collaborators

9 papers

quant-ph2026

Universal Optimization and Tighter Fidelity Bounds for Approximate Quantum Error Correction

Jing Wu, Michele Grossi, Doga Kurkcuoglu +1

Approximate quantum error correction (AQEC) not only dictates the performance of discrete- and continuous-variable quantum error correction codes but also serves as a unifying fram…

quant-ph2026

MPStab: an hybrid stabilizers tensor-network quantum circuit simulator

Giulio Crognaletti, Mattia Robbiano, Michele Grossi +1

The development of techniques for simulating quantum systems using classical computers is a paramount task for two primary reasons: i) there exist configurations for which classica…

quant-ph2026

Quantum Fourier Generative Models Trainable at Large Scale

Cenk Tüysüz, Oleksandr Kyriienko, Michele Grossi

We propose an algorithmic framework for building and training quantum generative models corresponding to multivariate probability distributions. Our model uses parallel Fourier fea…

quant-ph2026

Learning partial transpose signatures in qubit ququart states from a few measurements

Christian Candeago, Paolo Da Rold, Michele Grossi +2

Higher-dimensional quantum systems are attracting interest for improving quantum protocol performance by increasing memory space. Characterizing quantum resources of such systems i…

quant-ph2025

Sample-based training of quantum generative models

Maria Demidik, Cenk Tüysüz, Michele Grossi +1

Quantum computers can efficiently sample from probability distributions that are believed to be classically intractable, providing a foundation for quantum generative modeling. How…

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…