58 citations · 126 across the 14 of their papers we have counts for
15 papers
High-Redshift Type Ia Supernovae Exhibit Enhanced Calcium Abundances
Xingzhuo Chen, Ulisses Braga-Neto, Lifan Wang
Type Ia supernovae (SNe Ia) are major contributors to cosmic chemical enrichment, and their elemental abundances provide a probe of progenitor properties and explosion physics acro…
A GPU-Accelerated Transient Detection Pipeline for DECam Time-Domain Surveys
Lei Hu, Tomás Cabrera, Antonella Palmese +8
We present a GPU-accelerated transient detection pipeline developed for time-domain surveys with the Dark Energy Camera (DECam). It enables real-time-capable image processing, inco…
Convolution Operator Network for Forward and Inverse Problems (FI-Conv): Application to Plasma Turbulence Simulations
Xingzhuo Chen, Anthony Poole, Ionut-Gabriel Farcas +2
We propose the Convolutional Operator Network for Forward and Inverse Problems (FI-Conv), a framework capable of predicting system evolution and estimating parameters in complex sp…
SEDONA-GesaRaT: an AI-Accelerated Radiative Transfer Program for 3-D Supernova Simulations
Xingzhuo Chen, Ulisses Braga-Neto, Lifan Wang +5
We present SEDONA-GesaRaT, a rapid code for supernova radiative transfer simulation developed based on the Monte-Carlo radiative transfer code SEDONA. We use a set of atomic physic…
Kilonova constraints for the LIGO/Virgo/KAGRA neutron star merger candidate S250206dm: GW-MMADS observations
Lei Hu, Tomás Cabrera, Antonella Palmese +35
Gravitational wave (GW) neutron star mergers with an associated electromagnetic counterpart constitute powerful probes of binary evolution, the production sites of heavy elements,…
Measuring Type Ia Supernova Angular-Diameter Distances with Intensity Interferometry
A. G. Kim, P. E. Nugent, Xingzhuo Chen +2
This paper investigates the potential of intensity interferometry, based on the Hanbury Brown-Twiss effect, for measuring supernova sizes and distances. Through optimized telescope…
An Integral-Based Technique (IBT) to Accelerate the Monte-Carlo Radiative Transfer Computation for Supernovae
Xingzhuo Chen, Lifan Wang, Daniel Kasen
We present an integral-based technique (IBT) algorithm to accelerate supernova (SN) radiative transfer calculations. The algorithm utilizes ``integral packets'', which are calculat…
Artificial Intelligence Assisted Inversion (AIAI): Quantifying the Spectral Features of Ni of Type Ia Supernovae
Xingzhuo Chen, Lifan Wang, Lei Hu +1
Following our previous study of Artificial Intelligence Assisted Inversion (AIAI) of supernova analyses (Chen et al. 2020), we train a set of deep neural networks based on the one-…
Using Physics Informed Neural Networks for Supernova Radiative Transfer Simulation
Xingzhuo Chen, David J. Jeffery, Ming Zhong +3
We use physics informed neural networks (PINNs) to solve the radiative transfer equation and calculate a synthetic spectrum for a Type Ia supernova (SN~Ia) SN 2011fe. The calculati…
Constraints on Cosmological Parameters with a Sample of Type Ia Supernovae from JWST
Jia Lu, Lifan Wang, Xingzhuo Chen +7
We investigate the potential of using a sample of very high-redshift () (VHZ) Type Ia supernovae (SNe~Ia) attainable by the James Webb Space Telescope (JWST)…
Spectroscopic Studies of Type Ia Supernovae Using LSTM Neural Networks
Lei Hu, Xingzhuo Chen, Lifan Wang
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 spe…
Image Subtraction in Fourier Space
Lei Hu, Lifan Wang, Xingzhuo Chen +1
Image subtraction is essential for transient detection in time-domain astronomy. The point spread function (PSF), photometric scaling, and sky background generally vary with time a…
Constraining Type Ia Supernova Delay Time with Spatially Resolved Star Formation Histories
Xingzhuo Chen, Lei Hu, Lifan Wang
We present the delay time distribution (DTD) estimates of Type Ia supernovae (SNe~Ia) using spatially resolved SN~Ia host galaxy spectra from MUSE and MaNGA. By employing a groupin…
Artificial Intelligence Assisted Inversion (AIAI) of Synthetic Type Ia Supernova Spectra
Xingzhuo Chen, Lei Hu, Lifan Wang
We generate 100,000 model spectra of Type Ia Supernovae (SNIa) to form a spectral library for the purpose of building an Artificial Intelligence Assisted Inversion (AIAI) al…
A New Method to Classify Type IIP/IIL Supernovae Based on their Spectra
Xingzhuo Chen, Shihao Kou, Xuewen Liu
Type IIP and type IIL supernovae (SNe) are defined on their light curves, but the spectrum criteria in distinguishing these two type SNe remains unclear. We propose a new classific…