# Quantum computing with Qiskit

**Authors:** Ali Javadi-Abhari, Matthew Treinish, Kevin Krsulich, Christopher J. Wood, Jake Lishman, Julien Gacon, Simon Martiel, Paul D. Nation, Lev S. Bishop, Andrew W. Cross, Blake R. Johnson, Jay M. Gambetta  
**arXiv:** [2405.08810](https://arxiv.org/abs/2405.08810)  
**Date:** 2024-05-14  
**Summary page:** https://www.summarizepaper.com/en/arxiv-id/2405.08810v3/

## Key points

- Qiskit is a comprehensive software development kit for quantum information science
- Key design decisions have influenced its development
- Software architecture and core components are analyzed
- End-to-end workflow showcases how Qiskit can be used in solving problems in condensed matter physics on a quantum computer
- Capabilities of Qiskit include circuit representation and optimization, scalability, retargetability to new gates, and integration of quantum-classical computations through dynamic circuits
- Various tools and plugins within the Qiskit ecosystem extend its functionality for diverse tasks
- Importance of co-designing software and hardware in advancing quantum computing research is emphasized
- Recent release of version 1.0 has achieved maturity, stability, and performance suitable for utility-scale quantum computational workflows
- Potential future directions for Qiskit are discussed
- Quantum software development kits like Qiskit drive progress in quantum computing research by facilitating exploration across different aspects to surpass classical computation in practical applications

## Summary

This paper provides an in-depth discussion of Qiskit, a comprehensive software development kit designed for quantum information science. The authors delve into the key design decisions that have influenced its development and analyze its software architecture and core components. They showcase an end-to-end workflow that demonstrates how Qiskit can be utilized to solve problems in condensed matter physics on a quantum computer. This workflow highlights several capabilities of Qiskit such as circuit representation and optimization at different abstraction levels, scalability, retargetability to new gates, and integration of quantum-classical computations through dynamic circuits. Additionally, the authors explore various tools and plugins within the Qiskit ecosystem that extend its functionality for diverse tasks. They also emphasize the importance of co-designing software and hardware in advancing quantum computing research. With the recent release of version 1.0, Qiskit has achieved maturity, stability, and performance levels suitable for utility-scale quantum computational workflows. The authors discuss potential future directions for Qiskit and acknowledge the contributions of numerous individuals who have been instrumental in its development. Overall, this comprehensive analysis underscores the significance of quantum software development kits like Qiskit in driving progress in quantum computing research and development by facilitating exploration across different aspects of this technology to pave the way for surpassing classical computation in practical applications.