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Apress eBooks

QISKit, Awesome SDK for Quantum Programming in Python

Vladimir Silva

Published Jan 1, 2018• 3 citations
Publisher

Abstract

In this chapter you will get started with the QISKit, the best SDK out there for quantum programming. You will learn how easy it is to install the SDK in your local system. But before writing your first quantum program, it is always helpful to understand what quantum computation is and how it differs from classical computation. For this purpose, a very basic explanation of qubit states and quantum gates is presented using linear algebra. This section also shows how quantum computation can mirror its classical counterpart and furthermore find shortcuts to get results faster. Next, the chapter walks through the anatomy of a quantum program including system calls, circuit compilation formats, quantum assembly, and more.

DOI
10.1007/978-1-4842-4218-6_4

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Qiskit, Awesome SDK for Quantum Programming in Python

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In this chapter, you will get started with QISKit, the top SDK out there for quantum programming. You will learn how easy it is to install it in your local system. This section also shows how quantum computation can mirror its classical counterpart and find shortcuts to get results even faster. Next, the chapter walks through the anatomy of a quantum program including system calls, circuit compilation and design, quantum assembly, and more.

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One of the fundamental steps for realizing a quantum computing circuit is the coding aspect of it. Quantum computing simulations and realizing quantum computing circuits need coding and that too as expected a pretty complex method of coding. In this segment, we will understand coding in Python by developing simple circuits and code for understanding the basics of circuit building using basic quantum gates such as CNOT gates, Hadamard gates, Pauli gates, and more. This chapter will provide a slight insight into all the gates the Qiskit framework offers. So, let’s start with a short description followed by an intro to quantum gates present in the Qiskit module that will help us in coding the circuits.

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One of the greatest technological advancements in the last century lies in digital computer science. The idea of storing information and performing complicated calculations with the help of bits, i.e., 0 and 1. But due to a sudden surge in data, the classical computer system has been becoming weak in data processing. Quantum computers offer promising substantial speedup over classical computers for many applications. Quantum chip fabrication has made remarkable gains in recent years, with the number of qubits and fidelity growing. In general computing, a binary digit is the smallest unit of information or a bit. “In quantum computing, the term Qubit (Quantum Bit) serves the exact function of the term bit.” IBM Research released the IBMQ Experience in 2018, the first quantum computer that anyone can use and make accessible to a huge audience of different countries through cloud access. IBM also introduced the tool QISKIT (Quantum information software kit), which enables teachers, researchers, and developers to write coding and run their coding on quantum machines. It also includes different packages of quantum computing. In this paper, the author has discussed different steps to install qiskit. Mainly this paper focused on the “programming and application side of quantum computing.” Qiskit tools used in the python programming language. The “quantum circuits” are fabricated with the use of quantum gates and favorable algorithms with less execution time

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For many practical applications, Quantum computers offer major speed-ups over traditional machines. The production of quantum chips has recently made tremendous strides, with the quantity of Qubits increasing and fidelity increasing. The smallest unit of information is the binary digit i.e. bit in general computing. In Quantum Computing the term Qubit (Quantum Bit) is used for the same purpose. In order to differentiate between a classical bit and a Qubit, Bra-Ket or Dirac notation is used. So, the Qubits are represented as |0〉 and |1〉 and are often read as Ket 0 for zero state and Ket 1 for one state. In this paper mainly programming and application sides of Quantum Computing are focused. For that, Qiskit module and its tools are used in Python programming language. General circuit optimization scheme is given. The Quantum circuits with the concept of Quantum Gates implemented are stronger compared to the optimizing algorithm and with faster execution time. In addition, for prime factorization, access to IBM's Quantum computer is carried out successfully.

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This book provides an easy-to-read but practical introduction to quantum gate simulation to serious learners of the subject. Fundamental physical concepts and selected programming examples of quantum simulations are described for readers who want to use the simulation with a physical understanding background without the use of rigorous mathematics. This book is intended to offer a self-study book for senior and graduate students of physics, computer science, and mathematics who want to learn and write quantum codes. It may also serve as a textbook or a reference in academia and industry. Readers are expected to have introductory knowledge of linear algebra although it is briefly reviewed in this book. Some experience of computer programming is helpful, but no prior knowledge of Python is required for writing the quantum codes shown in this book. Part of IOP Series in Quantum Technology. Key features • Easy-to-read content for self-paced readers. • Many examples with background physics. • Detailed description of entanglement and teleportation. • Guide to industrial resources. • DIY quantum gate simulations.

