Introduction
The model DAO focuses on X-ray reflection, which is generally observed in the hard-state (Liu et al. 2023). It computes the reprocessed radiation from disk–corona systems, similar to well-known reflection models such as reflionx (Ross,Fabin 2005.)and xillver (García,Kallman. 2010). The main goal of DAO is to provide an accurate, flexible, and community-accessible reflection code that enables researchers to perform studies tailored to their specific scientific needs.
The model employs the latest version of the photoionization code XSTAR, v2.59, to compute atomic processes, thermal equilibrium, and ionization balance, and incorporates the Feautrier method to solve the radiative transfer. We adopt a constant-density gas with a specified column density under a plane-parallel geometry and azimuthal symmetry. I wrote a User Guide for users and try to keep it updating. Please refer to it for more details about DAO. The simplified results and underlying physics are all included in the guide.
Installation
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Download model
git clone https://github.com/ABHModels/DAO.git
cd DAO
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Create mods file
mkdir mods
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Change HEAsoft path in Makefile
e.g., heasoft/heasoft-6.31.1/x86\_64-pc\-linux-gnu-libc2.17
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Complie model
make
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Run model
./dao.x inputfile
DAO is written in Fortran, and require HEAsoft as external package to generate fits file . The model need a input file to set physic parameters such as ionization parameter, hydrogen density, iron abundance etc. We offer a template in the file ./templates. You can see all parameters in Section 3.1 in User Guide.
Run model by Python
Managing simulations with numerous parameters can be an error-prone task, particularly when testing many different configurations. To simplify this process and help organize the resulting outputs, we provide a Python interface designed to run the model and manage the data systematically. The instructions for using the Python script are provided in Section 3.3 of the User Guide.
Ouput
DAO model will generate 5 main out put data. Extra 2 files include a json file, which store the information of parameters of one calculation, and a input file will be generate if one use Pyhton script to run.
Main output data
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op_spec: The file consists of sequential data blocks, with each block corresponding to a single
iteration. Within each block, the data is organized into the following columns:-
Energy grid values [ev].
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Incident illumination spectrum from the top source
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Incident illumination spectrum from the bottom source (if active)
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Emergent specific intensity along the line of sight (defined by the cosine of the incidence angle, inmu)
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Angle-averaged (flux) spectrum.
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op_inte: This file provides a detailed diagnostic record of the angle-dependent specific intensity,
logging its state at each main iteration step.-
Energy grid, with units of eV
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Columns 2 through 11: The emergent specific intensity for each of the first 10
angle bins. Column 2 contains the intensity for the first angle (μ1), Column 3 for
the second angle (μ2), and so on.
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op_temp:Temperature profile along the vertical direction for each iteration step.
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Column 1: Thomson optical depth.
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Columns 2: Temperature value in K.
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op_abund: As same with xout_abund.fits in xstar.
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op_log: This file contains a detailed log of the entire calculation process, recording the status at
each main iteration step and each subsequent radiative transfer iteration.
Change log
[version 1.1]
Add thermally comptonized continuum (nthcomp) as a type of incident spectrum. When incident type is nthcomp, hcut is used to represent corona temperature in keV. Seed photons’ temperature is fixed at 0.1 keV.
[version 1.0]
First published DAO mdoel