arXiv subjects

Shi-Ju Kang

Publications and source records attributed to Shi-Ju Kang.

13 recordsLinked to original sources

arXiv2026

A Tentative Double Excess in the Gamma-Ray Spectrum of the Fermi Blazar 4FGL J0604.9-0000

Based on 17.75 years of Fermi-LAT observations, we report a tentative double excess in the gamma-ray spectrum of the blazar 4FGL J0604.9-0000, with peak energies at approximately 1.5 GeV and 11 GeV. The two excesses are modeled as double Gaussian components. For the lower-energy excess, the best-fit centroid is $E_1 = 1.59\pm0.07$ GeV with a width fixed to the instrumental resolution ($σ_1 = 0.145$ GeV). For the higher-energy excess, the centroid is $E_2 = 11.15\pm0.61$ GeV and the width is constrained to $σ_2 = 1.185$ GeV (about 10\% of the peak energy), which is comparable to the Fermi-LAT energy resolution at that energy. The two features have local significances of $2.6σ$ and $3.7σ$ (3 dof), respectively. A joint likelihood analysis yields a combined test statistic of TS $\simeq 27$, corresponding to a local significance of approximately $4.3σ$ (4 dof, without correction for trials and the look-elsewhere effect) or about $4.8σ$ (2 dof). To our knowledge, no other active galactic nucleus has been reported to show a similar double-excess candidate. The observed energy ratio of $\sim$1:7 is difficult to explain with standard astrophysical emission processes. However, the energies and their ratio are consistent with dark matter annihilation (e.g., $χχ\toγγ$ and $χχ\toγγ'$) for a particle mass near 11 GeV, making this source a promising target for follow-up observations with next-generation gamma-ray telescopes.

astro-ph.HE↗

arXiv2026

A Universal 1.5 GeV Gamma-Ray Line in Active Galactic Nuclei

We report the detection of a gamma-ray spectral line at approximately 1.5 GeV in three active galactic nuclei (AGN) using 17 years of Fermi-LAT observations. The sample includes both blazars (with relativistic jets directed toward Earth) and a radio galaxy (with a misaligned jet, free from significant beaming effects). The line is detected with local significances of $\sim$4.1$σ$, $\sim$3.9$σ$, and $\sim$2.8$σ$ in the individual sources. A joint likelihood analysis yields a combined test statistic TS $\simeq$ 57.77, corresponding to a significance well above 5$σ$. The line flux remains stable over the full observation period, in contrast to the variable continuum emission from the AGN. The appearance of an identical spectral feature in astrophysically distinct environments is difficult to reconcile with standard jet-based emission mechanisms. While a conventional astrophysical explanation remains elusive, the signal's characteristics are consistent with predictions for dark matter annihilation. This finding motivates further investigation into the nature of this spectral feature and its possible connection to particle dark matter.

astro-ph.HE↗

arXiv2024

Hunting for the candidates of Changing-Look Blazar using Mclust Clustering Analysis

The changing-look blazars (CLBs) are the blazars that their optical spectral lines at different epochs show a significant changes and present a clear transition between the standard FSRQ and BL Lac types. The changing-look phenomena in blazars are highly significant for enhancing our understanding of certain physical problems of active galactic nuclei (AGNs), such as the potential mechanism of the state transition in the accretion process of the supermassive black holes in the central engine of AGNs, the possible intrinsic variation of the jet, and the connection between the accretion disk and the jet. Currently, the CLBs reported in the literature are still rare astronomical objects. In our previous work, we found that there are 8 physical properties parameters of CLBs located between those of FSRQs and those of BL Lacs. In order to search more CLB candidates (CLBCs), we employed the $mclust$ Gaussian Mixture Modelling clustering algorithm to perform clustering analysis for the 255 subsets of the 8 physical properties parameters with 2250 blazars from the 4FGL-DR3. We find that there are 29 subsets with 3 groups (corresponding to bl lacs, fsrqs, and CLBCs), in which there are 4 subsets with the adjusted Rand index greater then 0.610 (ARI $>$ 0.610). The combined clustering results from 4 subsets report that there are 111 CLBCs that includes 44 CLBs reported in previous literature and 67 new CLBCs, where 11 CLBCs labeled as BL Lac and 56 CLBCs labeled as FSRQ in 4FGL catalog.

