Insider Brief:
- Terra Quantum and Evonik successfully collaborated on a project to optimize geometry within computational fluid dynamics (CFD) simulations using TQOptimaX, a quantum-inspired optimization solver, and its tensor networks-based component, TetraOpt.
- The project focused on solving multi-objective optimization problems, demonstrating the feasibility of quantum-inspired methods to improve design performance by efficiently handling high-dimensional data.
- Benchmarking tests showed that Terra Quantum’s TQOptimaX performed comparably with Evonik’s state-of-the-art production solver, validating its practicality for industrial applications.
PRESS RELEASE — In a recent release, Terra Quantum and Evonik announced the successful completion of a collaborative project to optimize geometry within Evonik’s computational fluid dynamics simulation processes. By leveraging Terra Quantum’s quantum-inspired optimization solver, TQOptimaX, and its tensor networks-based component, TetraOpt, the release reports the project demonstrated the feasibility of using advanced quantum-inspired methods to address industrial design challenges.
ADDRESSING COMPLEX INDUSTRIAL CHALLENGES
Computational Fluid Dynamics (CFD) simulation processes involve the use of numerical methods and algorithms to analyze and predict the behavior of fluids in various scenarios. These simulations solve complex equations governing fluid dynamics, such as the Navier-Stokes equations, to model phenomena like flow, heat transfer, and turbulence. CFD simulations are applicable in industries such as aerospace, automotive, energy, and chemical manufacturing, where they are used to optimize designs, improve performance, and reduce costs.
One aspect of these simulations is geometry optimization, which focuses on refining the shapes or configurations of physical components to improve their performance metrics—such as minimizing drag, improving heat dissipation, or optimizing fluid flow paths. Given the computational complexity of balancing multiple objectives and constraints, traditional methods often face limitations in efficiency and scalability.
To address these challenges, Evonik, a leading specialty chemicals company, collaborated with Terra Quantum to explore quantum-inspired optimization methods. The project focused on solving multi-objective optimization problems—tasks that involve balancing trade-offs between competing objectives under constraints–in order to achieve better designs through simulation.
Terra Quantum deployed its TQOptimaX optimization solver in Evonik’s simulation environment. This tool uses mathematical frameworks known as tensor networks, which efficiently handle high-dimensional data by simplifying its representation.
ABOUT TQOPTIMAX AND TETRAOPT
As reported in the release, the TQOptimaX solver is designed to address complex multi-objective optimization tasks with minimal computational overhead. It generates Pareto fronts—representations of optimal trade-offs between objectives—while reducing the number of function evaluations required. This efficiency is noted as especially valuable in industrial contexts, where time and computational resources are often constrained.
TetraOpt, a component of TQOptimaX, enhances optimization performance through its tensor train-based framework. Tensor trains, derived from tensor networks, are mathematical constructs that also compactly represent and process high-dimensional data. By using TetraOpt, the project was reported as achieving effective solutions to geometry optimization problems previously deemed too computationally demanding for conventional methods.
REAL-WORLD EVALUATION
To evaluate real-world practicality, the use of TQOptimaX was benchmarked against Evonik’s existing production solver. Terra Quantum’s solutions demonstrated performance levels similar to those of Evonik’s state-of-the-art production solver.
As reported in the release, Markus Pflitsch, CEO and Founder of Terra Quantum, emphasized this implication of the project: “This collaboration showcases the practical potential of quantum technologies for industrial applications. With TQOptimaX, we are challenging limitations in optimization and demonstrating the value of quantum computing for real-world use cases.”
Additionally, Henrik Hahn, Chief Digital Officer of Evonik, remarked, “Our work with Terra Quantum has proven that quantum computing solutions, such as TQOptimaX, can compete with the best solvers available. We look forward to exploring further applications of quantum computing in our operations as the technology continues to evolve.”
