Book Image

Quantum Computing with Silq Programming

By : Srinjoy Ganguly, Thomas Cambier
Book Image

Quantum Computing with Silq Programming

By: Srinjoy Ganguly, Thomas Cambier

Overview of this book

Quantum computing is a growing field, with many research projects focusing on programming quantum computers in the most efficient way possible. One of the biggest challenges faced with existing languages is that they work on low-level circuit model details and are not able to represent quantum programs accurately. Developed by researchers at ETH Zurich after analyzing languages including Q# and Qiskit, Silq is a high-level programming language that can be viewed as the C++ of quantum computers! Quantum Computing with Silq Programming helps you explore Silq and its intuitive and simple syntax to enable you to describe complex tasks with less code. This book will help you get to grips with the constructs of the Silq and show you how to write quantum programs with it. You’ll learn how to use Silq to program quantum algorithms to solve existing and complex tasks. Using quantum algorithms, you’ll also gain practical experience in useful applications such as quantum error correction, cryptography, and quantum machine learning. Finally, you’ll discover how to optimize the programming of quantum computers with the simple Silq. By the end of this Silq book, you’ll have mastered the features of Silq and be able to build efficient quantum applications independently.
Table of Contents (19 chapters)
1
Section 1: Essential Background and Introduction to Quantum Computing
6
Section 2: Challenges in Quantum Programming and Silq Programming
10
Section 3: Quantum Algorithms Using Silq Programming
14
Section 4: Applications of Quantum Computing

Getting started with the phase estimation algorithm

The concept of the QFT that we have learned about in the previous sections will now help us to understand the quantum phase estimation algorithm, which utilizes the QFT as a subroutine block. The quantum phase estimation algorithm is an important algorithm as it is used in several other quantum algorithms, such as Shor's factorization algorithm and in the quantum algorithm for linear systems of equations.

Quantum phase estimation is used to estimate the phase (or eigenvalue) of an eigenvector of a unitary operator. This unitary operator can be any quantum transformation or any quantum gate as well. In a more mathematical sense, if we have the quantum state as the eigenvector of a unitary operator U with an eigenvalue of , then the phase estimation is used to estimate the value of with a high probability. The eigenvalue equation holds true for the phase estimation technique.

If we increase the number of qubits, then it...