snorer
is a package for evaluating time-of-flight signatures of supernova-neutrino-boosted dark matter (SNν BDM) from our Milky Way (MW), SN1987a in Large Magellanic Cloud (LMC) and SN in arbitrary distant galaxy based on
Phys. Rev. Lett. 130, 111002 (2023) [arXiv:2206.06864]
and
Phys. Rev. D 108, 083013 (2023)
[arXiv:2307.03522].
If you use this package or part of the code in your research, please cite the followings:
- Y.-H. Lin et al., Phys. Rev. Lett. 130, 111002 (2023), arXiv:2206.06864
- Y.-H. Lin et al., Phys. Rev. D 108, 083013 (2023), arXiv:2307.03522
-
snorer
: https://github.com/yenhsunlin/snorer
To install, excute the following command on the prompt
$ pip install snorer
and everything should be processed on-the-fly.
snorer
requires python >= 3.8 and the following external packages
-
numpy
>= 1.20.0 -
scipy
>= 1.10.0 -
vegas
>= 6.0.1 -
astropy
>= 6.0.0
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 maybe required by these dependencies during the installation, see requirements.txt
for details.
The versions of these dependencies are not strict, but are recommended to update to the latest ones to avoid incompatibility.
We briefly summarize the usage in this section and a comprehensive tutorial can be found in the jupyter notebook in examples/tutorial.ipynb
.
To import, do
>>> import snorer
in python terminal and is similar in the jupyter notebook.
All functions and classes can be accessed by typing snorer.foo()
where foo
is the function/class/module name.
We document various useful physical constants and conversion factors...etc as the attributes of the instance snorer.constant
.
For example, we can retrieve
>>> snorer.constant.me # electron mas, MeV
0.511
>>> snorer.constant.kpc2cm # kpc to cm
3.085e+21
We did this instead of naming them as constant variables in some module to prevent them from being edited.
A boosted dark matter (BDM) with mass
Let snorer.get_vx()
to evaluate
>>> Tx,mx = 15,0.075
>>> snorer.get_vx(Tx,mx)
0.9999876239921284
The BDM flux, or afterglow to the
where
The function to evaluate this is snorer.flux()
with
>>> t,Tx,mx,Rstar,beta = 100,15,1e-2,8.5,0
>>> snorer.flux(t,Tx,mx,Rstar,beta,is_spike=True,neval=15000)
4.572295175982701e-16
Users can of course turn off the spike feature by setting is_spike=False
and will find both numerical results are similar.
It implies the contribution to the BDM flux comes from the place outside the spike's influence.
The BDM event number in a detector after exposing to the flux for a period of time,
where snorer.event()
with
Note that this function is normalized to
Now let
>>> mx,Rstar,beta = 0.015,8,0
>>> N_BDM = snorer.event(mx,Rstar,beta,is_spike=False,neval=50000)
>>> N_BDM
1.662174035857532e-06
For Super-Kamiokande, it has
>>> Ne,sigma_xe = 7e33,1e-35
>>> N_BDM*Ne*sigma_xe
1.1635218251002724e-07
The aforementioned functions for evaluating BDM signatures are based on model-agnostic picture. It means the cross sections between dark and visble sectors are generally independent of physical quantities, eg. energy, mass and coupling constants.
The most important feature snorer
carries is that it offers a general interface for users to implement their favorite particle models.
Furthermore, SN is not necessary exploding in our MW or LMC. As long as users can provide these celetial objects' coordinates and expressed them in ICRS J2000.0 metrics, snorer
can do the calculation.
snorer
also allows users to customize the halo shape, by manipulating
This will be done by the class snorer.GeneralInterface
.
All these user-specified features will be composed into an instance of snorer.GeneralInterface
.
The BDM signatures can be evaluated by calling the associated methods within it.
We have an example in examples/tutorial.ipynb
, also see the in-class docstring for more information.
We also provide many useful functions and classes at users' disposal. See examples/tutorial.ipynb
for details.
To evaluate BDM event, snorer
uses vegas
to handle the multidimensional integration.
The sampling method of vegas
cannot manipulate event calculation, e.g. snorer.event()
and the method in the instance of snorer.GeneralInterface
, properly, when SN is exactly at GC with spike and no DM self-annihilation.
Since the spike is a highly singular behavior, the sampling method may miss the substantial DM contribution from the inner galactic region and causes underestimate of
To be fair, the probability of a very cuspy DM spike surving the gravitational disturbance without annihilating away and SN happening exactly at the GC might be very rare.
This issue is scheduled to fix in the next major update of snorer
.
Please report to the author, Yen-Hsun Lin, via yenhsun@phys.ncku.edu.tw.