Publications
Below is a list of my publications. Please feel free to reach out if you have any questions or are interested in potential collaborations.
DAO: A New and Public Non-Relativistic Reflection Model
We present a new non-relativistic reflection model, DAO, designed to calculate reflection spectra in the rest frame of accretion disks in X-ray binaries and active galactic nuclei. The model couples the XSTAR code, which treats atomic processes, with the Feautrier method for solving the radiative transfer equation. A key feature of DAO is the incorporation of a high-temperature corrected cross section and an exact redistribution function to accurately treat Compton scattering. Furthermore, the model accommodates arbitrary illuminating spectra, enabling applications across diverse physical conditions. We investigate the spectral dependence on key physical parameters and benchmark the results against the widely used reflionx and xillver codes.
Neural Network XILLVER model
As parameter spaces grow, astrophysical table models have become excessively large, often consuming gigabytes of memory. This wastes computing resources and slows down the continuum fitting process (Bambi 2024).
My solution is nxillver, a neural network I designed and trained on the xillver model. It shrinks the model's footprint from gigabytes to tens of megabytes and can be integrated into the relxill framework to significantly boost fitting efficiency.
X-ray reflection spectroscopy with improved calculations of the emission angle
We presented a angle-improved model relxillA and fixed the bug in relxill. relxillA wasb designed for next-generation instrument: X-IFU instrument onboard NewAthena (Nandra et al. 2013) and LAD instrument (Zhang et al. 2016).
We compared relxillA with other relxill (García, Dauser et al 2014) and reltrans (Ingram et al. 2019) in this paper and simulated NewAthena/XIFU+LAD with relxill and relxillA. The results showed relxillA solve the large residuals problem as shown in Liu et al 2015.