Navegando por Autor "Canabarro, Askery"
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TCC Aplicação de técnicas elementares de machine learning à Física(Universidade Federal do Rio Grande do Norte, 2020-07-22) Souza, Nathane Vitória de Lima e; Macrì, Tommaso; Viswanathan, Madras Viswanathan Gandhi; Canabarro, AskeryAvanços recentes impulsionaram, uma vez mais, os investimentos na área de deep learning, que é um subconjunto da grande área de inteligência artificial. A versatilidade desse método possibilita que ele tenha aplicabilidade tanto comercial quanto acadêmica.O presente estudo teve por objetivo avaliar o desempenho de técnicas de deep leaning na resolução de dois problemas físicos, sendo eles a previsão de temperaturas na cidade do Natal/RN e a estimativa dos estados fundamentais de uma partícula sujeita à diversas funções potenciais, em uma dimensão. Para isso, utilizou-se o API Keras - uma plataforma de programação em Python, que possibilita a implementação de redes neurais artificiais. Para o primeiro sistema, foi usada uma arquitetura de camadas do tipo recurrent. Verificou-se que o custo permaneceu alto durante a validação e que a rede sofreu overfitting significativo. Já no segundo problema, a arquitetura escolhida consiste em camadas do tipo Dense empilhadas. Os valores reais do estado fundamental para cada potencial gerado foram comparados às previsões da rede. O resultado obtido indica que houve overfitting e mostra que, apesar do grande poder de representação das redes neurais, a rede em questão teve dificuldades em realizar o ajuste nos casos onde a função que descreve o estado fundamental apresentou maior heterogeneidade.Artigo Causal Networks and Freedom of Choice in Bell’s Theorem(PRX Quantum, 2021-11-03) Araújo, Rafael Chaves Souto; Moreno Filho, Marcos George Magalhães; Polino, Emanuele; Poderini, Davide; Agresti, Iris; Suprano, Alessia; Barros, Mariana Rodrigues; Carvacho, Gonzalo; Wolfe, Elie; Canabarro, Askery; Spekkens, Robert W.; Sciarrino, FabioBell’s theorem is typically understood as the proof that quantum theory is incompatible with local-hidden-variable models. More generally, we can see the violation of a Bell inequality as witnessing the impossibility of explaining quantum correlations with classical causal models. The violation of a Bell inequality, however, does not exclude classical models where some level of measurement dependence is allowed, that is, the choice made by observers can be correlated with the source generating the systems to be measured. Here, we show that the level of measurement dependence can be quantitatively upper bounded if we arrange the Bell test within a network. Furthermore, we also prove that these results can be adapted in order to derive nonlinear Bell inequalities for a large class of causal networks and to identify quantumly realizable correlations that violate them.Artigo Detecting quantum phase transitions in a frustrated spin chain via transfer learning of a quantum classifier algorithm(Physical Review A, 2024-05-20) Ferreira-Martins, André Juan; Silva, Leandro; Palhares Júnior, Alberto Bezerra de; Pereira, Rodrigo; Soares-Pinto, Diogo O.; Araújo, Rafael Chaves Souto; Canabarro, AskeryThe classification of phases and the detection of phase transitions are central and challenging tasks in diverse fields. Within physics, these rely on the identification of order parameters and the analysis of singularities in the free energy and its derivatives. Here, we propose an alternative framework to identify quantum phase transitions. Using the axial next-nearest-neighbor Ising (ANNNI) model as a benchmark, we show how machine learning can detect three phases (ferromagnetic, paramagnetic, and a cluster of the antiphase with the floating phase). Employing supervised learning, we demonstrate the feasibility of transfer learning. Specifically, a machine trained only with nearest-neighbor interactions can learn to identify a new type of phase occurring when next-nearest-neighbor interactions are introduced. We also compare the performance of common classical machine learning methods with a version of the quantum nearest neighbors (QNN) algorithmArtigo Experimental genuine tripartite nonlocality in a quantum triangle network(PRX Quantum, 2022-09-21) Araújo, Rafael Chaves Souto; Poderini, Davide; Polino, Emanuele; Agresti, Iris; Vera, Gonzalo Alfredo Carvacho; Canabarro, Askery; Wolfe, Elie; Suprano, Alessia; Sciarrino, FabioQuantum networks are the center of many of the recent advances in quantum science, not only leading to the discovery of new properties in the foundations of quantum theory but also allowing for novel communication and