As introduced in the previous articles, gates can be considered as operations on qubits that change their state from one to another. Since we represent our qubit states as vectors, we can consider quantum gates as matrices that can transform the vectors. Since quantum theory is unitary, quantum gates are represented as unitary matrices. Another way to understand gate operations is to think of them as rotations around the block sphere.

Any normalized pure state can be written in the following form:

The previous articles on Linear Algebra might have been a bit boring to at least some of you, especially since it was covering topics from various parts of Quantum mechanics and computing. Time to put it all into a form that finally makes some sense. And good news for all the programmers out there, we will finally get to code in this article. So let’s get the party started.

Remember the 2 qubit states, |0⟩ and |1⟩, that we had introduced in Linear Algebra Part 1. For the forgetful ones, they were introduced as bases (singular — basis), more specifically…

The primary objective of this article is to get you familiarised with the basics of Linear Algebra to have a better understanding of how qubits behave. Covering all the concepts of Linear Algebra is beyond the scope of this article, so we would limit our discussion to the key concepts necessary to get started with quantum computing.

Let’s start by exploring vectors. As most of you might have learned in high school, a vector may be defined as a physical quantity that has both magnitude and direction. …

Right now, as you are staring into your laptop or any other digital device, do you realize that there are millions of bits playing their own part in conveying the information to you? If you are intrigued by this fact, gear up because you are in for a treat.

Let me start off by quoting the words of Jasper Sitwell from Captain America: The Winter Soldier,

The 21st century is a digital book.

Sure, it is. Everything now is stored digitally. Morover, the millennium has witnessed the emergence of several mind-bending fields especially in the IT industry. …

For all those amateur Machine Learning and Deep Learning enthusiasts out there, Linear Regression is just the right way to kick start your journey. If you are new to Machine Learning with some background in PyTorch, then buckle up because you have just ended up at the right spot. In case you are not, don’t worry, checkout my previous article to pick up some fundamentals of PyTorch and then you are all good to go.

Linear Regression is a linear model that predicts the output, given a set of input variables, assuming that there is a linear relationship between the…

Deep Learning and Artificial Intelligence have been one of the hottest topics of 21st century. While there are many out there like TensorFlow, PyTorch has always stood out as one of the best open source machine learning framework for research prototyping. To put it formally, PyTorch is a scientific computing framework with wide support for machine learning algorithms that put GPUs first. It was primarily developed by Facebook’s artificial intelligence research group.

If you are new to PyTorch, this is the prefect blog for you to get started (provided you have a basic understanding of Python) as we will cover…

Artificial Intelligence | Machine learning | Quantum Computing