Search for: All records

Machine learning models have been developed for a wide variety of power system applications. The accuracy of a machine learning model strongly depends on the selection of training data. In many settings where real data are limited or unavailable, machine learning models are trained using synthetic data sampled via different strategies. Using the task of approximating the voltage magnitudes associated with specified complex power injections as an illustrative application, this paper compares the performance of neural networks trained on four different sampling strategies: (i) correlated loads at fixed power factor, (ii) correlated loads at varying power factor, (iii) uncor-related loads at fixed power factor, and (iv) uncorrelated loads at varying power factor. A new sampling strategy that combines these four strategies into one training dataset is also introduced and assessed. Results from transmission and distribution test cases of varying sizes show that these strategies for creating synthetic training data yield varied neural network accuracy. The accuracy differences across the various strategies vary by up to a factor of four. While none of the first four strategies outperform the others across all test cases, neural networks trained with the combined dataset perform the best overall, maintaining a high accuracy and low error spreads. 

Abstract The brightest gamma-ray burst (GRB) ever, GRB 221009A, displays ultralong GRB (ULGRB) characteristics, with a prompt emission duration exceeding 1000 s. To constrain the origin and central engine of this unique burst, we analyze its prompt and afterglow characteristics and compare them to the established set of similar GRBs. To achieve this, we statistically examine a nearly complete sample of Swift-detected GRBs with measured redshifts. We categorize the sample to bronze, silver, and gold by fitting a Gaussian function to the log-normal ofT₉₀duration distribution and considering three subsamples respectively to 1, 2, and 3 times of the standard deviation to the mean value. GRB 221009A falls into the gold subsample. Our analysis of prompt emission and afterglow characteristics aims to identify trends between the three burst groups. Notably, the gold subsample (a higher likelihood of being ULGRB candidates) suggests a collapsar scenario with a hyperaccreting black hole as a potential central engine, while a few GRBs (GRB 060218, GRB 091024A, and GRB 100316D) in our gold subsample favor a magnetar. Late-time near-IR observations from 3.6 m Devasthal Optical Telescope rule out the presence of any bright supernova associated with GRB 221009A in the gold subsample. To further constrain the physical properties of ULGRB progenitors, we employ the toolMESAto simulate the evolution of low-metallicity massive stars with different initial rotations. The outcomes suggest that rotating (Ω ≥ 0.2 Ω_c) massive stars could potentially be the progenitors of ULGRBs within the considered parameters and initial inputs toMESA. 

The bright GRB 210610B was discovered simultaneously by Fermi and Swift missions at redshift 1.13. We utilized broadband Fermi-GBM observations to perform a detailed prompt emission spectral analysis and to understand the radiation physics of the burst. Our analysis displayed that the low energy spectral index (αpt) exceeds boundaries expected from the typical synchrotron emission spectrum (-1.5,-0.67), suggesting additional emission signature. We added an additional thermal model with the typical Band or CPL function and found that CPL + BB function is better fitting to the data, suggesting a hybrid jet composition for the burst. Further, we found that the beaming corrected energy (Eγ,θj = 1.06 × 1051 erg) of the burst is less than the total energy budget of the magnetar. Additionally, the X-ray afterglow light curve of this burst exhibits achromatic plateaus, adding another layer of complexity to the explosion’s behavior. Interestingly, we noted that the X-ray energy release during the plateau phase (EX,iso = 1.94 × 1051 erg) is also less than the total energy budget of the magnetar. Our results indicate the possibility that a magnetar could be the central engine for this burst. 

Abstract The radiation mechanism underlying the prompt emission remains unresolved and can be resolved using a systematic and uniform time-resolved spectro-polarimetric study. In this paper, we investigated the spectral, temporal, and polarimetric characteristics of five bright gamma-ray bursts (GRBs) using archival data from AstroSat CZTI, Swift Burst Alert Telescope, and Fermi/GBM. These bright GRBs were detected by CZTI in its first year of operation, and their average polarization characteristics have been published in Chattopadhyay et al. In the present work, we examined the time-resolved (in 100–600 keV) and energy-resolved polarization measurements of these GRBs with an improved polarimetric technique such as increasing the effective area and bandwidth (by using data from low-gain pixels), using an improved event selection logic to reduce noise in the double events and extend the spectral bandwidth. In addition, we also separately carried out detailed time-resolved spectral analyses of these GRBs using empirical and physical synchrotron models. By these improved time-resolved and energy-resolved spectral and polarimetric studies (not fully coupled spectro-polarimetric fitting), we could pin down the elusive prompt emission mechanism of these GRBs. Our spectro-polarimetric analysis reveals that GRB 160623A, GRB 160703A, and GRB 160821A have Poynting flux-dominated jets. On the other hand, GRB 160325A and GRB 160802A have baryonic-dominated jets with mild magnetization. Furthermore, we observe a rapid change in polarization angle by ∼90° within the main pulse of very bright GRB 160821A, consistent with our previous results. Our study suggests that the jet composition of GRBs may exhibit a wide range of magnetization, which can be revealed by utilizing spectro-polarimetric investigations of the bright GRBs. 