astro-ph.HE↗

arXiv2024

The changing-look AGN SDSS J101152.98+544206.4 is returning to a type I state

Aims. We reported the discovery that a changing-look AGN SDSS J101152.98+544206.4 (J1011+5442 for short) gradually returns to the type 1 state after a short period between 2014 and 2019 in the faint type 1.9 state. Methods. Motivated by the rebrightening in optical and mid-infrared light curves from ZTF and WISE, we obtained the new spectroscopic observations by Xinglong 2.16-m, Lijiang 2.4-m, and MMT 6.5-m optical telescopes in 2024. Results. After changing the optical AGN type from 1 to 1.9 between 2003 and 2015 based on the repeat spectroscopy from the Time Domain Spectroscopic Survey, J1011+5442 returns to its type 1 state in 2024. We detect the significant and very broad Hbeta lines (FWHM > 5000 km/s) based on the new spectra, which suggests that J1011+5442 is in the intermediate state between the dim state in 2015 and the bright state in 2003. The long-term optical and mid-infrared light curves also show a brightening trend between 2019 and 2024 as the broad Hbeta line appears. The time lag of about 100 days between the mid-infrared and optical variability is consistent with the prediction of dust reverberation mapping. Conclusions. The behaviors of the photometric and spectroscopic observations of J1011+5442 are consistent with the argument that the repeating changing-look phenomenon is regulated by the variation of accretion rate.

astro-ph.HE↗

arXiv2024

The Physical Properties of Changing-look Blazars

Changing-look active galactic nuclei (AGNs) are a special class of AGNs that change their spectral type from type 1 to type 2 or vice versa. In recent years, a number of changing-look blazars (CLBs) were also reported, which transition between flat-spectrum radio quasars and BL Lacs. The physical properties of CLBs are still unclear. Using the $mclust$ R package for Gaussian Mixture Modeling, we performed a clustering analysis for a sample of 105 CLBs selected from the literature. Three kinds of analysis found that CLBs lie in between the parameter distributions of FSRQs and BL Lacs: (i) univariate analysis; (ii) bivariate analysis; and (iii) multivariate analysis, carried out with a dimension reduction approach of the physical properties of the three types of blazars. Our results suggest that CLBs belong to a transition type between FSRQs and BL Lacs, which may be regulated by the change of accretion process and may be similar to other changing-look AGNs.

astro-ph.HE↗

arXiv2023

Hunting for the candidates of misclassified sources in LSP BL Lacs using Machine learning

An equivalent width (EW) based classification may cause the erroneous judgement to the flat spectrum radio quasars (FSRQs) and BL Lacerate objects (BL Lac) due to the diluting the line features by dramatic variations in the jet continuum flux. To help address the issue, the present paper explore the possible intrinsic classification on the bias of a random forest supervised machine learning algorithm. In order to do so, we compile a sample of 1680 Fermi blazars that have both gamma-rays and radio-frequencies data available from the 4LAC-DR2 catalog, which includes 1352 training and validation samples and 328 forecast samples. By studying the results for all of the different combinations of 23 characteristic parameters, we found that there are 178 optimal parameters combinations (OPCs) with the highest accuracy ($\simeq$ 98.89\%). Using the combined classification results from the nine combinations of these OPCs to the 328 forecast samples, we predict that there are 113 true BL Lacs (TBLs) and 157 false BL Lacs (FBLs) that are possible intrinsically FSRQs misclassified as BL Lacs. The FBLs show a clear separation from TBLs and FSRQs in the $γ$-ray photon spectral index, $Γ_{\rm ph}$, and X-band radio flux, ${\rm log}{F_{R}}$, plot. Phenomenally, existence a BL Lac to FSRQ (B-to-F) transition zone is suggested, where the FBLs are in the stage of transition from BL Lacs to FSRQs. Comparing the LSP Changing-Look Blazars (CLBs) reported in the literatures, the majority of LSP CLBs are located at the B-to-F zone. We argue that the FBLs located at B-to-F transition zone are the most likely Candidates of CLBs.

astro-ph.HE↗

arXiv2021

On the origin of GeV spectral break for Fermi blazars: 3C 454.3

The GeV break in spectra of the blazar 3C 454.3 is a special observation feature that has been discovered by the {\it Fermi}-LAT. The origin of the GeV break in the spectra is still under debate. In order to explore the possible source of GeV spectral break in 3C 454.3, a one-zone homogeneous leptonic jet model, as well as the {\it McFit} technique are utilized for fitting the quasi-simultaneous multi-waveband spectral energy distribution (SED) of 3C 454.3. The outside border of the broad-line region (BLR) and inner dust torus are chosen to contribute radiation in the model as external, seed photons to the external-Compton process, considering the observed $γ$-ray radiation. The combination of two components, namely the Compton-scattered BLR and dust torus radiation, assuming a broken power-law distribution of emitted particles, provides a proper fitting to the multi-waveband SED of 3C 454.3 detected 2008 Aug 3 - Sept 2 and explains the GeV spectral break. We propose that the spectral break of 3C 454.3 may originate from an inherent break in the energy distribution of the emitted particles and the Klein-Nishina effect. A comparison is performed between the energy density of the 'external' photon field for the whole BLR $U_{\rm BLR}$ achieved via model fitting and that constrained from the BLR data. The distance from the position of the $γ$-ray radiation area of 3C 454.3 to the central black hole could be constrained at $\sim 0.78$pc ($\sim 4.00 R_{\rm BLR}$, the size of the BLR).

