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  1. Article ; Online: Statistical Properties of the Quantum Internet.

    Brito, Samuraí / Canabarro, Askery / Chaves, Rafael / Cavalcanti, Daniel

    Physical review letters

    2020  Volume 124, Issue 21, Page(s) 210501

    Abstract: Steady technological advances are paving the way for the implementation of the quantum internet, a network of locations interconnected by quantum channels. Here we propose a model to simulate a quantum internet based on optical fibers and employ network- ... ...

    Abstract Steady technological advances are paving the way for the implementation of the quantum internet, a network of locations interconnected by quantum channels. Here we propose a model to simulate a quantum internet based on optical fibers and employ network-theory techniques to characterize the statistical properties of the photonic networks it generates. Our model predicts a continuous phase transition between a disconnected and a highly connected phase and that the typical photonic networks do not present the small world property. We compute the critical exponents characterizing the phase transition, provide quantitative estimates for the minimum density of nodes needed to have a fully connected network and for the average distance between nodes. Our results thus provide quantitative benchmarks for the development of a quantum internet.
    Keywords covid19
    Language English
    Publishing date 2020-06-12
    Publishing country United States
    Document type Journal Article
    ZDB-ID 208853-8
    ISSN 1079-7114 ; 0031-9007
    ISSN (online) 1079-7114
    ISSN 0031-9007
    DOI 10.1103/PhysRevLett.124.210501
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  2. Article ; Online: Machine Learning Nonlocal Correlations.

    Canabarro, Askery / Brito, Samuraí / Chaves, Rafael

    Physical review letters

    2019  Volume 122, Issue 20, Page(s) 200401

    Abstract: The ability to witness nonlocal correlations lies at the core of foundational aspects of quantum mechanics and its application in the processing of information. Commonly, this is achieved via the violation of Bell inequalities. Unfortunately, however, ... ...

    Abstract The ability to witness nonlocal correlations lies at the core of foundational aspects of quantum mechanics and its application in the processing of information. Commonly, this is achieved via the violation of Bell inequalities. Unfortunately, however, their systematic derivation quickly becomes unfeasible as the scenario of interest grows in complexity. To cope with that, here, we propose a machine learning approach for the detection and quantification of nonlocality. It consists of an ensemble of multilayer perceptrons blended with genetic algorithms achieving a high performance in a number of relevant Bell scenarios. As we show, not only can the machine learn to quantify nonlocality, but discover new kinds of nonlocal correlations inaccessible with other current methods as well. We also apply our framework to distinguish between classical, quantum, and even postquantum correlations. Our results offer a novel method and a proof-of-principle for the relevance of machine learning for understanding nonlocality.
    Language English
    Publishing date 2019-06-10
    Publishing country United States
    Document type Journal Article
    ZDB-ID 208853-8
    ISSN 1079-7114 ; 0031-9007
    ISSN (online) 1079-7114
    ISSN 0031-9007
    DOI 10.1103/PhysRevLett.122.200401
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  3. Article ; Online: Experimental nonclassicality in a causal network without assuming freedom of choice.

    Polino, Emanuele / Poderini, Davide / Rodari, Giovanni / Agresti, Iris / Suprano, Alessia / Carvacho, Gonzalo / Wolfe, Elie / Canabarro, Askery / Moreno, George / Milani, Giorgio / Spekkens, Robert W / Chaves, Rafael / Sciarrino, Fabio

    Nature communications

    2023  Volume 14, Issue 1, Page(s) 909

    Abstract: In 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 ...

    Abstract In 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 complexity.
    Language English
    Publishing date 2023-02-17
    Publishing country England
    Document type Journal Article
    ZDB-ID 2553671-0
    ISSN 2041-1723 ; 2041-1723
    ISSN (online) 2041-1723
    ISSN 2041-1723
    DOI 10.1038/s41467-023-36428-w
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  4. Article: Statistical Properties of the Quantum Internet

    Brito, Samuraí / Canabarro, Askery / Chaves, Rafael / Cavalcanti, Daniel

    Phys Rev Lett

    Abstract: Steady technological advances are paving the way for the implementation of the quantum internet, a network of locations interconnected by quantum channels. Here we propose a model to simulate a quantum internet based on optical fibers and employ network- ... ...

