This January (2021), scientists established the world’s first integrated quantum communication network, spanning 4600 kilometers (2860 miles) across China. A communication network is a process or system enabling the transfer of information; examples include wireless, the Internet, and telephone communication. Tools such as cell phones, computers, and cell towers are elements of these systems. Current mainstream communication networks transmit information using electrical signals distributed over wires (or radio signals). For example, the network of phone wires across the world is a communication network. Quantum communication networks employ photons, or the particles of light, to create a decentralized and “UNHACKABLE” system…


Now that you’ve started learning the physics behind quantum computing, you might be wondering: “Hey, to actually use a quantum computer, do you really have to build quantum devices by hand?” And the answer is, well, there is a reason why quantum computers are called computers: they’re programmable!

In this series, we will be learning to build software to simulate the math concepts and to run on quantum computers. We will be using Python to write our code since it’s a clean, modern, and library-rich language. …


In the last post about “Linear Algebra for QC”, we explored the important concepts surrounding eigenvectors and eigenvalues. This post is dedicated to understanding the tensor product and finally see its application in Quantum Computing. Let’s get started!

The Tensor Product

This article revolves around how we look at things when quantum systems go beyond a single element. Before starting with the intuition behind tensor products, let us take a small mathematical detour and have a quick look at things called bases. The readers comfortable with vector spaces and basis vectors, feel free to skip ahead but in my opinion, recapitulation always helps!

Basis Vectors

If you have followed our Linear Algebra series, you may well be familiar with the concept of vectors, scalars and matrices. Let us also look at what a vector space is and what constitutes a basis.

Simply put…


A simple, illustrative guide to Simon’s Algorithm, including the problem, classical solutions, and the quantum advantage gained with the quantum solution.

Photo by Amos via Unsplash

This is the first half of a two-part guide to Simon’s Algorithm. The second half, which you’ll soon be able to read here on Quantum Untangled, goes through technical details, including the mathematics and implementation of the circuit using IBM’s Qiskit.

Introduction

Simon’s Algorithm is one that’s often overlooked in quantum resources, unjustly so. While it lacks the beautifully simple execution of The Deutsch-Jozsa Algorithm, or the incredible versatility and usefulness of Grover’s Algorithm, Simon’s Algorithm acts as the precursor…


Welcome to the second part of the series — the “hidden variable” interpretation of quantum mechanics! Einstein and Bell can be considered as the founding fathers of this theory.

The hidden variable interpretation actually came into being as a criticism of Copenhagen interpretation, which you can read about here. This is yet another way to describe the weirdness of quantum mechanics we’ve been going over.

Image: ©slideplayer.com

Main Idea

The central idea of the hidden variable theorem was based on the EPR paradox, which essentially argued that the current theory of QM was incomplete. According to this interpretation, it is believed that quantum theory…


Image: © Quanta Magazine

In the last month, we looked at some key phenomena of the Quantum world- namely, superposition, spin, and measurement. Here, we look at the last key concept necessary for sailing in the quantum world- entanglement. This has been a topic that has drawn questions and skepticism from a whole generation of physicists, most profoundly, Albert Einstein, who summed up his skepticism, calling entanglement “the spooky-action-at-a-distance”. So, naturally, don’t get down on yourself if it doesn’t make sense the first time around.

Let’s now jump into entanglement. As usual, we’ll start with the formal definition of entanglement, go word-by-word, and then…


Image: © Quanta Magazine

All through the previous articles in this series, we have been slowly and gradually building upon the idea of measurement: whether it be localization, or whether it be spin effects! Indeed, measurement is such a difficult concept to grasp that it confuses the brightest of minds (including Einstein, who said on the probabilistic effects of measurement, “God does not play dice!”). It’s this concept in physics, which beginners find most difficult and astonishing to digest. …


Background

The quantum computer is a fascinating machine that uses quantum phenomena like superposition and entanglement to provide a superior advantage in computation when compared to a classical computer.

The quantum computing model was first proposed in the early 1980s by Paul Benioff. However, the first wave of quantum popularity didn’t start until 1994 when Peter Shor developed Shor’s factoring algorithm. The past recent years saw the realization of “quantum supremacy” in Google Sycamore’s experiment, in which a quantum processor simulates the equivalence of 10,000 years of classical supercomputers in 200 seconds.

But what exactly is the “quantum advantage”, and how…


Image: © Physics World

Perhaps the most confusing topic which beginners get stuck on, is spin. What one understands by spin obviously depends upon his/her size of reference and of course, his/her intuition! Considering the first fact, the word ‘spin’ generates a wildfire of ideas in the mind of a beginner. What a person would imagine at first when he hears about the word ‘spin’ would of course be none other than a top spinning about its axis, or, the Earth spinning about its axis, going about its ‘day’ly business! …


In the last post for the Math for Quantum Computing series we talked about matrices and some of their operations. Now is the time to discuss a very important concept related to matrices i.e. eigenvectors — Let’s get started

This is the third article in the series Linear Algebra for Quantum Computing and everything you would need in order to get yourself started in the field. This article assumes that you are familiar with the key concepts of vectors and matrices and builds new concepts on top of them. You may find the previous articles in our series useful to brush upon your knowledge of the same here

In the previous posts we explored some very powerful mathematical representations of real world entities modeled by vectors and matrices. …

Quantum Untangled

Untangling the mysteries that surround quantum computing.

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