Heavy-Tailed Fluctuations in the Spiking Output Intensity of Semiconductor Lasers with Optical Feedback
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{"title"=>"Heavy-tailed fluctuations in the spiking output intensity of semiconductor lasers with optical feedback", "type"=>"journal", "authors"=>[{"first_name"=>"Boon Leong", "last_name"=>"Lan", "scopus_author_id"=>"7006128080"}, {"first_name"=>"Cristina", "last_name"=>"Masoller", "scopus_author_id"=>"56272301800"}], "year"=>2016, "source"=>"PLoS ONE", "identifiers"=>{"pui"=>"608919207", "doi"=>"10.1371/journal.pone.0150027", "scopus"=>"2-s2.0-84960533094", "sgr"=>"84960533094", "issn"=>"19326203"}, "id"=>"a7fe3c07-3c73-3773-ba20-649c6378f961", "abstract"=>"Copyright © 2016 Lan, Masoller. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permitsunrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Although heavy-tailed fluctuations are ubiquitous in complex systems, a good understanding of the mechanisms that generate them is still lacking. Optical complex systems are ideal candidates for investigating heavy-tailed fluctuations, as they allow recording large datasets under controllable experimental conditions. A dynamical regime that has attracted a lot of attention over the years is the so-called low-frequency fluctuations (LFFs) of semiconductor lasers with optical feedback. In this regime, the laser output intensity is characterized by abrupt and apparently random dropouts. The statistical analysis of the inter-dropout-intervals (IDIs) has provided many useful insights into the underlying dynamics. However, the presence of large temporal fluctuations in the IDI sequence has not yet been investigated. Here, by applying fluctuation analysis we show that the experimental distribution of IDI fluctuations is heavy-tailed, and specifically, is well-modeled by a non-Gaussian stable distribution. We find a good qualitative agreement with simulations of the Lang-Kobayashi model. Moreover, we uncover a transition from a less-heavy-tailed state at low pump current to a more-heavy-tailed state at higher pump current. Our results indicate that fluctuation analysis can be a useful tool for investigating the output signals of complex optical systems; it can be used for detecting underlying regime shifts, for model validation and parameter estimation.", "link"=>"http://www.mendeley.com/research/heavytailed-fluctuations-spiking-output-intensity-semiconductor-lasers-optical-feedback", "reader_count"=>4, "reader_count_by_academic_status"=>{"Unspecified"=>1, "Librarian"=>2, "Student > Master"=>1}, "reader_count_by_user_role"=>{"Unspecified"=>1, "Librarian"=>2, "Student > Master"=>1}, "reader_count_by_subject_area"=>{"Engineering"=>1, "Unspecified"=>1, "Physics and Astronomy"=>1, "Computer Science"=>1}, "reader_count_by_subdiscipline"=>{"Engineering"=>{"Engineering"=>1}, "Physics and Astronomy"=>{"Physics and Astronomy"=>1}, "Computer Science"=>{"Computer Science"=>1}, "Unspecified"=>{"Unspecified"=>1}}, "reader_count_by_country"=>{"Spain"=>1}, "group_count"=>0}

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Figshare

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  • {"files"=>["https://ndownloader.figshare.com/files/4414993"], "description"=>"<p><i>α</i> and <i>γ</i>, versus the pump parameter for two thresholds: (a), (b) experimental data; (c), (d) simulated data. For the experimental data, the maximum values of the 95% confidence interval half-widths are quite small, 0.007 and 0.003 for <i>α</i> and <i>γ</i>, respectively. For the simulated data, the maximum half-widths are also quite small, 0.01 and 0.004, respectively, and therefore the error bars (parameter +/− confidence interval) are also not plotted because they are all too small to be seen.</p>", "links"=>[], "tags"=>["IDI", "fluctuation analysis", "regime", "LFF", "laser output intensity", "Spiking Output Intensity"], "article_id"=>2738071, "categories"=>["Cell Biology", "Genetics", "Molecular Biology", "Environmental Sciences not elsewhere classified", "Chemical Sciences not elsewhere classified", "Biological Sciences not elsewhere classified", "Information Systems not elsewhere classified", "Mathematical Sciences not elsewhere classified", "Developmental Biology", "Plasma Physics", "Infectious Diseases"], "users"=>["Boon Leong Lan", "Cristina Masoller"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0150027.g002", "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/Fitted_stable_parameters_/2738071", "title"=>"Fitted stable-parameters.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2016-02-22 10:15:32"}

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  • {"unique-ip"=>"6", "full-text"=>"6", "pdf"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2018", "month"=>"12"}
  • {"unique-ip"=>"4", "full-text"=>"3", "pdf"=>"2", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2018", "month"=>"10"}
  • {"unique-ip"=>"7", "full-text"=>"6", "pdf"=>"1", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"8", "cited-by"=>"0", "year"=>"2018", "month"=>"7"}
  • {"unique-ip"=>"6", "full-text"=>"5", "pdf"=>"1", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2018", "month"=>"8"}
  • {"unique-ip"=>"2", "full-text"=>"2", "pdf"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2018", "month"=>"9"}
  • {"unique-ip"=>"5", "full-text"=>"5", "pdf"=>"2", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"3", "cited-by"=>"0", "year"=>"2019", "month"=>"2"}
  • {"unique-ip"=>"1", "full-text"=>"1", "pdf"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"6", "cited-by"=>"0", "year"=>"2019", "month"=>"3"}
  • {"unique-ip"=>"3", "full-text"=>"2", "pdf"=>"1", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2019", "month"=>"4"}
  • {"unique-ip"=>"7", "full-text"=>"7", "pdf"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2019", "month"=>"5"}
  • {"unique-ip"=>"8", "full-text"=>"9", "pdf"=>"1", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2019", "month"=>"8"}
  • {"unique-ip"=>"2", "full-text"=>"3", "pdf"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2019", "month"=>"9"}
  • {"unique-ip"=>"2", "full-text"=>"2", "pdf"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2019", "month"=>"10"}
  • {"unique-ip"=>"4", "full-text"=>"1", "pdf"=>"3", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2019", "month"=>"12"}
  • {"unique-ip"=>"5", "full-text"=>"3", "pdf"=>"1", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"6", "cited-by"=>"0", "year"=>"2020", "month"=>"2"}

Relative Metric

{"start_date"=>"2016-01-01T00:00:00Z", "end_date"=>"2016-12-31T00:00:00Z", "subject_areas"=>[]}
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