| Title: | A discrete-time benchmark for assessing critical slowing down indicators |
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| Authors: | ID Jafari, Sajad (Author)
ID Karthikeyan, Anitha (Author)
ID Mehrabbeik, Mahtab (Author)
ID Rajagopal, Karthikeyan (Author)
ID Baysal, Veli (Author)
ID Perc, Matjaž (Author) |
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| Files: |  RAZ_Jafari_Sajad_2026.pdf (2,34 MB)
MD5: B8537679D834773DAD9743D5A0F8612A
 https://iopscience.iop.org/article/10.1088/2632-072X/ae5384
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| Language: | English |
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| Work type: | Scientific work |
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| Typology: | 1.01 - Original Scientific Article |
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| Organization: | FNM - Faculty of Natural Sciences and Mathematics
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| Abstract: | We introduce a low-dimensional, discrete-time benchmark for evaluating critical slowing down indicators and early-warning signals in the presence of complex dynamics. Starting from a map-based attention-deficit-disorder model, we add a bias offset to obtain a modified system with a controllable, hysteresis-like coexistence band. Within this band, forward and backward parameter sweeps follow distinct branches, and abrupt switching can occur alongside periodic windows and chaotic regimes. We characterize the dynamics using state-space portraits, bifurcation diagrams, and Lyapunov exponents. We then evaluate four metric-based indicators - lag-1 autocorrelation, variance, skewness, and kurtosis - using a period-aware computation designed for regimes beyond period-one. We find that variance exhibits the most consistent warning trend near the coexistence boundaries, whereas autocorrelation is more susceptible to spurious spikes. Higher-order moments are generally less reliable, particularly in intermittently chaotic regions. Overall, the benchmark is computationally efficient and provides a practical testbed for stress-testing early-warning methods and for quantifying sensitivity to analysis choices. |
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| Keywords: | early warning signal, critical slowing down indicators, hysteresis, chaos, critical phase transition |
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| Publication status: | Published |
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| Publication version: | Version of Record |
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| Article acceptance date: | 17.03.2026 |
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| Publication date: | 31.03.2026 |
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| Year of publishing: | 2026 |
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| Number of pages: | 14 str. |
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| Numbering: | Letn. 7, št. 1, št. članka 015013 |
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| PID: | 20.500.12556/DKUM-97761  |
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| UDC: | 53.01:517.938 |
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| ISSN on article: | 2632-072X |
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| COBISS.SI-ID: | 274802179 |
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| DOI: | 10.1088/2632-072X/ae5384 |
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| Publication date in DKUM: | 10.04.2026 |
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| Views: | 176 |
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| Downloads: | 3 |
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| Metadata: |    |
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| Categories: | Misc.
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