Distinguishing signatures of determinism and stochasticity in spiking complex systems

Andrés Aragoneses* (Corresponding Author), Nicolás Rubido, Jordi Tiana-Alsina, M.C. Torrent, Cristina Masoller

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

24 Citations (Scopus)
4 Downloads (Pure)


We describe a method to infer signatures of determinism and stochasticity in the sequence of apparently random intensity dropouts emitted by a semiconductor laser with optical feedback. The method uses ordinal time-series analysis to classify experimental data of inter-dropout-intervals (IDIs) in two categories that display statistically significant different features. Despite the apparent randomness of the dropout events, one IDI category is consistent with waiting times in a resting state until noise triggers a dropout and the other is consistent with dropouts occurring during the return to the resting state, which have a clear deterministic component. The method we describe can be a powerful tool for inferring signatures of determinism in the dynamics of complex systems in noisy environments, at an event-level description of their dynamics.
Original languageEnglish
Article number1778
Number of pages6
JournalScientific Reports
Publication statusPublished - 7 May 2013


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