Author

Aman Mittal

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Preprint Sep 2026

Landscape Limits of Quantum-Inspired Evolutionary Optimization across 256 continuous functions

Quantum-inspired evolutionary optimization (QIEO) represents design variables as a set of qubits and searches a continuous, multi-dimensional landscape through rotation of the qubit's amplitude pair. Every generation rotates those amplitudes toward a single elite, which corresponds to that generation's best. The update...

R. Govind, F. Bosco, Kasturi Srikanth et al. · 0 citations

Preprint Sep 2026

Evaluation of portability and performance of an OpenMP5 offloaded Quantum-Inspired Evolutionary Optimization Across the GPU Ecosystem

Quantum-inspired evolutionary optimization (QIEO) is a new class of population-based metaheuristic optimization algorithms which represents design variables as a set of qubits and searches a continuous, multi-dimensional landscape through rotation of the qubit's amplitude pair. Every generation rotates those amplitudes...

Kasturi Srikanth, Ashish Singh, F. Bosco et al. · 0 citations

#natural language process... Preprint Sep 2026

Cross-Backend QIEO: Universal Runtime Portability across OpenMP5, CUDA, HIP, and Multi-Language Interfaces

Quantum-inspired algorithms emulate quantum mechanical principles, such as, superposition, interference, and probabilistic amplitude evolution, on classical hardware by representing candidate solutions as qubit vectors and evolving them through rotation-gate operators. This approach offers higher optimization performan...

Aman Mittal, F. Bosco, Kasturi Srikanth et al. · 0 citations