Navigate to main.py and input the key to your IBM Quantum account.
Run main.py and visualize Quantum Error Correction on a Quantum Computer!
This repository includes an exploration of various algorithms and techniques relevant to quantum computing, including quantum machine learning (QML), Shor's algorithm, and variational quantum eigensolvers (VQEs).
See Tutorials for Colab notebooks with these explorations.
We implement a Quantum Error Correction (QEC) algorithm to mitigate the noise associated with an increasing number of quantum gates in a circuit. QEC is a prerequisite to successfully implementing quantum computing at scale in order to solve the world's most complex problems.
Even for a small number of CNOT gates, the accuracy of a quantum circuit can plummet very quickly as shown in the figure below.
The following are some example quantum circuits. It is evident that even these simple circuits utilize several controlled gates, which are arguably the crux of quantum computing itself.
Our QEC algorithm successfully reduces the noise of several quantum circuits tested, which can enable quantum computing to be applied to encryption, machine learning, simulations, and more. Example results are shown below.
Please feel free to contact the authors with any questions.