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quant-ph2026

Parallel QEC Decoding Applied to Distributed Quantum Computing

Gabriele Incardona, Davide Ferrari, Michele Amoretti

A novel parallel approach is proposed for QEC decoding based on Belief Propagation with Ordered Statistics Decoding. The main idea is to pre-process the error vectors obtained from…

quant-ph2026

Advanced Scheduling Strategies for Distributed Quantum Computing Jobs

Gongyu Ni, Davide Ferrari, Lester Ho +1

Distributed quantum computing (DQC) is being actively investigated as a means of scaling the number of qubits across multiple connected quantum devices. This includes quantum circu…

quant-ph2026

Optimized Compilation for Distributed Quantum Computing

Michele Bandini, Davide Ferrari, Stefano Carretta +1

In many practical applications, quantum algorithms require several qubits, significantly more than those available with current noisy intermediate-scale quantum processors. Distrib…

quant-ph2024

A Design Framework for the Simulation of Distributed Quantum Computing

Davide Ferrari, Michele Amoretti

The growing demand for large-scale quantum computers is pushing research on Distributed Quantum Computing (DQC). Recent experimental efforts have demonstrated some of the building…

quant-ph2024

Multi-Class Quantum Convolutional Neural Networks

Marco Mordacci, Davide Ferrari, Michele Amoretti

Classification is particularly relevant to Information Retrieval, as it is used in various subtasks of the search pipeline. In this work, we propose a quantum convolutional neural…