Hybrid Computing: Where Quantum May Fit in Future Scientific Workflows
A common misconception about quantum computing is that it will eventually replace classical computing. In practice, the most promising approaches suggest something quite different.
Instead of replacing classical systems, quantum computers are likely to become part of hybrid computational workflows, where different technologies work together to solve complex problems.
This perspective is increasingly reflected across the industry. As one expert noted, "it's not quantum vs classical — it's quantum + classical creating new possibilities together."
The rise of hybrid algorithms
Many algorithms developed for today's quantum devices already follow this model. Classical computers handle tasks such as data preparation, parameter optimization, and result analysis, while quantum processors execute specific computational routines.
"In practice, hybrid algorithms function as a distributed workload," explains Karim Essafi, Director of Research and Technology at QunaSys Europe. "Classical HPC systems manage data orchestration and tasks optimized for classical architectures, while offloading specific, computationally intensive subroutines to the quantum processor."
This approach is expected to become even more relevant as quantum hardware evolves. In emerging fault-tolerant systems, quantum resources will remain limited and valuable, making it essential to reserve them for the parts of a problem where they provide the most benefit.
As Karim Essafi notes, "this multi-paradigm approach allows quantum resources to be used strictly for the most 'quantum-hard' operations, while the classical environment handles the remaining workload."
Integrating with existing computing ecosystems
Modern scientific research already relies on complex computational infrastructures. High-performance computing clusters, cloud-based simulations, and machine learning models are commonly used together in research workflows.
Quantum computing may eventually become another specialized component within this ecosystem — not as a standalone system, but as an integrated accelerator.
As observed across the field, quantum technologies are increasingly expected to behave less like independent machines and more like specialized components within larger computational systems.
Potential hybrid workflows could include:
- Classical simulations generating candidate molecular structures
- Quantum algorithms evaluating quantum properties of those molecules
- AI models analyzing and optimizing the results
Such integrated approaches could allow researchers to combine the strengths of multiple computational paradigms.
A gradual integration
Rather than appearing suddenly as a standalone technology, quantum computing may gradually integrate into existing scientific computing environments.
This gradual integration is already being explored in collaborative research projects.
For example, the Q-Neko initiative — a joint EU-Japan project involving both research institutions and industrial partners — focuses on developing hybrid HPC, AI, and quantum computing workflows for real-world applications. Rather than treating quantum computing as a standalone technology, the project explores how it can be embedded into existing computational infrastructures.
As highlighted in the project context, "quantum computing will realize its true value when it becomes seamlessly embedded in real industrial workflows."