4 citations · 4 across the 4 of their papers we have counts for
4 papers
A Representation-Theoretic Framework for Characterizing Barren Plateaus
Pedro Alcântara, Leandro Morais, Rafael Chaves
The scalability of variational quantum algorithms is fundamentally limited by the barren plateau effect, where the cost-function variance vanishes with system size, rendering optim…
Distinguishing Ordered Phases using Machine Learning and Classical Shadows
Leandro Morais, Tiago Pernambuco, Rodrigo G. Pereira +3
Classifying phase transitions is a fundamental and complex challenge in condensed matter physics. This work proposes a framework for identifying quantum phase transitions by combin…
Predicting topological invariants and unconventional superconducting pairing from density of states and machine learning
Flavio Noronha, Askery Canabarro, Rafael Chaves +1
Competition between magnetism and superconductivity can lead to unconventional and topological superconductivity. However, the experimental confirmation of the presence of Majorana…
Detecting quantum phase transitions in a frustrated spin chain via transfer learning of a quantum classifier algorithm
André J. Ferreira-Martins, Leandro Silva, Alberto Palhares +4
The classification of phases and the detection of phase transitions are central and challenging tasks in diverse fields. Within physics, it relies on the identification of order pa…