IBM Enhances Qiskit, Leading Quantum Software Toolkit

 

IBM Qiskit

IBM today announced the development and global adoption of its quantum software, Qiskit. Since its launch in 2017, Qiskit, an open-source software development kit (SDK), has enabled over 550,000 users to create and execute quantum circuits on IBM’s quantum hardware platforms, totaling over 3 trillion quantum circuit executions.

To achieve even greater performance, Qiskit has been developed into a whole software stack in its most recent version. From its humble beginnings as a well-liked quantum software development kit for investigating and executing quantum computing experiments, it has developed into a reliable SDK and services portfolio, designed to help users gain better performance when executing intricate quantum circuits on more than 100 qubit IBM quantum computers.

Members of the IBM Quantum Network will be able to discover the next generation of quantum algorithms in their respective areas with the most powerful Qiskit capabilities thanks to this extension, which will also help them uncover quantum advantage.

Users must have a set of tools that can map their issues to make use of both sophisticated classical and quantum computation, optimise the problem for effective quantum execution, and then successfully execute the quantum circuits on actual quantum hardware in order to achieve quantum advantage. These tools, which IBM has been developing for the past seven years, are now coming together to form the Qiskit software stack.

Qiskit has had over 100 releases since its debut as a pioneering quantum computing research tool. Qiskit is used by enterprises, governments, research centres, and universities to undertake large-scale quantum experiments.

The Qiskit software stack is expanded to include:

• The Qiskit SDK v1.x stable release is designed for creating, refining, and displaying quantum circuits.
• Quantum circuit optimisation using artificial intelligence (AI) integrated into the Qiskit Transpiler Service.
• Simplified modes of operation for the Qiskit Runtime Service, which may be adjusted to run quantum circuits efficiently on quantum hardware.
• Watsonx-based generative AI models enable the Qiskit Code Assistant to automate the creation of quantum code.
• Using quantum hardware and classical clusters, quantum-centric supercomputing tasks can be executed using the Qiskit Serverless open-source platform.

Qiskit SDK

Circuits for quantum hardware can now be optimized 39 times faster than with Qiskit 0.33 thanks to the addition of new features and enhancements to the Qiskit SDK. In addition, Qiskit is designed to minimize overhead and minimize the size of circuits; it has been shown to cut memory use by an average of three times when compared to Qiskit 0.43.

Additionally, by integrating AI and heuristic passes with the Qiskit Transpiler Service, customers can minimise circuit depth in comparison to utilising the Qiskit SDK without AI optimisation.

According to Jay Gambetta, IBM Fellow and Vice President, IBM Quantum, “the global adoption of quantum computing and the discovery of quantum advantage will require a combination of leading quantum hardware alongside a robust and performant software stack to run workloads.” The algorithm discovery process that has started on utility-scale quantum technology is based on these two foundations. The Qiskit stack is expected to serve as a fundamental tool for investigating the computational domains where quantum computing shines, as an expanding quantum ecosystem matches its most challenging issues to quantum circuits.

In 2023, IBM gave its quantum hardware’s utility-scale capabilities its first public demonstration. This was the first step towards a future where quantum hardware would be able to execute quantum circuits more quickly and precisely than a classical computer could emulate a quantum computer. Designed to optimise the capabilities of cutting-edge quantum hardware, the Qiskit software stack seeks to support a worldwide community of users in exploring novel quantum algorithms that investigate scenarios in which quantum computing may outperform traditional methods in solving problems.

Giorgio Cortiana, Head of Data and AI – Energy Intelligence, E.ON, stated, “it offers a valuable set of tools for E.ON as we investigate how quantum computing could help us navigate the financial and operational complexities of the energy industry.” “Our team is able to advance utility-scale prototypes with this as a performant foundation to build and discover quantum algorithms that can be applied to business use cases, with the aim of finding new solutions to challenges in the European energy sector.”

Senior scientist Stephan Eidenbenz of Los Alamos National Laboratory stated, “We started using Qiskit for our quantum computing efforts several years ago as part of an effort to help develop a quantum-ready workforce.” Every day, scientists in the lab utilise this to experiment with novel algorithmic concepts and to communicate with IBM’s quantum hardware backends. Our team can also add compiler optimisation steps and enable pulse-level access thanks to it’s open nature.

We have executed circuits on IBM’s quantum hardware at Brookhaven using Qiskit, and this work has led to the publication of around 20 articles to date, covering topics such as condensed matter systems, dynamic systems, and physics frontiers. According to James Misewich, Associate Laboratory Director for Energy and Photon Sciences at Brookhaven National Laboratory, “Qiskit has also allowed our teams to develop extensions that push forward our exploration of bosonic and hybrid qubit-bosonic circuits, and how they could advance fundamental quantum algorithm development and error correction.”

“We have integrated IBM’s Qiskit resources and tutorials into our educational programmes through Brookhaven’s Co-design Centre for Quantum Advantage, where we partner with academic institutions like Stony Brook University to prepare the quantum workforce of the future, as we advance the scientific applications of quantum computing.”

Director of the Department of Energy’s Quantum Science Centre at Oak Ridge National Laboratory, Travis Humble, stated, “Advances in quantum computing software can help support the innovation and rapid growth of our user community and their developing technologies for our Quantum Computing User Programme here at Oak Ridge National Laboratory.” Enhancements in software efficiency will have a substantial influence on how users assess and test the capabilities of current quantum computing systems.

“The Q-CTRL team is excited about collaborating with Qiskit for building,” stated Michael J. Biercuk, the company’s founder and CEO. “Its flexible new interfaces and enhanced stability are enabling us to efficiently build simple abstractions on top of our powerful performance-management software at utility scale, so end users can explore their toughest problems with a single command.”

Constructed for the Quantum Utility Era and Beyond

The breakthrough quantum circuits to advance the quantum utility era are planned to be run by it’s software stack, which is designed to handle the quickly evolving quantum hardware and offers flexibility independent of vendor. This is accomplished by using the Rust programming language in place of performance-critical code, together with an extensive set of tools to facilitate the effective operation of quantum circuits.

The company anticipates that it will continue to provide a framework for the open, iterative, and collaborative development of new quantum algorithms and applications, carried out in conjunction with a growing global ecosystem of clients across industries and domain expertise areas, as IBM continues to build milestones along its IBM Quantum Development and Innovation Roadmap towards error-corrected systems.

Furthermore, the goal of these developing capabilities is to assist users in combining classical and quantum computing resources into a new high-performance computing paradigm characterised by quantum-centric supercomputing, which combines CPUs, GPUs, and QPUs. This next step in high-performance computing, orchestrated by it’s performant software layer, intends to create significant, new, and powerful opportunities for companies throughout the world.

Qiskit 1.0

Please note that IBM’s performance claims for Qiskit are based on comparisons between the software’s performance in its present version and its performance in relevant previous versions when users could access similar functionality. The IBM Quantum Summit 2021 saw a total speed time of 430.89 seconds for Qiskit 0.33. When Qiskit 1.0 was released in February 2024, its total speed time was equal to 10.9 seconds.

Please note that IBM’s performance claims for it is based on comparisons between the software’s performance in its present version and its performance in relevant previous versions when users could access similar functionality. In May 2023, Qiskit 0.43 used 1,750 MiB of RAM. When Qiskit 1.0 was released in February 2024, its memory utilisation was equal to 580 MiB.

The plans, directions, and intentions expressed by IBM are subject to modification or retraction at any time, at IBM’s sole discretion, and without prior notice. Any future features or functionality that we mention for our products are subject to our exclusive discretion regarding their development, release, and timing.