Abstract With a small sample of fast X-ray transients (FXTs) with multiwavelength counterparts discovered to date, their progenitors and connections toγ-ray bursts (GRBs) and supernovae (SNe) remain ambiguous. Here, we present photometric and spectroscopic observations of SN 2025kg, the SN counterpart to the FXT EP 250108a. Atz= 0.17641, this is the closest known SN discovered following an Einstein Probe (EP) FXT. We show that SN 2025kg’s optical spectra reveal the hallmark features of a broad-lined Type Ic SN. Its light-curve evolution and expansion velocities are comparable to those of GRB-SNe, including SN 1998bw, and two past FXT-SNe. We present JWST/NIRSpec spectroscopy taken around SN 2025kg’s maximum light, and find weak absorption due to HeI1.0830μm and 2.0581μm and a broad, unidentified emission feature at ∼4–4.5μm. Further, we observe broadened Hαin optical data at 42.5 days that is not detected at other epochs, indicating interaction with H-rich material. From its light curve, we derive a⁵⁶Ni mass of 0.2–0.6M_⊙. Together with our companion Letter, our broadband data are consistent with a trapped or low-energy (≲10⁵¹erg) jet-driven explosion from a collapsar with a zero-age main-sequence mass of 15–30M_⊙. Finally, we show that the sample of EP FXT-SNe supports past estimates that low-luminosity jets seen through FXTs are more common than successful (GRB) jets, and that similar FXT-like signatures are likely present in at least a few percent of the brightest Type Ic-BL SNe. 

Increasing concerns and regulations about data privacy and sparsity necessitate the study of privacy-preserving, decentralized learning methods for natural language processing (NLP) tasks. Federated learning (FL) provides promising approaches for a large number of clients (e.g., personal devices or organizations) to collaboratively learn a shared global model to benefit all clients while allowing users to keep their data locally. Despite interest in studying FL methods for NLP tasks, a systematic comparison and analysis is lacking in the literature. Herein, we present the FedNLP, a benchmarking framework for evaluating federated learning methods on four different task formulations: text classification, sequence tagging, question answering, and seq2seq. We propose a universal interface between Transformer-based language models (e.g., BERT, BART) and FL methods (e.g., FedAvg, FedOPT, etc.) under various non-IID partitioning strategies. Our extensive experiments with FedNLP provide empirical comparisons between FL methods and helps us better understand the inherent challenges of this direction. The comprehensive analysis points to intriguing and exciting future research aimed at developing FL methods for NLP tasks. 

Abstract We present a detailed prompt emission and early optical afterglow analysis of the two very-high-energy (VHE) detected bursts GRB 201015A and GRB 201216C, and their comparison with a subset of similar bursts. Time-resolved spectral analysis of multistructured GRB 201216C using the Bayesian binning algorithm revealed that during the entire duration of the burst, the low-energy spectral index ( α pt ) remained below the limit of the synchrotron line of death. However, statistically some of the bins supported the additional thermal component. Additionally, the evolution of spectral parameters showed that both the peak energy ( E p ) and α pt tracked the flux. These results were further strengthened using the values of the physical parameters obtained by synchrotron modeling of the data. Our earliest optical observations of both bursts using the F/Photometric Robotic Atmospheric Monitor Observatorio del Roque de los Muchachos and Burst Observer and Optical Transient Exploring System robotic telescopes displayed a smooth bump in their early optical light curves, consistent with the onset of the afterglow due to synchrotron emission from an external forward shock. Using the observed optical peak, we constrained the initial bulk Lorentz factors of GRB 201015A and GRB 201216C to Γ 0 = 204 and Γ 0 = 310, respectively. The present early optical observations are the earliest known observations constraining outflow parameters and our analysis indicate that VHE detected bursts could have a diverse range of observed luminosity within the detectable redshift range of present VHE facilities.