    Abstract Steady technological advances are paving the way for the implementation of the quantum internet, a network of locations interconnected by quantum channels. Here we propose a model to simulate a quantum internet based on optical fibers and employ network-theory techniques to characterize the statistical properties of the photonic networks it generates. Our model predicts a continuous phase transition between a disconnected and a highly connected phase and that the typical photonic networks do not present the small world property. We compute the critical exponents characterizing the phase transition, provide quantitative estimates for the minimum density of nodes needed to have a fully connected network and for the average distance between nodes. Our results thus provide quantitative benchmarks for the development of a quantum internet.
    Keywords covid19
    Publisher WHO
    Document type Article
    Note WHO #Covidence: #32530693
    Database COVID19

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  5. Article ; Online: Data-Driven Study of the the COVID-19 Pandemic via Age-Structured Modelling and Prediction of the Health System Failure in Brazil amid Diverse Intervention Strategies

    Askery Canabarro / Elayne Tenorio / Renato Martins / Lais Martins / Samurai Brito / Rafael Chaves

    Abstract: In this work we propose a data-driven age-structured census-based SIRD-like epidemiological model capable of forecasting the spread of COVID-19 in Brazil. We model the current scenario of closed schools and universities and voluntary home quarantine to ... ...

    Abstract In this work we propose a data-driven age-structured census-based SIRD-like epidemiological model capable of forecasting the spread of COVID-19 in Brazil. We model the current scenario of closed schools and universities and voluntary home quarantine to show that it is still not enough to protect the health system by explicitly computing the demand for hospital intensive care unit beds. We also show that an urgent intense quarantine might be the only solution to avoid the collapse of the health system and, consequently, to minimize the quantity of deaths. On the other hand, we demonstrate that the relaxation of the already imposed control measures in the next days would be catastrophic.
    Keywords covid19
    Publisher medrxiv
    Document type Article ; Online
    DOI 10.1101/2020.04.03.20052498
    Database COVID19

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  6. Article ; Online: Data-driven study of the COVID-19 pandemic via age-structured modelling and prediction of the health system failure in Brazil amid diverse intervention strategies.

    Canabarro, Askery / Tenório, Elayne / Martins, Renato / Martins, Laís / Brito, Samuraí / Chaves, Rafael

    PloS one

    2020  Volume 15, Issue 7, Page(s) e0236310

    Abstract: In this work we propose a data-driven age-structured census-based SIRD-like epidemiological model capable of forecasting the spread of COVID-19 in Brazil. We model the current scenario of closed schools and universities, social distancing of people above ...

    Abstract In this work we propose a data-driven age-structured census-based SIRD-like epidemiological model capable of forecasting the spread of COVID-19 in Brazil. We model the current scenario of closed schools and universities, social distancing of people above sixty years old and voluntary home quarantine to show that it is still not enough to protect the health system by explicitly computing the demand for hospital intensive care units. We also show that an urgent intense quarantine might be the only solution to avoid the collapse of the health system and, consequently, to minimize the quantity of deaths. On the other hand, we demonstrate that the relaxation of the already imposed control measures in the next days would be catastrophic.
    MeSH term(s) Adolescent ; Adult ; Age Distribution ; Aged ; Aged, 80 and over ; Betacoronavirus ; Brazil/epidemiology ; COVID-19 ; Child ; Child, Preschool ; Coronavirus Infections/epidemiology ; Coronavirus Infections/mortality ; Coronavirus Infections/prevention & control ; Coronavirus Infections/virology ; Disease Transmission, Infectious/prevention & control ; Female ; Forecasting ; Humans ; Infant ; Infant, Newborn ; Male ; Middle Aged ; Models, Theoretical ; Pandemics/prevention & control ; Pneumonia, Viral/epidemiology ; Pneumonia, Viral/mortality ; Pneumonia, Viral/prevention & control ; Pneumonia, Viral/virology ; Prognosis ; Quarantine/methods ; SARS-CoV-2 ; Young Adult
    Keywords covid19
    Language English
    Publishing date 2020-07-30
    Publishing country United States
    Document type Journal Article ; Research Support, Non-U.S. Gov't
    ZDB-ID 2267670-3
    ISSN 1932-6203 ; 1932-6203
    ISSN (online) 1932-6203
    ISSN 1932-6203
    DOI 10.1371/journal.pone.0236310
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  7. Article ; Online: Data-driven study of the COVID-19 pandemic via age-structured modelling and prediction of the health system failure in Brazil amid diverse intervention strategies.

    Askery Canabarro / Elayne Tenório / Renato Martins / Laís Martins / Samuraí Brito / Rafael Chaves

    PLoS ONE, Vol 15, Iss 7, p e

    2020  Volume 0236310

    Abstract: In this work we propose a data-driven age-structured census-based SIRD-like epidemiological model capable of forecasting the spread of COVID-19 in Brazil. We model the current scenario of closed schools and universities, social distancing of people above ...

