相关论文: Interpolating Detailed Simulations of Kilonovae: A…
Accurate PET imaging increasingly requires methods that support unconstrained detector layouts from walk-through designs to long-axial rings where gaps and open sides lead to severely undersampled sinograms. Instead of constraining the…
We present advances in modeling Type IIP supernovae using MESA for evolution to shock breakout coupled with STELLA for generating light and radial velocity curves. Explosion models and synthetic light curves can be used to translate…
A key step in any resonant anomaly detection search is accurate modeling of the background distribution in each signal region. Data-driven methods like CATHODE accomplish this by training separate generative models on the complement of each…
The polynomial kernels are widely used in machine learning and they are one of the default choices to develop kernel-based classification and regression models. However, they are rarely used and considered in numerical analysis due to their…
Satellite observations play a critical role in numerical weather prediction where they are assimilated through an observation operator that maps model states to radiances. In the traditional Ensemble Kalman Filter, these observations are…
The supernova remnants left behind by Type Ia supernovae provide an excellent opportunity for the study of these enigmatic objects. In a previous work, we showed that it is possible to use the X-ray spectra of young Type Ia supernova…
Recently, artificial neural networks have been gaining momentum in the field of gravitational wave astronomy, for example in surrogate modelling of computationally expensive waveform models for binary black hole inspiral and merger.…
We present a novel projection-based model reduction framework for parametric linear time-invariant systems that allows interpolating the transfer function at a given frequency point along parameter-dependent curves as opposed to the…
In this paper, we discuss a novel model reduction framework for generalized linear systems. The transfer functions of these systems are assumed to have a special structure, e.g., coming from second-order linear systems and time-delay…
The electromagnetic transients accompanying compact binary mergers ($\gamma$-ray bursts, afterglows and 'macronovae') are crucial to pinpoint the sky location of gravitational wave sources. Macronovae are caused by the radioactivity from…
Molecular simulations can provide microscopic insight into the physical and chemical driving forces of complex molecular processes. Despite continued advancement of simulation methodology, model errors may lead to inconsistencies between…
Machine learning models of accelerator systems (`surrogate models') are able to provide fast, accurate predictions of accelerator physics phenomena. However, approaches to date typically do not include measured input diagnostics, such as…
Super-resolution of LiDAR range images is crucial to improving many downstream tasks such as object detection, recognition, and tracking. While deep learning has made a remarkable advances in super-resolution techniques, typical…
We estimate systematic errors due to K-corrections in standard photometric analyses of high redshift Type Ia supernovae. Errors due to K-correction occur when the spectral template model underlying the lightcurve fitter poorly represents…
We compare parameters of well-observed type II SN1999em derived by M.Hamuy and D.Nadyozhin based on Litvinova-Nadyozhin (1985) analytic fits with those found from the simulations with our radiative hydro code Stella. The difference of SN…
We present radiative transfer simulations for blue kilonovae hours after neutron star (NS) mergers by performing detailed opacity calculations for the first time. We calculate atomic structures and opacities of highly ionized elements (up…
Polarization has been detected at early times for all types of supernova, indicating that such systems result from or quickly develop some form of asymmetry. In addition, the detection of strong line polarization in supernovae is suggestive…
Radiation transport codes are often used in astrophysics to construct spectral models. In this work we demonstrate how producing these models for a time series of data can provide unique information about supernovae (SNe). Unlike previous…
Follow-up of gravitational-wave events by wide-field surveys is a crucial tool for the discovery of electromagnetic counterparts to gravitational wave sources, such as kilonovae. Machine learning tools can play an important role in aiding…
Image interpolation is a special case of image super-resolution, where the low-resolution image is directly down-sampled from its high-resolution counterpart without blurring and noise. Therefore, assumptions adopted in super-resolution…