Bao Wang

Type Ic broad-line supernovae (SNe Ic-BL) are often associated with energetic explosions that display a prompt outburst of high-energy emission. Since their progenitor lost the H and He envelopes before the explosion exposing the C/O core, their explosion dynamics and geometry can be seen in an unobscured and undistorted way. We present imaging polarimetry and spectropolarimetry of the Type Ic-BL SN 2026gzf obtained 4.6 and 16.5 days after the X-ray shock breakout, which was recorded by the Einstein Probe satellite as EP260321a, showing it to be one of the softest and intrinsically dimmest extragalactic fast X-ray transients. The persistent low continuum polarization indicates that the outer layer of SN 2026gzf is mostly spherical, suggesting the explosion did not significantly disrupt the progenitor envelope. At day 16.5, the calcium near-infrared triplet displays a peak polarization above 1.5%. The geometry of the associated line opacity is also compatible with an axisymmetric configuration. The spatial distribution of such oxygen-burning ashes thus indicates the presence of a symmetry axis of the excitation structure within the nearly spherical ejecta. The Ca , II triplet polarization is dominated by a primary component spanning ∼25,000–40,000 km s ⁻¹ , while a possible high-velocity polarization substructure of modest statistical significance may indicate a complex, nonaxisymmetric excitation geometry in the outer ejecta. By implementing a three-dimensional Monte Carlo calculation, we infer that a viewing angle of ∼40 ^∘ from the symmetry axis of the excitation structure could plausibly reproduce the observed spectral and polarization profiles of the Ca II triplet.

Fast radio bursts (FRBs) and gamma-ray bursts (GRBs) are both linked to compact-object activity, yet their possible connection remains unclear. Here we perform a systematic search for spatial and temporal associations between FRBs in the second CHIME/FRB catalog and Swift GRBs. Instead of using the positional ellipses reported in the catalog, the full CHIME localization probability maps are adopted for spatial cross-matching. This yields 130 candidate pairs and increases the number of spatially consistent matches by a factor of several. Applying a distance-consistency criterion based on dispersion-measure-inferred FRB redshifts and GRB distances inferred via the Amati relation reduces the sample to 37 pairs, including 26 GRB-preceding-FRB candidates (24 LGRB–FRB and 2 SGRB–FRB). Monte Carlo simulations show that the overall excess of associations is not statistically significant, and the distribution of matches across localization confidence levels is consistent with random expectations. These pairs are therefore not claimed as secure associations, but are used to constrain a possible subdominant FRB–GRB connection. These results place constraints on any FRB–GRB connection and highlight the need for improved localization and larger samples.

Flow matching-based generative models have been integrated into the plug-and-play image restoration framework, and the resulting plug-and-play flow matching (PnP-Flow) model has achieved some remarkable empirical success for image restoration. However, the theoretical understanding of PnP-Flow lags its empirical success. In this paper, we derive a continuous limit for PnP-Flow, resulting in a stochastic differential equation (SDE) surrogate model of PnP-Flow. The SDE model provides two particular insights to improve PnP-Flow for image restoration: (1) It enables us to quantify the error for image restoration, informing us to improve step scheduling and regularize the Lipschitz constant of the neural network-parameterized vector field for error reduction. (2) It informs us to accelerate off-the-shelf PnP-Flow models via extrapolation, resulting in a rescaled version of the proposed SDE model. We validate the efficacy of the SDE-informed improved PnP-Flow using several benchmark tasks, including image denoising, deblurring, super-resolution, and inpainting. Numerical results show that our method significantly outperforms the baseline PnP-Flow and other state-of-the-art approaches, achieving superior performance across evaluation metrics.

Fast radio bursts (FRBs) are mysterious millisecond-duration radio transients of extragalactic origin. Some of them repeat, while others apparently do not. Investigations of periodic activity in repeating FRB have been conducted to probe their origins. While periodicity in the burst rate has been reported, studies of periodicities in other properties, such as dispersion measure and rotation measure (RM), are sparse. FRB 20220529 was monitored by the Five-hundred-meter Aperture Spherical radio Telescope for nearly 3 yr, providing an opportunity to investigate periodicity in its observed properties. Here we report a possible period of ∼200 days in the RM evolution, with a significance of 4.1 σ estimated via the Lomb–Scargle algorithm and 3.1 σ with the phase-folding method. Periodicity in the burst rate was also investigated. It may indicate that the FRB progenitor is in a binary system, which is consistent with the significant RM increase and prompt recovery of this FRB on a week timescale. Other scenarios, such as a system with an intermediate-mass black hole, are also explored.

Decentralized federated learning (DFL) uses peer-to-peer communication to avoid the single point of failure problem in federated learning and has been considered an attractive solution for machine learning tasks on distributed devices. We provide the first solution to a fundamental network problem of DFL: what overlay network should DFL use to achieve fast training of highly accurate models, low communication, and decentralized construction and maintenance? Overlay topologies of DFL have been investigated, but no existing DFL topology includes decentralized protocols for network construction and topology maintenance. Without these protocols, DFL cannot run in practice. This work presents an overlay network, called FedLay, which provides fast training and low communication cost for practical DFL. FedLay is the first solution for constructing near-random regular topologies in a decentralized manner and maintaining the topologies under node joins and failures. Experiments based on prototype implementation and simulations show that FedLay achieves the fastest model convergence and highest accuracy on real datasets compared to existing DFL solutions while incurring small communication costs and being resilient to node joins and failures.

The dispersion measures of fast radio bursts have been identified as a powerful tool for testing the zero-mass hypothesis of the photon. The classical approach treats the massive photon-induced and plasma-induced time delays as two separate phenomena. Recently, Y.-B. Wang et al. suggested that the joint influence of the nonzero photon mass and plasma effects should be considered, and proposed a revised time delay for massive photons propagating in a plasma medium, denoted as Δ t m γ ′ ∝ ν − 4 , which departures from the classical dispersion relation (∝ν ⁻²). Here we discuss the derivation presented by Y.-B. Wang et al. and show that the classical dispersion relation remains valid based on Proca equations.

We compare, with data from quasars, Hubble parameter measurements, and Pantheon+ type Ia supernova, three different relations between X-ray luminosity (L _X) and ultraviolet luminosity (L _UV) of quasars. These three relations consist of the standard and two redshift-evolutionary L _X–L _UV relations, which are constructed, respectively, by considering a redshift-dependent correction to the luminosities of quasars and using the statistical tool copula. By employing the PAge approximation for a cosmological model–independent description of the cosmic background evolution and dividing the quasar data into the low-redshift and high-redshift parts, we find that the constraints on the PAge parameters from the low-redshift and high-redshift data, which are obtained with the redshift-evolutionary relations, are consistent with each other, while they are not when the standard relation is considered. If the data are used to constrain the coefficients of the relations and the PAge parameters simultaneously, then the observations support the redshift-evolutionary relations at more than 3σ. The Akaike and Bayes information criteria indicate that there is strong evidence against the standard relation and mild evidence against the redshift-evolutionary relation constructed by considering a redshift-dependent correction to the luminosities of quasars. This suggests that the redshift-evolutionary L _X–L _UV relation of quasars constructed from copula is favored by the observations.