arXiv subjects

Fu-Wen Zhang

Publications and source records attributed to Fu-Wen Zhang.

At least 19 recordsLinked to original sources

arXiv2026

Identifying Merger-Driven and Collapsar-Driven Gamma-Ray Bursts with Precursor based Solely on Prompt Emission

Gamma-ray bursts (GRBs) are generally classified as Type~I GRBs, which originate from compact binary mergers, and Type~II GRBs, which originate from massive collapsars. The traditional correspondence between short--Type~I GRBs and long--Type~II GRBs, separated by a duration of 2 seconds, has been challenged by recent observations of long GRBs associated with kilonovae (i.e., Type~I-L GRBs) and a short GRB associated with a supernova. In this paper, we focus on GRBs with precursor emission (PE) and compile 366 GRBs detected by Fermi/GBM. Applying the unsupervised machine learning methods t-SNE and UMAP, we are able to distinguish Type~I (including subclass Type~I-L) and Type~II GRBs for the first time and identify PE as a key feature for distinguishing GRBs of different origins. Inspired by results of machine learning, we propose a diagnostic parameter, the $E_{\rm p,ME}$-precursor index ($EPI$), defined as ${\rm log_{10}}(E_{\rm p,ME}^{2}/(T_{\rm 100,PE}T_{\rm 100,QE1}^{1/2}T_{\rm MVT,PE}))$, where most Type~I GRBs have $EPI > 6.2$ and most Type~II GRBs have $EPI < 6.2$. This parameter can help the community to diagnose the origin of any GRB with PE based solely on its prompt emission and rapidly plan for follow-up observations. The validation using Swift GRBs provides illustrative evidence that our method may also be applicable to GRBs observed by instruments other than Fermi.

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arXiv2026

Estimating the peak energy of Swift gamma-ray bursts using supervised machine learning

Gamma-ray bursts (GRBs) are among the most energetic explosive phenomena in the Universe, and their peak energy ($E_{\rm p}$) is a key physical quantity for understanding the prompt emission mechanism. However, due to the limited energy coverage of the Swift satellite, a large fraction of Swift GRBs lack reliable peak energy measurements. Therefore, developing an accurate and efficient method for estimating $E_{\rm p}$ is of great importance. In this work, we propose a method based on the SuperLearner framework that integrates multiple supervised machine learning algorithms to estimate the $E_{\rm p}$ of Swift/BAT GRBs. We used the Swift/BAT observational data from December 2004 to September 2022 as training features, and adopted the peak energies of 516 GRBs jointly detected by Swift and either Fermi/GBM or Konus-Wind as training labels. After training and testing multiple supervised models, the final SuperLearner ensemble yields a more robust and reliable predictive model. In 100 iterations of five-fold cross-validation, the estimated $E'_{\rm p}$ values show a tight correlation with the observed $E_{\rm p}$, with an average Pearson correlation coefficient of $r = 0.72$. Compared with previous Bayesian estimates, our model provides estimations that are likely closer to the true values. Based on the trained model, we further estimated the peak energies of 650 Swift GRBs, significantly increasing the number of GRBs with estimated peak energies and providing new statistical support for constraining GRB emission mechanisms and energy origins.

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arXiv2026

Unveiling the spectral morphological division of fast radio bursts with CHIME/FRB Catalog 2

Fast radio bursts (FRBs) are commonly classified into repeating and apparently nonrepeating sources, yet whether this distinction reflects intrinsically different physical populations remains uncertain. Using the Second CHIME/FRB Catalog, we apply an unsupervised machine learning framework combining Uniform Manifold Approximation and Projection (UMAP) with density-based clustering to investigate the intrinsic structure of the FRB population in a multi-dimensional parameter space. We find that FRBs are primarily separated into two robust clusters dominated by spectral morphology. One cluster is characterized by narrowband emission and longer durations, while the other exhibits relatively broadband spectra and shorter burst timescales. This classification scheme achieves a recall of 0.94 for known repeaters. Within the repeating population, we further identify a stable subclass of atypical repeaters that are broadband, shorter in duration, and more luminous, resembling nonrepeating bursts. Furthermore, broadband nonrepeaters exhibit systematically higher dispersion measures (by approximately 200 $\text{pc cm}^{-3}$) and isotropic luminosities approximately an order of magnitude larger than those of repeating FRBs. Without invoking catastrophic progenitor scenarios, these differences are naturally explained by instrumental sensitivity limits and distance-dependent selection effects. Our results provide new statistical evidence for a physical connection between repeating and nonrepeating FRBs.

