Skip to main content

This package evaluates the time-of-flight signatures of boosted dark matter due to supernova neutrinos from our Milky Way

Project description

Python License ArXiv ArXiv

snorer: Supernova-Neutrino-bOosted daRk mattER

Version API Docs

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].

Citation

If you use this package or part of the code in your research, please cite the followings:

  1. Y.-H. Lin et al., Phys. Rev. Lett. 130, 111002 (2023), arXiv:2206.06864
  2. Y.-H. Lin et al., Phys. Rev. D 108, 083013 (2023), arXiv:2307.03522
  3. snorer: https://github.com/yenhsunlin/snorer/

Installation

To install, excute the following command on the prompt

$ pip install snorer

and everything should be processed on-the-fly.

Dependency

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.

snorer Document

See the snorer documentation: https://yenhsunlin.github.io/snorer/ for more details.

Known Issue

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.BoostedDarkMatter, 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 $N_{\rm BDM}$ plus unstable results. To avoid this, users may try to displace the SN from GC a little bit when evaluating $N_{\rm BDM}$ with DM sipke and no DM annihilation. For BDM flux evaluation, there is no such issue.

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 future update.

Bugs and Troubleshooting

Please report to the author, Yen-Hsun Lin, via yenhsun@phys.ncku.edu.tw.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

snorer-2.1.0.tar.gz (64.0 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

snorer-2.1.0-py3-none-any.whl (59.0 kB view details)

Uploaded Python 3

File details

Details for the file snorer-2.1.0.tar.gz.

File metadata

  • Download URL: snorer-2.1.0.tar.gz
  • Upload date:
  • Size: 64.0 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.12.2

File hashes

Hashes for snorer-2.1.0.tar.gz
Algorithm Hash digest
SHA256 2dad32688f396b2fc3566cd16065aaf76a52950d200126d451684d67775b6b0c
MD5 96da3e8bc7ea3e4f89215b69e8ac4508
BLAKE2b-256 33e1ff0fe15c4d3a816f9fb698bd90732be629407ce33b7fdaaab679e7292e2b

See more details on using hashes here.

File details

Details for the file snorer-2.1.0-py3-none-any.whl.

File metadata

  • Download URL: snorer-2.1.0-py3-none-any.whl
  • Upload date:
  • Size: 59.0 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.12.2

File hashes

Hashes for snorer-2.1.0-py3-none-any.whl
Algorithm Hash digest
SHA256 698f90235a00d63fe198358d515d11b35a98b0351889dd75c371ed0c5174ce78
MD5 8f9193d5b6730efac6de79ee708a8c22
BLAKE2b-256 0f2300e537699f58b7e705ad53f16dc211e5203c51301adcf114d5410e3717e9

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page