This package evaluates the signatures of diffuse boosted dark matter by supernova neutrinos in the early Universe
Project description
dukes: DiffUse-boosted darK mattEr by Supernova neutrinos
dukes
is a pyhon package for evaluating the signatures of diffuse boosted dark matter by supernova neutrinos in the early Universe based on arXiv:2404.08528.
It also supports an experimental feature that implements particle-model-dependent differential cross sections for DM-neutrino and DM-electron.
Citation
If you use this package or part of the code in your research, please cite the following:
- Yen-Hsun Lin and Meng-Ru Wu, Echoes of darkness: Supernova-neutrino-boosted dark matter from all galaxies, arXiv:2404.08528
dukes
: https://github.com/yenhsunlin/dukes
Installation
To install, excute the following command on the prompt
$ pip install dukes
and everything should be processed on-the-fly.
Dependency
dukes
requires python >= 3.8 and the following packages
numpy
>= 1.20.0scipy
>= 1.10.0vegas
>= 6.0.1
where vegas
is a the backend engine for evaluating multidimensional integrals based on adaptive Monte Carlo vegas algorithm, see its homepage: https://pypi.org/project/vegas/.
Other packages, e.g. gvar
, maybe required by these dependencies during the installation.
The versions of these dependencies are not strict, but are recommended to update to the latest ones to avoid incompatibility.
Usage
We briefly summarize the usage in this section and a comprehensive tutorial can be found in the jupyter notebook in tutorial/tutorial.ipynb
.
To import, do
>>> import dukes
in python terminal and is similar in the jupyter notebook. All module functions named funcname can be called by typing dukes.funcname
.
Examples
Boosted dark matter velocity
A boosted dark matter (BDM) with mass $m_\chi$ and kinetic energy $T_\chi$ has the velocity $v_\chi$,
$$ \frac{v_\chi}{c} = \frac{\sqrt{T_\chi(2m_\chi+T_\chi)}}{m_\chi+T_\chi}. $$
Let $T_\chi=$ Tx
and $=m_\chi=$ mx
, the corresponding function that evaluates $v_\chi/c$ is
>>> Tx,mx = 5,1 # MeV
>>> dukes.vBDM(Tx,mx)
0.9860132971832694
The diffuse BDM flux
The averaged diffuse BDM (DBDM) flux at redshift $z=0$ is given by
$$ \frac{d\Phi_\chi}{dT_\chi} = \frac{v_\chi}{H_0} \int_0^{z_{\rm max}} \frac{dz}{\varepsilon(z)} \int dM_G \frac{d\Gamma_{{\rm SN}}(z)}{dM_G}\frac{d\bar N_\chi(M_G)}{dT_\chi^\prime}. $$
Same as the above example,
>>> dukes.flux(Tx,mx,usefit=True,nitn=10,neval=50000)
4.422705310516041e-08
as in MeV−1 cm−2 s−1.
Throughout the entire package, we have implemented the differential DM-neutrino scattering cross section in CM frame is isotropic and energy-independent
$$
\frac{d\sigma_{\chi \nu}}{d\Omega_{\rm CM}}=10^{-35}{\rm cm^2sr^{-1}}.
$$
The argument usefit
is to turn on/off the fitting function used in obtaining the average supernova position on the galactic plane for galaxy with baryonic mass $M_G$.
If usefit=False
, the function will call galacticDensityProfile
to evaluate the area density for galaxy with arbitrary $M_G$.
It requires quadrature integration quad
from scipy and the computation time surges accordingly, but the accuracy is improved insignificantly.
The arguments nitn
and neval
are passed to vegas
and determine how many chains of iteration and how many numbers to be evaluated in each chain. Increasing them will improve the accuracy of the results but also cost longer computation time. We relegate the detail to vegas
documentation.
Physical constants
We have a class named constant
that contains multiple physical constants and conversion factors frequently used in this package.
For instance, electron mass
>>> dukes.constant.me
0.511
as in MeV and the speed of light
>>> dukes.constant.c
29980000000.0
as in cm s−1. Conversion factors such as converting kiloparsec to centimeters
>>> dukes.constant.kpc2cm
3.085e21
and year to seconds
>>> dukes.constant.year2Seconds
31556926
Scripting
In python script (see tests/dukes_example.py
), one can write
# dukes_example.py
import sys
import dukes
if __name__ == '__main__':
Tx = float(sys.argv[1]) # DM kinetic energy, MeV
mx = float(sys.argv[2]) # DM mass, MeV
vx = dukes.vBDM(Tx,mx) # BDM velocity
print(vx) # Print the BDM velocity
and excute this on the prompt
$ python dukes_example.py 5 1
0.9860132971832694
or whatever style you like!
Bugs and troubleshooting
Please report to the author, Yen-Hsun Lin, via yenhsun@phys.ncku.edu.tw.
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