collaborators

10 papers

quant-ph2026

Approximate Quantum State Preparation Through Proximal Policy Optimization

Marco Mordacci, Michele Amoretti

In this work, a quantum architecture search framework for approximate quantum state preparation (QSP) is proposed. QSP is a challenging task, since the search space grows exponenti…

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

A Novel Single-Layer Quantum Neural Network for Approximate SRBB-Based Unitary Synthesis

Giacomo Belli, Marco Mordacci, Michele Amoretti

In this work, a novel quantum neural network is introduced as a means to approximate any unitary evolution through the Standard Recursive Block Basis (SRBB) and is subsequently red…

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-ph2026

Algebraic Reduction to Improve an Optimally Bounded Quantum State Preparation Algorithm

Giacomo Belli, Michele Amoretti

The preparation of -qubit quantum states is a cross-cutting subroutine for many quantum algorithms, and the effort to reduce its circuit complexity is a significant challenge. I…