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Quantum computing with Qiskit

Ali Javadi-Abhari IBM Quantum IBM T. J. Watson Research Center 10598Yorktown HeightsNY, Matthew Treinish IBM Quantum IBM T. J. Watson Research Center 10598Yorktown HeightsNY, Kevin Krsulich IBM Quantum IBM T. J. Watson Research Center 10598Yorktown HeightsNY, Christopher J Wood IBM Quantum IBM T. J. Watson Research Center 10598Yorktown HeightsNY, Jake Lishman IBM Quantum IBM Research Europe HursleyUnited Kingdom, Julien Gacon IBM Quantum IBM Research Europe ZürichSwitzerland, Simon Martiel IBM Quantum IBM France Lab OrsayFrance, Paul D Nation IBM Quantum IBM T. J. Watson Research Center 10598Yorktown HeightsNY, Lev S Bishop IBM Quantum IBM T. J. Watson Research Center 10598Yorktown HeightsNY, Andrew W Cross IBM Quantum IBM T. J. Watson Research Center 10598Yorktown HeightsNY, Blake R Johnson IBM Quantum IBM T. J. Watson Research Center 10598Yorktown HeightsNY, Jay M Gambetta IBM Quantum IBM T. J. Watson Research Center 10598Yorktown HeightsNY (2024)

Paper Information
arXiv ID
2405.08810
Venue
arXiv.org
Domain
quantum computing
SOTA Claim
Yes
Code
Available
Reproducibility
8/10
Contents

Abstract

We describe Qiskit, a software development kit for quantum information science.We discuss the key design decisions that have shaped its development, and examine the software architecture and its core components.We demonstrate an end-to-end workflow for solving a problem in condensed matter physics on a quantum computer that serves to highlight some of Qiskit's capabilities, for example the representation and optimization of circuits at various abstraction levels, its scalability and retargetability to new gates, and the use of quantum-classical computations via dynamic circuits.Lastly, we discuss some of the ecosystem of tools and plugins that extend Qiskit for various tasks, and the future ahead.

Summary

This paper describes Qiskit, a prominent software development kit for quantum computing. It outlines key design decisions, software architecture, and core components of Qiskit, followed by an end-to-end workflow demonstration for solving a problem in condensed matter physics using a quantum computer. The paper discusses Qiskit's capabilities in circuit representation, optimization, scalability, and integration of quantum-classical computations. The authors highlight the evolution of Qiskit, its ecosystem of tools, and the progress towards achieving major functional milestones in quantum computing software. The future of Qiskit and its importance in facilitating research and education in quantum technology are also discussed.

Methods

This paper employs the following methods:

  • Qiskit
  • Dynamic Circuits
  • Transpilation
  • Parameter Binding

Models Used

  • None specified

Datasets

The following datasets were used in this research:

  • None specified

Evaluation Metrics

  • None specified

Results

  • Demonstrated end-to-end workflow on a quantum computer
  • Improved performance using dynamic circuits
  • Capability to target hardware with optimized circuit transpilations

Limitations

The authors identified the following limitations:

  • None specified

Technical Requirements

  • Number of GPUs: None specified
  • GPU Type: None specified

Keywords

Qiskit quantum circuits quantum algorithms quantum hardware software architecture

Papers Using Similar Methods

External Resources

Funding: IBM, U.S. Department of Energy
References: 92
Influential Citations: 17