Early warning signals indicate a critical transition in Betelgeuse

George, Sandip V.; Kachhara, Sneha; Misra, Ranjeev; Ambika, G.

doi:10.1051/0004-6361/202038785

Cited by 19 publications

(24 citation statements)

References 54 publications

(86 reference statements)

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“…Different hypotheses have been proposed to interpret the nature of this unprecedented fading. They include the formation of a dust cloud due to a recent mass-loss episode (Levesque & Massey 2020;Dupree et al 2020;Cotton et al 2020;Montargès et al 2021), thermal changes in the photosphere accompanying a temperature drop of ∼200 K or the presence of a dark spot covering ∼50% of the stellar surface (Dharmawardena et al 2020), or a critical transition in Betelgeuse seen as a complex dynamical system undergoing a regime shift (George et al 2020).…”

Section: Betelgeuse Is One Of the Closest (222 +48mentioning

confidence: 99%

Atmosphere of Betelgeuse before and during the Great Dimming event revealed by tomography

Kravchenko

Jorissen²,

Eck³

et al. 2021

A&A

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Context. Despite being the best studied red supergiant star in our Galaxy, the physics behind the photometric variability and mass loss of Betelgeuse is poorly understood. Moreover, recently the star has experienced an unusual fading with its visual magnitude reaching a historical minimum. The nature of this event was investigated by several studies where mechanisms, such as episodic mass loss and the presence of dark spots in the photosphere, were invoked. Aims. We aim to relate the atmospheric dynamics of Betelgeuse to its photometric variability, with the main focus on the dimming event. Methods. We used the tomographic method which allowed us to probe different depths in the stellar atmosphere and to recover the corresponding disk-averaged velocity field. The method was applied to a series of high-resolution HERMES observations of Betelgeuse. Variations in the velocity field were then compared with photometric and spectroscopic variations. Results. The tomographic method reveals that the succession of two shocks along our line-of-sight (in February 2018 and January 2019), the second one amplifying the effect of the first one, combined with underlying convection and/or outward motion present at this phase of the 400 d pulsation cycle, produced a rapid expansion of a portion of the atmosphere of Betelgeuse and an outflow between October 2019 and February 2020. This resulted in a sudden increase in molecular opacity in the cooler upper atmosphere of Betelgeuse and, thus, in the observed unusual decrease of the star’s brightness.

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Section: Betelgeuse Is One Of the Closest (222 +48mentioning

confidence: 99%

Atmosphere of Betelgeuse before and during the Great Dimming event revealed by tomography

Kravchenko

Jorissen²,

Eck³

et al. 2021

A&A

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“…For example, the order parameter can be used as such parameter, if the critical transition is the first or the second order phase transition. Other EWS are recurrence measures such as determinism, laminarity and entropy (see the paper [6]).…”

Section: Introductionmentioning

confidence: 99%

Early Warning Signals for Critical Transitions in Sandpile Cellular Automata

et al. 2022

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The sandpile cellular automata, despite the simplicity of their basic rules, are adequate mathematical models of real-world systems, primarily open nonlinear systems capable to self-organize into the critical state. Such systems surround us everywhere. Starting from processes at microscopic distances in the human brain and ending with large-scale water flows in the oceans. The detection of critical transitions precursors in sandpile cellular automata will allow progress significantly in the search for effective early warning signals for critical transitions in complex real systems. The presented paper is devoted to the detection and investigation of such signals based on multifractal analysis of the time series of falls of the cellular automaton cells. We examined cellular automata in square lattice and random graphs using standard and facilitated rules. It has been established that log wavelet leaders cumulant are effective early warning measures of the critical transitions. Common features and differences in the behavior of the log cumulants when cellular automata transit into the self-organized critical state and the self-organized bistability state are also established.

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“…Because critical slowing down may occur prior to transitions in a system, rising autocorrelation and variance have been termed early warning signals (EWS). EWS have been shown to precede transitions in a wide variety of systems, such as climate change (7), starlight shifts (8), and animal extinction (9).…”

Section: Introductionmentioning

confidence: 99%

Anticipating manic and depressive transitions in patients with bipolar disorder using early warning signals

Bos¹,

Schreuder²,

George³

et al. 2021

Preprint

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Background. In bipolar disorder treatment, accurate prediction of manic and depressive episodes is paramount but remains difficult. A novel idiographic approach to prediction is to monitor generic early warning signals (EWS), which may manifest in symptom dynamics. EWS could thus form personalized alerts in clinical care. The present study investigated whether EWS can anticipate mood shifts in individual patients with bipolar disorder. Methods. Twenty bipolar type I/II patients participated in ecological momentary assessment (EMA), completing five questionnaires a day for four months (Mean=491 observations per person). Weekly completed symptom questionnaires on depressive (Quick Inventory for Depressive Symptomatology Self-Report) and manic (Altman Self-Rating Mania Scale) symptoms were used to determine transitions. EWS (rises in autocorrelation at lag-1 and standard deviation) were calculated in moving windows over 17 affective and symptomatic EMA items. Positive and negative predictive values were calculated to determine clinical utility. Results. Eleven (of the twenty) patients reported 1-2 manic or depressive transitions. The presence of EWS increased the probability of impending transitions towards depression and mania from 32-36% to 46-48% (autocorrelation) and 29-41% (standard deviation). However, the absence of EWS could not be taken as a sign that no transition would occur in the near future. The momentary states that indicated nearby transitions most accurately (predictive values: 65-100%) were cheerfulness, focusing ability, full of ideas, worry, racing thoughts, agitation, energy, and tiredness. Large individual differences in the utility of EWS were found.Conclusions. EWS may improve anticipating manic and depressive transitions in bipolar disorder, but await further empirical testing.

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Early warning signals indicate a critical transition in Betelgeuse

Cited by 19 publications

References 54 publications

Atmosphere of Betelgeuse before and during the Great Dimming event revealed by tomography

Atmosphere of Betelgeuse before and during the Great Dimming event revealed by tomography

Early Warning Signals for Critical Transitions in Sandpile Cellular Automata

Anticipating manic and depressive transitions in patients with bipolar disorder using early warning signals

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