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arXiv2025

A Practical Framework for Estimating the Repetition Likelihood of Fast Radio Bursts from Spectral Morphology

The repeating behavior of fast radio bursts (FRBs) is regarded as a key clue to understanding their physical origin, yet reliably distinguishing repeaters from apparent non-repeaters with current observations remains challenging. Here we propose a physically interpretable and practically quantifiable classification framework based on spectral morphology. Using dimensionality reduction, clustering, and feature-importance analysis, we identify the spectral running $r$ and spectral index $\gamma$ as the most critical parameters for distinguishing repeaters from apparent non-repeaters in the CHIME/FRB sample. In the $\gamma$-$r$ space, repeaters preferentially occupy regions with steeper, narrower-band spectra, whereas non-repeaters cluster in flatter, broader-band regions, resulting in a clear density separation. We further construct an empirical probability map in the $\gamma$-$r$ space, showing a clear gradient of repetition likelihood, from $\sim 65\%$ in the high-repetition region to $\sim 5\%$ in the low-repetition region. Combining this with Gaussian Mixture Model posterior analysis, we identify several apparent non-repeaters with high inferred repetition probability, recommending them as priority targets for future monitoring. This framework provides a simple and generalizable tool for assessing repeatability in the CHIME/FRB sample and highlights the diagnostic power of spectral morphology in unveiling FRB origins.

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arXiv2025

Unsupervised machine learning classification of gamma-ray bursts based on the rest-frame prompt emission parameters

Gamma-ray bursts (GRBs) are generally believed to originate from two distinct progenitors, compact binary mergers and massive collapsars. Traditional and some recent machine learning-based classification schemes predominantly rely on observer-frame physical parameters, which are significantly affected by the redshift effects and may not accurately represent the intrinsic properties of GRBs. In particular, the progenitors usually could only be decided by successful detection of the multi-band long-term afterglow, which could easily cost days of devoted effort from multiple global observational utilities. In this work, we apply the unsupervised machine learning (ML) algorithms called t-SNE and UMAP to perform GRB classification based on rest-frame prompt emission parameters. The map results of both t-SNE and UMAP reveal a clear division of these GRBs into two clusters, denoted as GRBs-I and GRBs-II. We find that all supernova-associated GRBs, including the atypical short-duration burst GRB 200826A (now recognized as collapsar-origin), consistently fall within the GRBs-II category. Conversely, all kilonova-associated GRBs (except for two controversial events) are classified as GRBs-I, including the peculiar long-duration burst GRB 060614 originating from a merger event. In another words, this clear ML separation of two types of GRBs based only on prompt properties could correctly predict the results of progenitors without follow-up afterglow properties. Comparative analysis with conventional classification methods using $T_{90}$ and $E_{\rm p,z}$--$E_{\rm iso}$ correlation demonstrates that our machine learning approach provides superior discriminative power, particularly in resolving ambiguous cases of hybrid GRBs.

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arXiv2025

Comprehensive Statistical Analysis of Initial Lorentz Factor and Jet Opening Angle of Gamma-Ray Bursts