astro-ph.HE↗

arXiv2020

An Explanation for 13 consecutive days activities of Mrk 421

It is surprising to find a fact for migration in the peak positions of synchrotron spectra energy distribution component during in the activity epochs of Mrk 421, accompanying with an orphan flaring at the X-ray and GeV-TeV $γ$-ray bands. A geometric interpretation and standard shock or stochastic acceleration models of blazar emission have difficulty reproducing these observed behaviours. The present paper introduces a linear acceleration by integrating the reconnection electric field into the particle transport model for the observed behaviours of Mrk 421. We note that the strong evidence for evolution of multi-wavelength spectral energy distribution characteristic by shifting the peak frequency, accompanying with an orphan flaring at the X-ray and GeV-TeV $γ$-ray bands provides an important electrostatic acceleration diagnostic in blazar jet. Assuming suitable model parameters, we apply the results of the simulation to the 13-day flaring event in 2010 March of Mrk 421, concentrating on the evolution of multi-wavelength spectral energy distribution characteristic by shifting the peak frequency. It is clear that the ratio of the electric field and magnetic field strength plays an important role in temporal evolution of the peak frequency of synchrotron spectral energy distribution component. We suggest the electrostatic acceleration responsible for the evolution of multi-wavelength spectral energy distribution characteristic by shifting the peak frequency is reasonable. Based on the model results, we issue that the peak frequency of the synchrotron spectral energy distribution component may denote a temporary characteristic of blazars, rather than a permanent one.

astro-ph.HE↗

arXiv2020

Searching for AGN and Pulsar Candidates in 4FGL Unassociated Sources Using Machine Learning

In the fourth \emph{Fermi} Large Area Telescope source catalog (4FGL), 5064 $γ$-ray sources are reported, including 3207 active galactic nuclei (AGNs), 239 pulsars, 1336 unassociated sources, 92 sources with weak association with blazar at low Galactic latitude and 190 other sources. We employ two different supervised machine learning classifiers, combined with the direct observation parameters given by the 4FGL fits table, to search for sources potentially classified as AGNs and pulsars in the 1336 unassociated sources. In order to reduce the error caused by the large difference in the sizes of samples, we divide the classification process into two separate steps in order to identify the AGNs and the pulsars. First, we select the identified AGNs from all of the samples, and then select the identified pulsars from the remaining. Using the 4FGL sources associated or identified as AGNs, pulsars, and other sources with the features selected through the K-S test and the random forest (RF) feature importance measurement, we trained, optimized, and tested our classifier models. Then, the models are applied to classify the 1336 unassociated sources. According to the calculation results of the two classifiers, we show the sensitivity, specificity, accuracy in each step, and the class of unassociated sources given by each classifier. The accuracy obtained in the first step is approximately $95\%$; in the second step, the obtained overall accuracy is approximately $80\%$. Combining the results of the two classifiers, we predict that there are 583 AGN-type candidates, 115 pulsar-type candidates, 154 other types of $γ$-ray candidates, and 484 of uncertain types.

astro-ph.HE↗

arXiv2020

An empirical "high-confidence" candidate zone for $Fermi$ BL Lacertae objects

In the third catalog of active galactic nuclei detected by the $Fermi$ Large Area Telescope Clean (3LAC) sample, there are 402 blazars candidates of uncertain type (BCU). The proposed analysis will help to evaluate the potential optical classification flat spectrum radio quasars (FSRQs) versus BL Lacertae (BL Lacs) objects of BCUs, which can help to understand which is the most elusive class of blazar hidden in the Fermi sample. By studying the 3LAC sample, we found some critical values of $γ$-ray photon spectral index ($Γ_{\rm ph}$), variability index (VI) and radio flux (${\rm F_R}$) of the sources separate known FSRQs and BL Lac objects. We further utilize those values to defined an empirical "high-confidence" candidate zone that can be used to classify the BCUs. Within such a zone ($Γ_{\rm ph}<2.187$, log${\rm F_R}<2.258$ and ${ \rm logVI <1.702}$), we found that 120 BCUs can be classified BL Lac candidates with a higher degree of confidence (with a misjudged rate $<1\%$). Our results suggest that an empirical "high confidence" diagnosis is possible to distinguish the BL Lacs from the Fermi observations based on only on the direct observational data of $Γ_{\rm ph}$, VI and ${\rm F_R}$.

