IonQ Demonstrates Computer-Aided Engineering Workload Acceleration by up to 14.6% with Quantum Technology

IonQ and Synopsys demonstrate hybrid quantum workflows that meaningfully shorten large industrial simulations in standard engineering software.

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New hybrid quantum research breakthrough cuts through supercomputing bottlenecks to save processing time for complex car and jet engine simulations

COLLEGE PARK, Md. & TORONTO--(BUSINESS WIRE)-- IonQ (NYSE: IONQ), the world’s leading full-stack quantum platform and foundry, today detailed research conducted with Synopsys. The publication shows early results that quantum algorithms integrated into mainstream engineering software can accelerate complex industrial design by up to 14.6%. The research illustrates hybrid quantum computing can address major computational bottlenecks for classical supercomputers. It also earned a 1st Place Best Paper Award at IEEE Quantum Week 2026 in Toronto.

Companies designing products—from vehicles to sensors to nuclear reactors—rely on simulation to predict product performance against true-to-reality physics. Larger scale simulations, such as those used for virtual crash tests and aerodynamic analysis, can require significant compute resources. Those resources are necessary to solve large systems of equations containing hundreds of millions of variables. Depending on the simulation setup, standard computers may generate extra calculations that consume memory and extend processing times.

To solve this, simulation software attempts to efficiently reorganize the equations before solving them. In this research, IonQ and Synopsys plugged an advanced quantum algorithm directly into Synopsys's industry-standard Ansys LS-DYNA simulation software. Instead of relying on traditional, time-consuming trial-and-error to find the best setup, the quantum system acted like a highly efficient traffic cop. It rapidly identified the best way to organize the data to avoid those unnecessary calculations entirely.

"Engineering simulations for jet engines or automotive crash tests require extremely large classical compute clusters running for days at a time. By embedding an advanced quantum algorithm into the core workflow, we reduced total simulation times by up to 14.6 percent," said Dr. Martin Roetteler, IonQ’s Vice President of Quantum Solutions and Technical Fellow and co-author of the paper. "Because this complex organizing step only needs to happen once at the start of a simulation, the time saved pays off repeatedly. That means faster solutions, reduced compute costs, and lower energy consumption for industrial users."

This new research builds on the team’s prior research. This time, the team tested hybrid workflow across complex digital models of an automobile, an industrial drill component, a fluid impeller, and a jet engine assembly. This study featured meshes made up of up to 35 million individual data points. The numerical simulations were conducted on up to 150 qubits, and physical execution was validated on IonQ's 36-qubit Forte trapped-ion quantum computer.

Across all industrial models tested, the quantum-enhanced sorting method yielded consistent runtime improvements of at least 5.9%, peaking at a 14.6% reduction in total time for complex dynamic simulations. That means a massive digital stress test that typically takes seven continuous days to run on a classical supercomputer, saves approximately one full day of non-stop computing.

"Together with IonQ, we are advancing the development of quantum computers and hybrid simulation workloads to unlock new possibilities for engineering design and optimization,” said Prith Banerjee, Senior Vice President of Innovation at Synopsys. “Quantum computers have the potential to drastically accelerate large simulation workloads while improving predictive accuracy. By focusing on achievable breakthroughs in the NISQ era, we can unlock some of that potential in the near-term for our customers while preparing for the full promise of fault-tolerant quantum computing."

The research paper, titled "End-to-end Performance of Quantum-Accelerated Large-Scale Linear Algebra Workflows," is one of nine IonQ research papers accepted at IEEE Quantum Week 2026, held Sept. 13–18 in Toronto, Canada.

About IonQ

IonQ, Inc. [NYSE: IONQ] is the world’s leading quantum platform and foundry - delivering integrated quantum solutions across computing, networking, sensing, and security. IonQ’s newest generation of quantum computers, the Superion, is the latest in a line of cutting-edge systems. Earlier systems have helped customers and partners including Amazon Web Services, AstraZeneca, and NVIDIA achieve a 20x performance increase over previous quantum solutions and accelerate innovation in drug discovery, materials science, financial modeling, logistics, cybersecurity, and defense. In 2025, the company achieved 99.99% two-qubit gate fidelity, setting a world record in quantum computing performance.

Headquartered in College Park, Maryland, IonQ has operations across North America, Latin America, EMEA, and APAC. Our quantum computing services have been available through all major cloud providers since 2021, while we also meet the needs of networking and sensing customers across land, sea, air, and space. IonQ is making quantum platforms more accessible and impactful than ever before. Learn more at IonQ.com.

View source version on businesswire.com: https://www.businesswire.com/news/home/20260917187917/en/

IonQ Media Contacts
Cheryl Krauss
cheryl.krauss@ionq.co

Tor Constantino
tor.constantino@ionq.co

IonQ Investor Contact
investors@ionq.co

Source: IonQ

Key Terms

hybrid quantum computing technical

A computing approach that combines quantum processors, which handle specific tasks that benefit from quantum effects, with conventional processors for everyday calculations and control. Think of it as a team where a specialist handles the hardest problems and the rest of the team completes routine work; for investors, this matters because it shortens the path to practical applications, influences development costs and timelines, and can create competitive advantages for companies that commercialize useful hybrid systems.

qubits technical

Qubits are the basic units of information in quantum computing, similar to how traditional computers use bits. Unlike regular bits that are either 0 or 1, qubits can represent both at the same time, allowing quantum computers to process complex problems much faster. This potential for unprecedented speed and power could transform industries, making qubits a key focus for investors interested in cutting-edge technology.

trapped-ion quantum computer technical

A trapped-ion quantum computer is a type of quantum computer that stores and processes information using individual charged atoms (ions) held in place by electromagnetic fields and manipulated with lasers or microwaves. It matters to investors because this technology promises a different way to solve certain complex problems much faster than conventional computers—like optimizing logistics or simulating molecules—so companies developing reliable, scalable trapped-ion systems could create new markets or competitive advantages akin to early breakthroughs in microchips.

nisq technical

NISQ stands for “Noisy Intermediate-Scale Quantum,” describing the current generation of quantum computers that have a moderate number of qubits but suffer from errors and limited stability. Investors care because NISQ machines can enable early practical quantum experiments and niche applications—like a prototype tool that can hint at future capabilities—so companies working on NISQ hardware, software, or related services may influence technology roadmaps, partnerships, and long-term value creation.