The initial Lorentz factor ($\Gamma_{0}$) and jet half-opening angle ($\theta_{\rm jet}$) of gamma-ray bursts (GRBs) are critical physical parameters for understanding the dynamical evolution of relativistic jets and the true energy release of GRBs. We compile a sample of 89 GRBs that exhibit an onset bump feature in their early optical or GeV light curves, 42 of which also display a jet break feature, and derive their $\Gamma_{0}$ and $\theta_{\rm jet}$ values. Using this sample, we re-eaxmine the correlations between $\Gamma_{0}$ and the prompt emission parameters (isotropic energy $E_{\rm iso}$, peak luminosity $L_{\rm iso}$, and peak energy $E_{\rm p}$). Our results confirm the previously reported $\Gamma_{0}$$-$$E_{\rm iso}$ ($L_{\rm iso}$), $\Gamma_{0}$$-$$E_{\rm p,z}$, and $E_{\rm iso}$ ($L_{\rm iso}$)$-$$E_{\rm p}$$-$$\Gamma_{0}$ relations for both homogeneous interstellar medium (ISM) and wind density profiles (Wind). Notably, we find that the short GRB 090510 complies with the $\Gamma_{0}$$-$$E_{\rm iso}$ relation, but significantly deviates from the $\Gamma_{0}$$-$$L_{\rm iso}$ and $\Gamma_{0}$$-$$E_{\rm p,z}$ relations. We systematically investigate the influence of $\theta_{\rm jet}$ on $\Gamma_{0}$ and find a weak dependence. Additionally, we report, for the first time, three new three-parameter correlations, i.e., $E_{\rm iso}$ (or $L_{\rm iso}$, $E_{\rm p,z}$)$-$$\Gamma_{0}$$-$$\theta_{\rm jet}$ correlations. In addition, we further explore the relations between the initial Lorentz factor and the jet-corrected energy. We also find that the jet-corrected correlations remain significant, suggesting that these relations are intrinsic to the physical nature of GRBs. However, the increased dispersion after correction implies that underlying differences persist among individual GRBs.

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arXiv2025

Identifying Merger-Driven Long Gamma-Ray Bursts based on Machine Learning

Gamma-ray bursts (GRBs) are classified as Type I GRBs originated from compact binary mergers and Type II GRBs originated from massive collapsars. While Type I GRBs are typically shorter than 2 seconds, recent observations suggest that some extend to tens of seconds, forming a potential subclass, Type IL GRBs. However, apart from their association with kilonovae, so far no rapid identification is possible. Given the uncertainties and limitations of optical and infrared afterglow observations, an identification method based solely on prompt emission can make such identification possible for many more GRBs. Interestingly, two established Type IL GRBs: GRB 211211A and GRB 230307A, exhibit a three-episode structure: precursor emission (PE), main emission (ME), and extended emission. Therefore, we comprehensively search for GRBs in the Fermi/GBM catalog and identify 29 three-episode GRBs. Based on 12 parameters, we utilize machine learning to distinguish Type IL GRBs from Type II GRBs. Apart from GRB 211211A and GRB 230307A, we are able to identify six more previously unknown Type IL GRBs: GRB 090831, GRB 170228A, GRB 180605A, GRB 200311A, GRB 200914A, and GRB 211019A. We find that Type IL GRBs are characterized by short duration and minimum variability timescale of PE, a short waiting time between PE and ME, and that ME follows the $E_{\rm p,z}$--$E_{\rm iso}$ correlation of Type I GRBs. For the first time, we identify a high-significant PE in the confirmed Type IL GRB 060614.

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arXiv2024

Exploring the Key Features of Repeating Fast Radio Bursts with Machine Learning

Fast radio bursts (FRBs) are enigmatic high-energy events with unknown origins, which are observationally divided into two categories, i.e., repeaters and non-repeaters. However, there are potentially a number of non-repeaters that may be misclassified, as repeating bursts are missed due to the limited sensitivity and observation periods, thus misleading the investigation of their physical properties. In this work, we propose a repeater identification method based on the t-distributed Stochastic Neighbor Embedding (t-SNE) algorithm and apply the classification to the first Canadian Hydrogen Intensity Mapping Experiment Fast Radio Burst (CHIME/FRB) catalog. We find that the spectral morphology parameters, specifically spectral running ($r$), represent the key features for identifying repeaters from the non-repeaters. Also, the results suggest that repeaters are more biased towards narrowband emission, whereas non-repeaters are inclined toward broadband emission. We provide a list of 163 repeater candidates, 5 of which are confirmed with an updated repeater catalog from CHIME/FRB. Our findings improve our understanding of the various properties underlying repeaters and non-repeaters, as well as guidelines for future FRB detection and categorization.

