相关论文: Spatio-temporal characterization of Cassiopeia A

We identify a point-symmetric morphology of the supernova remnant (SNR) Cassiopeia A compatible with shaping by at least two, and more likely more than four, pairs of opposite jets, as expected in the jittering jets explosion mechanism…

Supernovae Type-Ia (SNeIa) play a significant role in exploring the history of the expansion of the Universe, since they are the best-known standard candles with which we can accurately measure the distance to the objects. Finding large…

We present a data-driven method based on long short-term memory (LSTM) neural networks to analyze spectral time series of Type Ia supernovae (SNe Ia). The dataset includes 3091 spectra from 361 individual SNe Ia. The method allows for…

The central few parsecs of the Milky Way host a complex X-ray-emitting environment in which several extended plasma components are blended along the line of sight, complicating attempts to measure the intrinsic properties of individual…

The expansion structure of supernova remnants (SNRs) is important for understanding not only how heavy elements are distributed into space, but also how supernovae explode. The ejecta expansion structure of the young core-collapse SNR Cas A…

Using a simplified model for the hadronic emission from young supernova remnants (SNRs), we derive an expression to calculate the hadronic luminosity with time, depending on the SN ejecta density profile and the density structure of the…

ROSAT all-sky survey (RASS) data have provided another window to search for supernova remnants (SNRs). In reexamining this data archive, a list of unidentified extended X-ray objects have been suggested as promising SNR candidate. However,…

We present Spline-based Convolutional Neural Networks (SplineCNNs), a variant of deep neural networks for irregular structured and geometric input, e.g., graphs or meshes. Our main contribution is a novel convolution operator based on…

Identification of anomalous light curves within time-domain surveys is often challenging. In addition, with the growing number of wide-field surveys and the volume of data produced exceeding astronomers ability for manual evaluation,…

Photometry is the most easily acquired information about supernovae. The light curves constructed from regular imaging provide signatures not only for the energy input, the radiation escape, the local environment and the progenitor stars,…

Mapping the physical conditions of the shocked plasma of young supernova remnants (SNR) is crucial for understanding their explosion mechanisms, ejecta structure, and large-scale asymmetries. Using $>350$ ks of XRISM/Resolve high spectral…

Time series data mining is an important field of research in the era of "Big Data". Next generation astronomical surveys will generate data at unprecedented rates, creating the need for automated methods of data analysis. We propose a…

We present a technique to measure lightcurves of time-variable point sources on a spatially structured background from imaging data. The technique was developed to measure light curves of SNLS supernovae in order to infer their distances.…

Kepler's supernova remnant (SNR) which is produced by the most recent naked-eye supernova in our Galaxy is one of the best studied SNRs, but its gamma-ray detection has eluded us so far. Observations with modern imaging atmospheric…

Supernova remnants (SNRs) are among the most important sources of non-thermal X-rays in the sky and likely contributors to Galactic cosmic rays and represent ideal targets to showcase the capabilities of the Imaging X-ray Polarimetry…

The Galactic core-collapse supernova (SN) rate is estimated at $\approx 1-3$ per century; however, no optically visible SN has been discovered in the past 400 years. Although records of the last optically detected SN (Cassiopeia A) are…

We have for the first time measured the overall expansion rate of the supernova remnant Cas A as seen in X-rays using ROSAT and Einstein HRI images with time differences up to almost 17 years. The overall expansion timescale of Cas A is…

We propose CaSPR, a method to learn object-centric Canonical Spatiotemporal Point Cloud Representations of dynamically moving or evolving objects. Our goal is to enable information aggregation over time and the interrogation of object state…

The investigation of extragalactic Supernova Remnants (SNRs) gives us the advantage of surmounting the challenges we are usually confronted with when observing Galactic SNRs, most notably Galactic extinction and distance uncertainties. At…

Gravitationally lensed Type Ia supernovae are an emerging probe with great potential for constraining dark energy, spatial curvature, and the Hubble constant. The multiple images and their time delayed and magnified fluxes may be…