EJSIIResearch AreasQuantum, Computational & Emerging Technologies
Research Area

Quantum, Computational & Emerging Technologies

Research on quantum computing, advanced computation, high-performance computing, scientific simulation, novel computing architectures, and emerging technologies with a rigorous scientific or engineering foundation.

Scope Guidance

What We Publish

Submissions in this area should make a clear scientific, engineering, computational, analytical, or interdisciplinary contribution. Suitable research includes:

01

Quantum algorithms, quantum information, quantum machine learning, and hybrid quantum-classical computation.

02

High-performance computing, parallel algorithms, accelerators, and scientific computing systems.

03

Advanced numerical methods, large-scale simulation, computational modelling, and digital experimentation.

04

Neuromorphic, unconventional, edge, and emerging computing architectures.

05

AI-quantum integration, computational optimization, and emerging algorithmic paradigms.

06

Benchmarking and reproducibility studies for advanced and emerging computing platforms.

Illustrative Examples

Example Research Directions

The examples below illustrate the type and level of research that can fit this area. They are examples, not a closed list.

Hybrid quantum-classical optimization for engineering design problems
Benchmarking quantum machine-learning models under realistic noise
GPU-accelerated multiphysics simulation for complex systems
Energy-efficient emerging architectures for scientific AI workloads
Scalable parallel algorithms for large scientific datasets
Reproducibility framework for emerging computational accelerators
Scope Boundaries

Generally Not Suitable

×

Speculative technology claims without mathematical, computational, or experimental evidence.

×

Quantum-themed commentary with no substantive technical contribution.

×

Simple implementation of known algorithms without meaningful analysis or evaluation.

Important: A manuscript is assessed by its actual research contribution and scope fit, not only by its subject label. Borderline interdisciplinary work may still be suitable when the scientific or technological contribution is clear.
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