ABSTRACT
A total of 660 discrete jumps in the rotation frequency (ı) and the spin-down rate (ıı) of
about 140 pulsars were studied. Out of the 660 discrete jumps, 394 were classical glitches
(the so-called macroglitches) and 266 were microglitches. The objects are grouped into
normal radio pulsars, anomalous x-ray pulsars and recycled millisecond pulsars. A bimodal
distribution was observed in many of the pulsar glitch parameters, namely the discrete
absolute fractional jumps in the rotation frequency (| Δııı|), the entire absolute discrete
jumps in the spin down rate (|Δıı|), cumulative of the absolute jumps in the rotation frequency
(Σ|Δı|), cumulative of the absolute fractional jumps in rotation frequency (Σ| Δııı|) for
macroglitches may suggest that glitch events may be triggered by dual glitch mechanism.
The distribution of the entire absolute discrete fractional jumps in the rotation frequency
(|Δııı|), cumulative of the absolute jumps in the rotation frequency (Σ|Δı|) and the
cumulative of the absolute jumps in spin down rate (Σ|Δıı|) of microglitches equally suggests
that a glitch event is triggered by one mechanism. It was observed that some of the
macroglitches have magnitudes in ı (rotation frequency) which overlapped with the
microglitches completely which suggest that some of the rotational jumps that was
characterized as macroglitches by previous authors should have been recorded as
microglitches since their glitch magnitude Δııı < 10ıı. The distribution of the glitches
over the spin down parameters shows that pulsars with characteristic age 3 – 4, rotational
frequency of ~ 0.4 − 0.9, spin down rate ~ − 13 − (− 12) and surface magnetic field
strength of 12 − 13 on logarithmic scales exhibit the highest frequency of macroglitches
while those within the characteristic age 5 − 6 , rotational frequency of ~ − 0.1 − 0.4 , spin
down rate of − 14 – (− 13) and surface magnetic field strength of 11 − 12 on logarithmic
scales exhibit the highest frequency of microglitches. From the regression analysis, it was
observed that there was a strong positive linear relationship between (Σ |Δı|) − (Σ|Δıı|)for
the macroglitches and microglitches data when analysed separately and jointly. There was no
correlation between (Σ |Δı|) – ıdata for both samples. On the otherhand, there was a strong
(Σ |Δı|) – |ıı| correlation for the macroglitches and microglitches data when analysed
LOVINA, A (2021). Analysis Of Glitch Activity In Rotating Neutron Stars. Afribary. Retrieved from https://track.afribary.com/works/analysis-of-glitch-activity-in-rotating-neutron-stars
LOVINA, ASOGWA "Analysis Of Glitch Activity In Rotating Neutron Stars" Afribary. Afribary, 14 May. 2021, https://track.afribary.com/works/analysis-of-glitch-activity-in-rotating-neutron-stars. Accessed 25 Dec. 2024.
LOVINA, ASOGWA . "Analysis Of Glitch Activity In Rotating Neutron Stars". Afribary, Afribary, 14 May. 2021. Web. 25 Dec. 2024. < https://track.afribary.com/works/analysis-of-glitch-activity-in-rotating-neutron-stars >.
LOVINA, ASOGWA . "Analysis Of Glitch Activity In Rotating Neutron Stars" Afribary (2021). Accessed December 25, 2024. https://track.afribary.com/works/analysis-of-glitch-activity-in-rotating-neutron-stars