Qiskit Aqua

Introduction

Qiskit Aqua is a high-level, domain-specific library for quantum computing that is part of the Qiskit software framework. It is designed to be used with Qiskit Terra, which provides the foundational roots for quantum computation. Aqua is focused on providing end-to-end quantum algorithms and is designed to be extensible and robust.

A screenshot of a Qiskit Aqua code snippet running in a Jupyter notebook.

A screenshot of a Qiskit Aqua code snippet running in a Jupyter notebook.

Overview

Qiskit Aqua was developed by IBM as part of their Qiskit project, which aims to create a full-stack, open-source quantum computing software framework. The Aqua library is designed to be used by researchers, developers, and quantum computing enthusiasts who want to solve complex problems using quantum algorithms. It is written in Python and can be run on local machines or on real quantum hardware via the IBM Quantum Experience.

Features

Qiskit Aqua provides a rich set of features that make it a powerful tool for quantum computing. These include:

• A comprehensive library of quantum algorithms: Qiskit Aqua includes implementations of many popular quantum algorithms, such as the Quantum Approximate Optimization Algorithm (QAOA), Variational Quantum Eigensolver (VQE), and Quantum Phase Estimation (QPE).

• Extensibility: Qiskit Aqua is designed to be extensible, allowing users to create and integrate their own quantum algorithms, variational forms, and optimizers.

• Integration with Qiskit Terra: Qiskit Aqua is designed to work seamlessly with Qiskit Terra, which provides the low-level quantum circuits and quantum hardware interface.

• Support for classical simulators and quantum hardware: Qiskit Aqua can be run on classical simulators provided by Qiskit Aer, as well as on real quantum hardware through the IBM Quantum Experience.

Quantum Algorithms

Qiskit Aqua provides a comprehensive library of quantum algorithms. These algorithms are designed to solve a variety of complex problems, from optimization and machine learning to chemistry and finance. Some of the key algorithms included in Qiskit Aqua are:

• Quantum Approximate Optimization Algorithm (QAOA): This is a hybrid quantum-classical algorithm that is used to solve combinatorial optimization problems.

• Variational Quantum Eigensolver (VQE): This is a hybrid quantum-classical algorithm that is used to find the ground state energy of a molecule.

• Quantum Phase Estimation (QPE): This is a quantum algorithm that is used to estimate the eigenvalues of a unitary operator.

• Shor's Algorithm: This is a quantum algorithm for integer factorization, which forms the basis of RSA encryption.

• Grover's Algorithm: This is a quantum algorithm for searching an unsorted database with quadratic speedup.

Extensibility

One of the key features of Qiskit Aqua is its extensibility. Users can create and integrate their own quantum algorithms, variational forms, and optimizers. This allows researchers and developers to experiment with new ideas and techniques in quantum computing.

Integration with Qiskit Terra

Qiskit Aqua is designed to work seamlessly with Qiskit Terra, which provides the low-level quantum circuits and quantum hardware interface. This integration allows users to build complex quantum algorithms using the high-level features of Aqua, while still having access to the low-level control provided by Terra.

Support for Classical Simulators and Quantum Hardware

Qiskit Aqua can be run on classical simulators provided by Qiskit Aer, as well as on real quantum hardware through the IBM Quantum Experience. This flexibility allows users to develop and test their quantum algorithms on a simulator before running them on actual quantum hardware.

See Also

• Qiskit
• Quantum Computing
• IBM Quantum Experience