astro-ph.HE↗

arXiv2019

Evaluating the classification of Fermi BCUs from the 4FGL Catalog Using Machine Learning

The recently published fourth Fermi Large Area Telescope source catalog (4FGL) reports 5065 gamma-ray sources in terms of direct observational gamma-ray properties. Among the sources, the largest population is the Active Galactic Nuclei (AGN), which consists of 3137 blazars, 42 radio galaxies, and 28 other AGNs. The blazar sample comprises 694 flat-spectrum radio quasars (FSRQs), 1131 BL Lac-type objects (BL Lacs), and 1312 blazar candidates of an unknown type (BCUs). The classification of blazars is difficult using optical spectroscopy given the limited knowledge with respect to their intrinsic properties, and the limited availability of astronomical observations. To overcome these challenges, machine learning algorithms are being investigated as alternative approaches. Using the 4FGL catalog, a sample of 3137 Fermi blazars with 23 parameters is systematically selected. Three established supervised machine learning algorithms (random forests (RFs), support vector machines (SVMs), artificial neural networks (ANNs)) are employed to general predictive models to classify the BCUs. We analyze the results for all of the different combinations of parameters. Interestingly, a previously reported trend the use of more parameters leading to higher accuracy is not found. Considering the least number of parameters used, combinations of eight, 12 or 10 parameters in the SVM, ANN, or RF generated models achieve the highest accuracy (Accuracy $\simeq$ 91.8\%, or $\simeq$ 92.9\%). Using the combined classification results from the optimal combinations of parameters, 724 BL Lac type candidates and 332 FSRQ type candidates are predicted; however, 256 remain without a clear prediction.

astro-ph.HE↗

arXiv2019

Evaluating the optical classification of Fermi BCUs using machine learning

In the third catalog of active galactic nuclei detected by the Fermi-LAT (3LAC) Clean Sample, there are 402 blazars candidates of uncertain type (BCU). Due to the limitations of astronomical observation or intrinsic properties, it is difficult to classify blazars using optical spectroscopy. The potential classification of BCUs using machine learning algorithms is essential. Based on the 3LAC Clean Sample, we collect 1420 Fermi blazars with 8 parameters of γ-ray photon spectral index, radio flux, flux density, curve significance, the integral photon flux in 100 to 300 MeV, 0.3 to 1 GeV, 10 to 100 GeV and variability index. Here, we apply 4 different supervised machine learning (SML) algorithms (\emph{Decision trees, Random forests, support vector machines and Mclust Gaussian finite mixture models}) to evaluate the classification of BCUs based on the direct observational properties. All the 4 methods can perform exceedingly well with a more accuracy and can effective forecast the classification of Fermi BCUs. The evaluating results show the results of these methods (SML) are valid and robust, where, about 1/4 sources are FSRQs and 3/4 are BL Lacs in 400 BCUs, which are consistent with some other recent results. Although a number of factors influence the accuracy of SML, the results are stable at a fixed ratio 1:3 between FSRQs and BL Lacs, which suggests that the SML can provides an effective method to evaluate the potential classification of BCUs. Among the 4 methods, Mclust Gaussian Mixture Modelling has the highest accuracy for our training sample (4/5, seed=123).

astro-ph.HE↗

arXiv2018

On the intrinsic shape of gamma-ray spectrum for Fermi blazars

The curvature of the $γ$-ray spectrum in blazars may reflect the intrinsic distribution of the emitting electron distribution, which will further give some information on the possible acceleration and cooling processes in the emitting region. The $γ$-ray spectra of Fermi blazars are normally fitted either by a single power-law (PL) or a log-normal (call Logarithmic Parabola, LP) form. The possible reason for this differnece is not unclear. We statistically explore this issue based on the different observational properties of 1419 Fermi blazars in the 3LAC Clean sample. We find that the $γ$-ray flux (100 MeV-100 GeV) and variability index follow bimodal distributions for PL and LP blazars, where $γ$-ray flux and variability index show {a positive correlation}. However, the distributions of the $γ$-ray luminosity and redshift follow a unimodal distribution. Our results suggest that the bimodal distribution of $γ$-ray flux for LP and PL blazars may be not intrinsic and all blazars may have an intrinsic curved $γ$-ray spectrum and the PL spectrum is just caused by the fitting effect due to the less photons.

astro-ph.HE↗