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arXiv2024

Classification of Fermi Gamma-Ray Bursts Based on Machine Learning

Gamma-ray bursts (GRBs) are typically classified into long and short GRBs based on their durations. However, there is a significant overlapping in the duration distributions of these two categories. In this paper, we apply the unsupervised dimensionality reduction algorithm called t-SNE and UMAP to classify 2061 Fermi GRBs based on four observed quantities: duration, peak energy, fluence, and peak flux. The map results of t-SNE and UMAP show a clear division of these GRBs into two clusters. We mark the two clusters as GRBs-I and GRBs-II, and find that all GRBs associated with supernovae are classified as GRBs-II. It includes the peculiar short GRB 200826A, which was confirmed to originate from the death of a massive star. Furthermore, except for two extreme events GRB 211211A and GRB 230307A, all GRBs associated with kilonovae fall into GRBs-I population. By comparing to the traditional classification of short and long GRBs, the distribution of durations for GRBs-I and GRBs-II do not have a fixed boundary. We find that more than 10% of GRBs-I have a duration greater than 2 seconds, while approximately 1% of GRBs-II have a duration shorter than 2 seconds.

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arXiv2019

GW170817: The energy extraction process of the off-axis relativistic outflow and the constraint on the equation of state of neutron stars

As revealed recently by the modeling of the multi-wavelength data of the emission following GW170817/GRB 170817A, there was an off-axis energetic relativistic outflow component launched by this historic double neutron star merger event. In this work we use the results of these modeling to examine the energy extraction process of the central engine. We show that the magnetic process (i.e., the Blandford-Znajek mechanism) is favored, while the neutrino process usually requires a too massive accretion disk if the duration of the central engine activity is comparable to the observed $T_{90}$ of GRB 170817A, unless the timescale of the central engine activity is less than $\sim$ 0.2s. We propose that the GRB observations are helpful to constrain the combined tidal parameter $\tildeΛ$, and by adopting the accretion disk mass distribution estimated in BZ mechanism, the $90\%$ credible interval of $\tildeΛ$ for the progenitor of GW170817 is inferred as $309-954$.

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arXiv2019

Characteristics of Long Gamma-Ray bursts in the Comoving Frame

We compile a sample of 93 long gamma-ray bursts (GRBs) from Fermi satellite and 131 from Konus-Wind, which have measured redshifts and well determined spectra, and estimate their pseudo Lorentz factors (${Γ_0}$) using the tight ${L_{\rm{iso}}}$-${E_{\rm p}}$-${Γ_0}$ correlation. The statistical properties and pair correlations of temporal and spectral parameters are studied in the observer frame, rest frame and comoving frame, respectively. We find that the distributions of the duration, peak energy, isotropic energy and luminosity in the different frames are basically lognormal, and their distributions in the comoving frame are narrow, clustering around $T'_{\rm 90}\sim 4000$ s, $E'_{\rm p,c}\sim 0.7$ keV, $E'_{\rm iso,c} \sim 8\times10^{49}$ erg and $L'_{\rm iso,c}\sim 2.5\times10^{46}$ erg s$^{-1}$, where the redshift evolution effect has been taken into account. We also find that the values of ${Γ_0}$ are broadly distributed between few tens and several hundreds with median values $\sim 270$. We further analyze the pair correlations of all the quantities, and well confirm ${E_{\rm{iso}}}$-${E_{\rm p}}$, ${L_{\rm{iso}}}$-${E_{\rm p}}$, ${L_{\rm{iso}}}$-${Γ_0}$ and $E_{\rm{iso}}$-${Γ_0}$ relations, and find that the corresponding relations in the comoving frame do still exist, but have large dispersions. This suggests not only the well-known spectrum-energy relations are intrinsic correlations, but also the observed correlations are governed by the Doppler effect. In addition, the peak energies of long GRBs are independent of durations both in the rest frame and in the comoving frame. And there is a weak anticorrelation between the peak energy and Lorentz factor.

