2 papers
quant-ph2026
Edge-Local and Qubit-Efficient Quantum Graph Learning for the NISQ Era
Armin Ahmadkhaniha, Jake Doliskani
Graph neural networks (GNNs) are a powerful framework for learning representations from graph-structured data, but their direct implementation on near-term quantum hardware remains…
quant-ph2025
QRTlib: A Library for Fast Quantum Real Transforms
Armin Ahmadkhaniha, Lu Chen, Jake Doliskani +1
Real-valued transforms such as the discrete cosine, sine, and Hartley transforms play a central role in classical computing, complementing the Fourier transform in applications fro…