2 papers
quant-ph2026
Quantum noise modeling through Reinforcement Learning
Simone Bordoni, Andrea Papaluca, Piergiorgio Buttarini +3
In the current era of quantum computing, robust and efficient tools are essential to bridge the gap between simulations and quantum hardware execution. In this work, we introduce a…
quant-ph2025
Qiboml: towards the orchestration of quantum-classical machine learning
Matteo Robbiati, Andrea Papaluca, Andrea Pasquale +12
We present Qiboml, an open-source software library for orchestrating quantum and classical components in hybrid machine learning workflows. Building on Qibo's quantum computing cap…