cryptography protocols. It is known that networks beyond that in the paradigmatic Bell’s theorem imply new and sometimes stronger forms of nonclassicality. Due to a number of practical difficulties, however, the experimental implementation of such networks remains far less explored. Going beyond what has been previously tested, here we verify the nonlocality of an experimental triangle network, consisting of three independent sources of bipartite entangled photon states interconnecting three distant parties. By performing separable measurements only and evaluating parallel chained Bell inequalities, we show that such networks can lead to a genuine form of tripartite nonlocality, where classical models are unable to mimic the quantum predictions even if some of the parties are allowed to communicateArtigo Experimental nonclassicality in a causal network without assuming freedom of choice(Nature Communications, 2023-02-17) Polino, Emanuele; Poderini, Davide; Rodari, Giovanni; Agresti, Iris; Suprano, Alessia; Carvacho, Gonzalo; Wolfe, Elie; Canabarro, Askery; Moreno Filho, Marcos George Magalhães; Milani, Giorgio; Spekkens, Robert W.; Araújo, Rafael Chaves Souto; Sciarrino, FabioIn a Bell experiment, it is natural to seek a causal account of correlations wherein only a common cause acts on the outcomes. For this causal structure, Bell inequality violations can be explained only if causal dependencies are modeled as intrinsically quantum. There also exists a vast landscape of causal structures beyond Bell that can witness nonclassicality, in some cases without even requiring free external inputs. Here, we undertake a photonic experiment realizing one such example: the triangle causal network, consisting of three measurement stations pairwise connected by common causes and no external inputs. To demonstrate the nonclassicality of the data, we adapt and improve three known techniques: (i) a machine-learning-based heuristic test, (ii) a data-seeded inflation technique generating polynomial Bell-type inequalities and (iii) entropic inequalities. The demonstrated experimental and data analysis tools are broadly applicable paving the way for future networks of growing complexityArtigo Predicting topological invariants and unconventional superconducting pairing from density of states and machine learning(Physical Review B, 2025-01-02) Santos, Flávio Luis Noronha dos; Canabarro, Askery; Araújo, Rafael Chaves Souto; Pereira, Rodrigo G.Competition between magnetism and superconductivity can lead to unconventional and topological superconductivity. However, the experimental confirmation of the presence of Majorana edge states and unconventional pairing poses a major challenge. Here, we consider a two-dimensional lattice model for a superconductor with spin-orbit coupling and exchange coupling to randomly distributed magnetic impurities. Depending on parameters of the model, this system may display topologically trivial or nontrivial edge states. We map out the phase diagram by computing the Bott index, a topological invariant defined in real space. We then use machine learning (ML) algorithms to predict the Bott index from the local density of states (LDOS) at zero energy, obtaining high-accuracy results. We also train ML models to predict the amplitude of odd-frequency pairing in the anomalous Green's function at zero energy. Once the ML models are trained using the LDOS, which is experimentally accessible via scanning tunneling spectroscopy, our method could be applied to predict the number of Majorana edge states and estimate the magnitude of odd-frequency pairing in real materials.Artigo Satellite-based photonic quantum networks are small-world(PRX Quantum, 2021-01-08) Araújo, Rafael Chaves Souto; Canabarro, Askery; Cavalcanti, Daniel; Brito, Samuraí Gomes de AguiarRecent milestone experiments establishing satellite-to-ground quantum communication are paving the way for the development of the quantum Internet, a network interconnected by quantum channels. Here, we employ network theory to study the properties of the photonic networks that can be generated by satellite-based quantum communication and compare them with those of their optical-fiber counterpart. We predict that satellites can generate small-world networks, implying that physically distant nodes are actually near from a network perspective. We also analyze the connectivity properties of the network and show, in particular, that they are robust against random failures. This positions satellite-based quantum communication as the most promising technology to distribute entanglement across large distances in quantum networks of growing size and complexity