6 papers
A variational quantum algorithm for entanglement quantification
Lucas Friedrich, Marcos L. W. Basso, Alberto B. P. Junior +4
Quantum entanglement is a foundational resource in quantum information science, underpinning applications across physics. However, detecting and quantifying entanglement remains a…
QuForge: A Library for Qudits Simulation
Tiago de Souza Farias, Lucas Friedrich, Jonas Maziero
Quantum computing with qudits, an extension of qubits to multiple levels, is a research field less mature than qubit-based quantum computing. However, qudits can offer some advanta…
Quantum neural network with ensemble learning to mitigate barren plateaus and cost function concentration
Lucas Friedrich, Jonas Maziero
The rapid development of quantum computers promises transformative impacts across diverse fields of science and technology. Quantum neural networks (QNNs), as a forefront applicati…
A short review on qudit quantum machine learning
Tiago de Souza Farias, Lucas Friedrich, Jonas Maziero
As quantum devices scale toward practical machine learning applications, the binary qubit paradigm faces expressivity and resource efficiency limitations. Multi-level quantum syste…
Barren plateaus are amplified by the dimension of qudits
Lucas Friedrich, Tiago de Souza Farias, Jonas Maziero
Variational Quantum Algorithms (VQAs) have emerged as pivotal strategies for attaining quantum advantage in diverse scientific and technological domains, notably within Quantum Neu…
Learning to learn with an evolutionary strategy applied to variational quantum algorithms
Lucas Friedrich, Jonas Maziero
Variational Quantum Algorithms (VQAs) employ parameterized quantum circuits optimized using classical methods to minimize a cost function. While VQAs have found broad applications,…