computing more approachable and helps deepen the reader’s understanding.
At the same time, a mobile simulator of this kind has its limitations. My simulator performs one shot per button press, so it is not well suited to collecting statistics from a large number of measurement shots. However, because it theoretically calculates the probabilities of all computational basis states, this is unlikely to be a serious limitation in most cases.
The simulator also cannot integrate with classical optimization modules, which are required for applications such as quantum machine learning. For those tasks, platforms such as IBM Qiskit are the better choice.
Reference
I have included the logo of the Africa Quantum Consortium because I find its design especially beautiful.



