Interpretable Neural Network based Quantum Error Correction
Note: this is currently a Work In Progress blogpost.
A Note on Mathematics
The topic of Quantum Computers and Quantum Error Correction are very math heavy topics, although someone with a good understanding of linear algebra but without much knowledge on Quantum Mechanics will likely be able to follow along. If you are not familiar with this, this article may not make much sense to you. I try my best to explain these topics as well as possible without the mathematics but sometimes I do have to share some mathematics to get into the details of things.
Introduction
During my time as an undergraduate physics student at RWTH Aachen university, I came into contact with the concept of Quantum Computing. First from an experimental standpoint, implementing qubits on physical hardware and later, during my Masters degree, also at RWTH, from a more theoretical perspective.
As quickly became clear to me from both theoretical and experimental standpoints, quatum computers have great potential, altough this potential is currently hemmed by practical concerns. Current physical hardware is noisy and not ready yet for large scale computations. For this reason, people are scrambling for ways to improve physical hardware on the one hand but also to improve results of computations on existing and near-term hardware possible.
This is where the concept of Quantum Error Correction comes in. Quantum error correction is the quantum analogy to classical error correction schemes used to protect data in communications and data storage.
A Quick Mathematical Fresh-Up on Qubits
To understand Quantum Computers, one has to understand Quantum Mechanics.