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arXiv2019

Late afterglow emission statistics: a clear link between GW170817 and bright short GRBs

GW170817, the first neutron star merger event detected by advanced LIGO/Virgo detectors, was associated with an underluminous short duration GRB 170817A. In this work we compare the forward shock afterglow emission of GW170817/GRB 170817A to other luminous short GRBs (sGRBs) with both a known redshift and an afterglow emission lasting at least one day after the burst. In the rapid decay phase, the afterglow emission of the bright sGRBs and GW170817/GRB 170817A form a natural and continuous sequence, though separated by an observation time gap. If viewed on-axis, the forward shock afterglow emission of GW170817/GRB 170817A would be among the brightest ones detected so far. This provides a strong evidence for the GW170817-like merger origin of bright sGRBs, and suggests that the detection of the forward shock afterglow emission of most neutron star merger events are more challenging than the case of GW170817 since usually the mergers will be more distant and the viewing angles are plausibly higher.

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arXiv2018

Short GRBs: opening angles, local neutron star merger rate and off-axis events for GRB/GW association

The jet breaks in the afterglow lightcurves of short gamma-ray bursts (SGRBs), rarely detected so far, are crucial for estimating the half-opening angles of the ejecta ($θ_{\rm j}$) and hence the neutron star merger rate. In this work we report the detection of jet decline behaviors in GRB 150424A and GRB 160821B and find $θ_{\rm j}\sim 0.1$ rad. Together with five events reported before 2015 and other three "identified" recently (GRB 050709, GRB 060614 and GRB 140903A), we have a sample consisting of nine SGRBs and one long-short GRB with reasonably estimated $θ_{\rm j}$. In particular, three {\it Swift} bursts in the sample have redshifts $z\leq 0.2$, with which we estimate the local neutron star merger rate density {to be $\sim 1109^{+1432}_{-657}~{\rm Gpc^{-3}~yr^{-1}}$ or $162^{+140}_{-83} {\rm Gpc^{-3}yr^{-1}}$ if the narrowly-beamed GRB 061201 is excluded}. Inspired by the typical $θ_{\rm j}\sim 0.1$ rad found currently, we further investigate whether the off-beam GRBs (in the uniform jet model) or the off-axis events (in the structured jet model) can significantly enhance the GRB/GW association or not. For the former the enhancement is at most moderate, while for the latter the enhancement can be much greater and a high GRB/GW association probability of $\sim 10\%$ is possible. We also show that the data of GRB 160821B may contain a macronova/kilonova emission component with a temperature of $\sim 3100$ K at $\sim 3.6$ days after the burst and more data are needed to ultimately clarify.

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arXiv2018

How Special Is GRB 170817A?

GRB 170817A is the first short gamma-ray burst (GRB) with direct detection of the gravitational-wave radiation and also the spectroscopically identified macronova emission (i.e., AT 2017gfo). The prompt emission of this burst, however, is underluminous in comparison with the other short GRBs with known redshift. In this work, we examine whether GRB 170817A is indeed unique. We firstly show that GRB 130603B/macronova may be the on-axis "analogs" of GRB 170817A/AT 2017gfo, and the extremely dim { but long-lasting} afterglow emission of GRB 170817A may suggest a low number density ($\sim 10^{-5}~{\rm cm^{-3}}$) of its circumburst medium { and a structured outflow}. We then discuss whether GRB 070923, GRB 080121, GRB 090417A, GRB 111005A, and GRB 170817A form a new group of very nearby underluminous GRBs originated from neutron star mergers. If the short events GRB 070923, GRB 080121, and GRB 090417A are indeed at a redshift of $\sim 0.076,~0.046,~0.088$, respectively, their isotropic energies of the prompt emission are $\sim 10^{47}$ erg and thus comparable to the other two events. The non-detection of optical counterparts of GRB 070923, GRB 080121, GRB 090417A, and GRB 111005A, however, strongly suggests that the macronovae from neutron star mergers are significantly diverse in luminosities or, alternatively, there is the other origin channel (for instance, the white dwarf and black hole mergers). We finally suggest that GW170817/GRB 170817A are likely not alone and similar events will be detected by the upgraded/upcoming gravitational-wave detectors and the electromagnetic monitors.

