5 papers · 1 filter
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…
Training Variational Quantum Circuits Using Particle Swarm Optimization
Marco Mordacci, Michele Amoretti
In this work, the Particle Swarm Optimization (PSO) algorithm has been used to train various Variational Quantum Circuits (VQCs). This approach is motivated by the fact that common…
Impact of Single Rotations and Entanglement Topologies in Quantum Neural Networks
Marco Mordacci, Michele Amoretti
In this work, an analysis of the performance of different Variational Quantum Circuits is presented, investigating how it changes with respect to entanglement topology, adopted gat…
Triplet Loss Based Quantum Encoding for Class Separability
Marco Mordacci, Mahul Pandey, Paolo Santini +1
An efficient and data-driven encoding scheme is proposed to enhance the performance of variational quantum classifiers. This encoding is specially designed for complex datasets lik…
SRBB-Based Quantum State Preparation
Giacomo Belli, Marco Mordacci, Michele Amoretti
In this work, a scalable algorithm for the approximate quantum state preparation problem is proposed, facing a challenge of fundamental importance in many topic areas of quantum co…