    Abstract In this work we propose a data-driven age-structured census-based SIRD-like epidemiological model capable of forecasting the spread of COVID-19 in Brazil. We model the current scenario of closed schools and universities, social distancing of people above sixty years old and voluntary home quarantine to show that it is still not enough to protect the health system by explicitly computing the demand for hospital intensive care units. We also show that an urgent intense quarantine might be the only solution to avoid the collapse of the health system and, consequently, to minimize the quantity of deaths. On the other hand, we demonstrate that the relaxation of the already imposed control measures in the next days would be catastrophic.
    Keywords Medicine ; R ; Science ; Q ; covid19
    Language English
    Publishing date 2020-01-01T00:00:00Z
    Publisher Public Library of Science (PLoS)
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  8. Article ; Online: How a single particle simultaneously modifies the physical reality of two distant others: a quantum nonlocality and weak value study.

    de Lima Bernardo, Bertúlio / Canabarro, Askery / Azevedo, Sérgio

    Scientific reports

    2017  Volume 7, Page(s) 39767

    Abstract: The concept of wave-particle duality, which is a key element of quantum theory, has been remarkably found to manifest itself in several experimental realizations as in the famous double-slit experiment. In this specific case, a single particle seems to ... ...

    Abstract The concept of wave-particle duality, which is a key element of quantum theory, has been remarkably found to manifest itself in several experimental realizations as in the famous double-slit experiment. In this specific case, a single particle seems to travel through two separated slits simultaneously. Nevertheless, it is never possible to measure it in both slits, which naturally appears as a manifestation of the collapse postulate. In this respect, one could as well ask if it is possible to "perceive" the presence of the particle at the two slits simultaneously, once its collapse could be avoided. In this article, we use the recently proposed entanglement mediation protocol to provide a positive answer to this question. It is shown that a photon which behaves like a wave, i.e., which seems to be present in two distant locations at the same time, can modify two existing physical realities in these locations. Calculations of the "weak trace" left by such photon also enforce the validity of the present argumentation.
    Language English
    Publishing date 2017-01-03
    Publishing country England
    Document type Journal Article ; Research Support, Non-U.S. Gov't
    ZDB-ID 2615211-3
    ISSN 2045-2322 ; 2045-2322
    ISSN (online) 2045-2322
    ISSN 2045-2322
    DOI 10.1038/srep39767
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  9. Article ; Online: Data-driven study of the COVID-19 pandemic via age-structured modelling and prediction of the health system failure in Brazil amid diverse intervention strategies

    Canabarro, Askery / Tenório, Elayne / Martins, Renato / Martins, Laís / Brito, Samuraí / Chaves, Rafael

    PLOS ONE

    2020  Volume 15, Issue 7, Page(s) e0236310

    Keywords General Biochemistry, Genetics and Molecular Biology ; General Agricultural and Biological Sciences ; General Medicine ; covid19
    Language English
    Publisher Public Library of Science (PLoS)
    Publishing country us
    Document type Article ; Online
    ISSN 1932-6203
    DOI 10.1371/journal.pone.0236310
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  10. Book ; Online: Towards accurate real-time luminescence thermometry

    Santos, Emanuel P. / Pugina, Roberta S. / Hilário, Eloísa G. / Carvalho, Alyson J. A. / Jacinto, Carlos / Rego-Filho, Francisco A. M. G. / Canabarro, Askery / Gomes, Anderson S. L. / Caiut, José Maurício A. / Moura, André L.

    an automated machine learning approach

    2023  

    Abstract: Luminescence thermometry has been extensively exploited in the last decades both from the fundamental and applied point of views. The application of photoluminescent nanoparticles on the microscopic level based on rare-earth doped (RED) nanostructures is ...

    Abstract Luminescence thermometry has been extensively exploited in the last decades both from the fundamental and applied point of views. The application of photoluminescent nanoparticles on the microscopic level based on rare-earth doped (RED) nanostructures is yet a challenge. Distinct underlying physical mechanisms in the RED nanomaterials have been exploited, such as intensity ratio between radiative transitions associated with thermally coupled energy levels, energy peak and lifetime of an excited state variations with the temperature. The drawbacks of such systems are the relatively low thermal sensitivity (Sr), and the large temperature uncertainty. To overcome that, several research groups have been seeking new functionalized materials. The majority of the efforts have been directed towards increasing Sr with record around 10 %{\deg}C-1, which is, however, considered unsatisfactory. We propose the use of an automated machine learning tool to retrieve an ideal pipeline improving the response of photoluminescence thermometers. As a proof-of-concept, we used Nd3+-doped YAG nanoparticles, excited at 760 nm, and the photoluminescence spectra in the range from 860 nm to 960 nm as input parameters. In addition to the improvement in the accuracy (> 5.5x over traditional methods), the implementation is very simple, without the requirement of any deconvolution procedure or knowledge of any underlying physical mechanism. Our findings demonstrate that this approach is resilient to natural variances across various spectral acquisitions, which may otherwise lead to an inaccurate estimation of temperature, opening the door for real-time applications. Our open-source code is designed to be accessible to individuals without programming experience.
    Keywords Physics - Instrumentation and Detectors ; Physics - Optics
    Subject code 621
    Publishing date 2023-06-22
    Publishing country us
    Document type Book ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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