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Qiskit Metal and Introduction to Chip Design

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As discussed in previous chapters, the Qiskit Metal framework plays a crucial role in designing superconducting qubits. Moving forward, we will use this framework extensively for simulations, where we’ll need to code specific parameters to generate simulations, matrices, and desired outputs. The framework is built using the Python programming language, and Qiskit Metal supports a Python IDE, which facilitates efficient coding. In this chapter, we will explore how to write Python code to develop superconducting circuits. However, before diving directly into the code for superconducting qubits, it is essential to understand some basic concepts.

Apress eBooks•Jan 1, 2025•0 citations
In this chapter you will get started with the QISKit, the best SDK out there for quantum programming. You will learn how easy it is to install the SDK in your local system. But before writing your first quantum program, it is always helpful to understand what quantum computation is and how it differs from classical computation. For this purpose, a very basic explanation of qubit states and quantum gates is presented using linear algebra. This section also shows how quantum computation can mirror its classical counterpart and furthermore find shortcuts to get results faster. Next, the chapter walks through the anatomy of a quantum program including system calls, circuit compilation formats, quantum assembly, and more.
One of the fundamental steps for realizing a quantum computing circuit is the coding aspect of it. Quantum computing simulations and realizing quantum computing circuits need coding and that too as expected a pretty complex method of coding. In this segment, we will understand coding in Python by developing simple circuits and code for understanding the basics of circuit building using basic quantum gates such as CNOT gates, Hadamard gates, Pauli gates, and more. This chapter will provide a slight insight into all the gates the Qiskit framework offers. So, let’s start with a short description followed by an intro to quantum gates present in the Qiskit module that will help us in coding the circuits.
One of the greatest technological advancements in the last century lies in digital computer science. The idea of storing information and performing complicated calculations with the help of bits, i.e., 0 and 1. But due to a sudden surge in data, the classical computer system has been becoming weak in data processing. Quantum computers offer promising substantial speedup over classical computers for many applications. Quantum chip fabrication has made remarkable gains in recent years, with the number of qubits and fidelity growing. In general computing, a binary digit is the smallest unit of information or a bit. “In quantum computing, the term Qubit (Quantum Bit) serves the exact function of the term bit.” IBM Research released the IBMQ Experience in 2018, the first quantum computer that anyone can use and make accessible to a huge audience of different countries through cloud access. IBM also introduced the tool QISKIT (Quantum information software kit), which enables teachers, researchers, and developers to write coding and run their coding on quantum machines. It also includes different packages of quantum computing. In this paper, the author has discussed different steps to install qiskit. Mainly this paper focused on the “programming and application side of quantum computing.” Qiskit tools used in the python programming language. The “quantum circuits” are fabricated with the use of quantum gates and favorable algorithms with less execution time
For many practical applications, Quantum computers offer major speed-ups over traditional machines. The production of quantum chips has recently made tremendous strides, with the quantity of Qubits increasing and fidelity increasing. The smallest unit of information is the binary digit i.e. bit in general computing. In Quantum Computing the term Qubit (Quantum Bit) is used for the same purpose. In order to differentiate between a classical bit and a Qubit, Bra-Ket or Dirac notation is used. So, the Qubits are represented as |0〉 and |1〉 and are often read as Ket 0 for zero state and Ket 1 for one state. In this paper mainly programming and application sides of Quantum Computing are focused. For that, Qiskit module and its tools are used in Python programming language. General circuit optimization scheme is given. The Quantum circuits with the concept of Quantum Gates implemented are stronger compared to the optimizing algorithm and with faster execution time. In addition, for prime factorization, access to IBM's Quantum computer is carried out successfully.
This book provides an easy-to-read but practical introduction to quantum gate simulation to serious learners of the subject. Fundamental physical concepts and selected programming examples of quantum simulations are described for readers who want to use the simulation with a physical understanding background without the use of rigorous mathematics. This book is intended to offer a self-study book for senior and graduate students of physics, computer science, and mathematics who want to learn and write quantum codes. It may also serve as a textbook or a reference in academia and industry. Readers are expected to have introductory knowledge of linear algebra although it is briefly reviewed in this book. Some experience of computer programming is helpful, but no prior knowledge of Python is required for writing the quantum codes shown in this book. Part of IOP Series in Quantum Technology. Key features • Easy-to-read content for self-paced readers. • Many examples with background physics. • Detailed description of entanglement and teleportation. • Guide to industrial resources. • DIY quantum gate simulations.
As discussed in previous chapters, the Qiskit Metal framework plays a crucial role in designing superconducting qubits. Moving forward, we will use this framework extensively for simulations, where we’ll need to code specific parameters to generate simulations, matrices, and desired outputs. The framework is built using the Python programming language, and Qiskit Metal supports a Python IDE, which facilitates efficient coding. In this chapter, we will explore how to write Python code to develop superconducting circuits. However, before diving directly into the code for superconducting qubits, it is essential to understand some basic concepts.