Minijets and Broken Stationarity in a Blazar: Novel Insights into the Origin of <i>γ</i> -Ray Variability in CTA 102

Abstract High-energy blazar light curves, in X-rays and beyond, have historically preferred a log-normal flux distribution, signifying multiplicative processes either in the jet itself or due to connection(s) with accretion. Here we present 18 yr archival Fermi Large Area Telescope light curves (0.1–100 GeV) of the flat spectrum radio quasar CTA 102 from 2008 August to 2025 November, which underwent a huge flare in 2017, with a ∼ factor of 100 jump in γ -ray flux, along with similar flaring in X-rays. Our statistical analyses confirm that neither the pre- nor the postflare total GeV light curves follow a strictly log-normal distribution. Instead, we observe a statistically significant reduction in skewness from the pre- to the postflare light curves, which implies the blazar transitioned from an energetic state with frequent flaring to a more plateaued state with occasional flaring. We further find that this state transition can be explained through magnetic relaxation, where many reconnection events caused the 2017 flare, after which the magnetic field was ordered and its energy reached a minimum. To explain this further, we use a Monte Carlo simulation of a modified minijets-in-a-jet model where GeV flares are produced only when a maximum number of minijets move toward the broad line region and toward the line of sight, in the context of an external Compton model. The flux distributions (both observed and simulated) could be fit by a modified log-normal power-law distribution, implying our minijets model can reproduce the GeV flares in CTA 102 as well as their flux distributions.

Authors

Publication Details

Journal
The Astrophysical Journal
Published
2026-01-22
DOI
https://doi.org/10.3847/1538-4357/ae3140
Primary Topic
Astrophysics and Cosmic Phenomena
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Minijets and Broken Stationarity in a Blazar: Novel Insights into the Origin of γ -Ray Variability in CTA 102

Agniva Roychowdhury
The Astrophysical Journal
Astrophysics and Cosmic Phenomena
article

Minijets and Broken Stationarity in a Blazar: Novel Insights into the Origin of γ -Ray Variability in CTA 102

Agniva Roychowdhury
article en

Abstract

Abstract High-energy blazar light curves, in X-rays and beyond, have historically preferred a log-normal flux distribution, signifying multiplicative processes either in the jet itself or due to connection(s) with accretion. Here we present 18 yr archival Fermi Large Area Telescope light curves (0.1–100 GeV) of the flat spectrum radio quasar CTA 102 from 2008 August to 2025 November, which underwent a huge flare in 2017, with a ∼ factor of 100 jump in γ -ray flux, along with similar flaring in X-rays. Our statistical analyses confirm that neither the pre- nor the postflare total GeV light curves follow a strictly log-normal distribution. Instead, we observe a statistically significant reduction in skewness from the pre- to the postflare light curves, which implies the blazar transitioned from an energetic state with frequent flaring to a more plateaued state with occasional flaring. We further find that this state transition can be explained through magnetic relaxation, where many reconnection events caused the 2017 flare, after which the magnetic field was ordered and its energy reached a minimum. To explain this further, we use a Monte Carlo simulation of a modified minijets-in-a-jet model where GeV flares are produced only when a maximum number of minijets move toward the broad line region and toward the line of sight, in the context of an external Compton model. The flux distributions (both observed and simulated) could be fit by a modified log-normal power-law distribution, implying our minijets model can reproduce the GeV flares in CTA 102 as well as their flux distributions.

The Astrophysical JournalVol. 997(2)
Affordable and clean energy
Openalex Percentile: Top 77%
Astrophysics and Cosmic Phenomena
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.