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arXiv2018

GRB 111005A at Z = 0.0133 and the Prospect of Establishing Long-short GRB/GW Association

GRB 111005A, one long duration gamma-ray burst (GRB) occurred within a metal-rich environment that lacks massive stars with $M_{\rm ZAMS}\geq 15M_\odot$, is not coincident with supernova emission down to stringent limit and thus should be classified as a "long-short" GRB (lsGRB; also known as SN-less long GRB or hybrid GRB), like GRB 060505 and GRB 060614. In this work we show that in the neutron star merger model, the non-detection of the optical/infrared emission of GRB 111005A requires a sub-relativistic neutron-rich ejecta with the mass of $\leq 0.01~M_\odot$, (significantly) less massive than that of GRB 130603B, GRB 060614 and GRB 050709. The lsGRBs are found to have a high rate density and the neutron star merger origin model can be unambiguously tested by the joint observations of the second generation gravitational wave (GW) detectors and the full-sky gamma-ray monitors such as Fermi-GBM and the proposing GECAM. If no lsGRB/GW association is observed in 2020s, alternative scenarios have to be systematically investigated. With the detailed environmental information achievable for the very-nearby events, a novel kind of merger or explosion origin may be identified.

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arXiv2017

GW170817/GRB 170817A/AT2017gfo association: some implications for physics and astrophysics

On 17 August 2017, a gravitational wave event (GW170817) and an associated short gamma-ray burst (GRB 170817A) from a binary neutron star merger had been detected. The followup optical/infrared observations also identified the macronova/kilonova emission (AT2017gfo). In this work we discuss some implications of the remarkable GW170817/GRB 170817A/AT2017gfo association. We show that the $\sim 1.7$s time delay between the gravitational wave (GW) and GRB signals imposes very tight constraint on the superluminal movement of gravitational waves (i.e., the relative departure of GW velocity from the speed of light is $\leq 4.3\times 10^{-16}$) or the possible violation of weak equivalence principle (i.e., the difference of the gamma-ray and GW trajectories in the gravitational field of the galaxy and the local universe should be within a factor of $\sim 3.4\times 10^{-9}$). The so-called Dark Matter Emulators and a class of contender models for cosmic acceleration ("Covariant Galileon") are ruled out, too. The successful identification of Lanthanide elements in the macronova/kilonova spectrum also excludes the possibility that the progenitors of GRB 170817A are a binary strange star system. The high neutron star merger rate (inferred from both the local sGRB data and the gravitational wave data) together with the significant ejected mass strongly suggest that such mergers are the prime sites of heavy r-process nucleosynthesis.

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arXiv2017

Possible correlations between the emission properties of short GRBs and their offsets from the host galaxies

Short Gamma-Ray Bursts(SGRBs) are widely believed to be from mergers of binary compact objects involving at least one neutron star and hence have a broad range of spatial offsets from their host galaxies. In this work we search for possible correlations between the emission properties of 18 SGRBs and their offsets from the host galaxies. The SGRBs with and without extended emission do not show significant difference between their offset distribution, in agreement with some previous works. There are however possible correlations between the optical and X-ray afterglow emission and the offsets. The underlying physical origins are examined.

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arXiv2016

Implications of the Tentative Association between GW150914 and a {\it Fermi}-GBM Transient

The merger-driven Gamma-ray Bursts (GRBs) and their associated gravitational wave (GW) radiation, if both successfully detected, have some far-reaching implications, including for instance: (i) The statistical comparison of the physical properties of the short/long-short GRBs with and without GW detection can test the general origin model; (ii) Revealing the physical processes taking place at the central engine; (iii) Measuring the velocity of the Gravitational wave directly/accurately. In this work we discuss these implications in the case of possible association of GW150914/ GBM transient 150914. We compared GBM transient 150914 with other SGRBs and found that such an event {may be} a distinct outlier in some statistical diagrams, possibly due to its specific binary-black-hole merger origin. However, the presence of a "new" group of SGRBs with "unusual" physical parameters is also possible. If the outflow of GBM transient 150914 was launched by the accretion onto the nascent black hole, the magnetic activity rather than the neutrino process is likely responsible for the energy extraction and the accretion disk mass is estimated to be $\sim 10^{-5}~M_\odot$. The GW150914/GBM transient 150914 association, {if confirmed, would} provide the first opportunity to directly measure the GW velocity and its departure from the speed of the light {should be within} a factor of $\sim 10^{-17}$.

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