In part 1, we managed to solve the first two exercises. We did this quickly and had momentum going. Now, let’s get into the solutions for the next two exercises: quantum error correction and transmon qubits.

After a rather easy time with the first two exercises, I arrived at quantum error correction. A few weeks ago, I had attended a couple of lectures on surface code, so I felt confident when I saw that was the theme of this challenge.

The purpose of quantum error correction is to detect and correct errors introduced during the execution of a circuit. Overall…

One of the biggest quantum computing events of the year — the IBM Quantum Challenge — for this year just ended. This year’s challenges offer everyone interested in quantum computing an opportunity to learn about quantum algorithms, hardware, and more! All this while taking you in a trip along the timeline of quantum computing, starting all the way back in 1980 with the Toffoli gate and finishing at the recently developed Variational Quantum Eigensolver in 2014.

After a bit over a year of getting into quantum computing, this challenge was a great opportunity to test what I’ve learned in that…

This is the second article of our series talking about the fundamentals of linear algebra and everything you need to know about it in order to work with it in Quantum Computing. You can find the first article, which talks about vectors and scalars, here.

Okay, now that we have a solid understanding of what vectors and scalars are, we can begin to explore matrices. While they have a great variety of functions and applications throughout linear algebra, for our purposes in quantum computing, matrices can be purely thought of as operations acting on vectors.

Let’s look at a simple…

It’s no secret that linear algebra is what allows us to represent quantum computing in a much more intuitive way, abstracting some concepts of quantum mechanics that are to complicated to work with for the purpose of quantum algorithms. Because of this, it is important to have a clear understanding of the basic concepts of linear algebra and to know how to work with them.

We, Quantum Untangled, are going to give you an overview of the concepts of linear algebra that are used in quantum computing through a series of articles, this being the first article from this series…

Teleportation may seem as a concept only existent in the world of science fiction — at least for those who are not yet familiar with the concepts of quantum physics and quantum computing. It’s pretty crazy to hear about the teleportation of quantum information the first time. Specially since it involves the instantaneous transfer of quantum data, and I’m pretty sure instantaneous is faster than the speed of light, since entanglement works no matter how far apart the two qubits are.

But isn’t this against the rules of relativity that govern our universe? Supposedly, no object can be affected by…

Quantum computing is full of clever tricks that help us solve problems that would take us years to solve with purely classical computing. These tricks usually involve a relatively small circuit that performs a specific task inside a much bigger algorithm. In fact, quantum computing is all about learning how to take advantage of the strange tricks that inhabit quantum mechanics to solve problems through computation. You may have heard about some of these tricks, such as entanglement and superposition. There are many more, and among them you will find phase kickback.

Phase kickback is a very common and useful…