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Glitch time series and size distributions in eight prolific pulsars

2019· article· en· W3104494974 on OpenAlexaff
J. R. Fuentes, C. M. Espinoza, Andreas Reisenegger

Bibliographic record

VenueSpringer Link (Chiba Institute of Technology) · 2019
Typearticle
Languageen
FieldPhysics and Astronomy
TopicPulsars and Gravitational Waves Research
Canadian institutionsMcGill University
Fundersnot available
KeywordsPulsarGlitchVelaPhysicsAstrophysicsExponential functionStatistical physicsMonte Carlo methodAstronomyStatisticsMathematicsOpticsMathematical analysis

Abstract

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Context. Glitches are rare spin-up events that punctuate the smooth slow-down of the rotation of pulsars. For the Vela pulsar and PSR J0537−6910, their large glitch sizes and the times between consecutive events have clear preferred scales (Gaussian distributions), contrary to the handful of other pulsars with enough glitches for such a study. Moreover, PSR J0537−6910 is the only pulsar that shows a strong positive correlation between the size of each glitch and the waiting time until the following one. Aims. We attempt to understand this behaviour through a detailed study of the distributions and correlations of glitch properties for the eight pulsars with at least ten detected glitches. Methods. We modelled the distributions of glitch sizes and of the times between consecutive glitches for the eight pulsars with at least ten detected events. We also looked for possible correlations between these parameters and used Monte Carlo simulations to explore two hypotheses that could explain why the correlation so clearly seen in PSR J0537−6910 is absent in other pulsars. Results. We confirm the above results for Vela and PSR J0537−6910, and verify that the latter is the only pulsar with a strong correlation between glitch size and waiting time to the following glitch. For the remaining six pulsars, the waiting time distributions are best fitted by exponentials, and the size distributions are best fitted by either power laws, exponentials, or log-normal functions. Some pulsars in the sample yield significant Pearson and Spearman coefficients (rp and rs) for the aforementioned correlation, confirming previous results. Moreover, for all except the Crab pulsar, both coefficients are positive. For each coefficient taken separately, the probability of this happening is 1/16. Our simulations show that the weaker correlations in pulsars other than PSR J0537−6910 cannot be due to missing glitches that are too small to be detected. We also tested the hypothesis that each pulsar may have two kinds of glitches, namely large, correlated ones and small, uncorrelated ones. The best results are obtained for the Vela pulsar, which exhibits a correlation with rp = 0.68 (p-value = 0.003) if its two smallest glitches are removed. The other pulsars are harder to accommodate under this hypothesis, but their glitches are not consistent with a pure uncorrelated population either. We also find that all pulsars in our sample, except the Crab pulsar, are consistent with the previously found constant ratio between glitch activity and spin-down rate, $ \dot\nu_{\mathrm{g}}/|\dot\nu|=0.010\pm 0.001 $, even though some of them have not shown any large glitches. Conclusions. To explain these results, we speculate except in the case of the Crab pulsar, that all glitches draw their angular momentum from a common reservoir (presumably a neutron superfluid component containing ≈1% of the star’s moment of inertia). However, two different trigger mechanisms could be active, a more deterministic one for larger glitches and a more random one for smaller ones.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.186
Threshold uncertainty score0.548

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.006
GPT teacher head0.258
Teacher spread0.252 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations33
Published2019
Admission routes1
Has abstractyes

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