Practical quantum computing comes closer to reality every day. Some of the best minds on the planet are working on quantum scaling and error correction to unlock the potential of quantum computers to exponentially accelerate innovation in areas including cryptography, drug discovery, finance, logistics, and materials development. Quantum computing shows great promise for machine learning, computational fluid dynamics (CFD), and more, and it can be put to work solving complex problems like climate change.

But quantum computing won’t replace traditional high-performance computing (HPC). Because HPC and quantum computing excel at different types of challenges, they’ll coexist and synergistically support each other. Classical computers are much better at serial processing and today’s general-purpose computing, and quantum systems require preprocessing to make algorithms quantum-ready. Quantum computing is already being used alongside classical HPC, and the growth potential is significant.

Integrating quantum computing with classical HPC enables us to begin solving industrial-scale problems that classical computing alone can’t handle. Because quantum computing — unlike classical computing — excels when data patterns are complex, hard to detect, or tend to change, it complements HPC and has the potential to significantly accelerate problem-solving in science, engineering, and finance.

Developing a Platform for Hybrid Classical-Quantum Workloads

Altair and G2Q, a quantum-ready software company that develops cutting-edge hybrid classical-quantum optimization algorithms, have partnered to develop a feasible, efficient platform for hybrid classical-quantum workloads and perform a fraud-detection proof of concept (POC).

Within this project, the Altair® Accelerator™ and Altair® FlowTracer™ components of the Altair® HPCWorks® platform were adapted to efficiently run a novel hybrid quantum-classical workflow to detect fraudulent credit card transactions and significantly reduce the number of false positives without a precipitous drop in the number of actual fraudulent transactions detected.

The results strongly suggest that quantum computing can be efficiently integrated with HPC to begin solving industrial-scale problems that can’t be optimally addressed with classical computation alone, significantly accelerating critical science, engineering, and financial applications.

Altair HPCWorks efficiently supports hybrid classical-quantum programs by leveraging proven scheduling, reporting, and workflow orchestration capabilities and adapting them for quantum computing. By combining these features with the powerful G2Q hybrid classical-quantum optimization algorithmic framework, Altair HPCWorks supports verifiable, scalable, optimized execution of quantum-accelerated workloads on HPC and quantum infrastructures.

The G2Q-Altair platform gives users a unique combination of infrastructure and quantum-ready algorithms that yields meaningful solutions and takes advantage of small NISQ quantum computers to reduce the amount of classical computation required, potentially saving time, money, and energy. Quantum computers use substantially less time and computational energy resources than classical HPC for the complex problems they’re designed to solve.

Quantum computing has the potential to dramatically improve energy efficiency in real-world applications including climate modeling, material science, and grid optimization — in which technologies including AI and the Internet of Things (IoT) help to efficiently manage supply and demand in complex electrical power grids, reducing energy waste and streamlining power distribution. Quantum computing can also be used to design efficient, cost-effective energy storage solutions and optimize manufacturing processes and supply chains to reduce energy waste and minimize costs. The scheduling features and integration capabilities in Altair HPCWorks make it a robust, flexible base for hybrid classical-quantum workloads.

Learn more about quantum computing with G2Q and Altair in a new white paper.