Skip to main content

A simulator for neutrino propagation through the earth.

Project description

Propagate neutrinos through the earth.

A python package and command line utility, including fortran for performance with openMP.

Installation

with pip

python3 -m pip install nupyprop

with conda

We recommend installing nupyprop into a conda environment like so. In this example the name of the environment is “nupyprop”

conda create -n nupyprop -c conda-forge -c nuspacesim nupyprop
conda activate nupyprop

Usage

nupyprop --help

Example for running tau propagation for 107 GeV neutrinos at 10 degrees with a statistics of 107 particles with stochastic energy loss & with all other parameters as defaults:

nupyprop -e 7 -a 10 -t stochastic -s 1e7

Run parameters are defined in run.py. Different switches are described as follows:

  1. -e or –energy: incoming neutrino energy in log_10(GeV). Works for single energy or multiple energies. For multiple energies, separate energies with commas eg. 7,8,9,10,11. Default energies are 107,107.25,107.5,…1011 GeV.

  2. -a or –angle: slant Earth angles in degrees. Works for single angle or multiple angles. For multiple angles, separate angles with commas eg. 1,3,5,7,10. Default angles are 1->35 degrees, in steps of 1 degree.

  3. -i or –idepth: depth of ice/water in km. Default value is 4 km.

  4. -l or –lepton: flavor of lepton used to propagate. Can be either muon or tau. Default is tau.

  5. -n or –nu_type: type of neutrino matter. Can be either neutrino or anti-neutrino. Default is Neutrino.

  6. -t or –energy_loss: energy loss type for lepton - can be stochastic or continuous. Default is stochastic.

  1. -x or –xc_model: neutrino/anti-neutrino cross-section model used. For a list of model names, see lookup_tables.h5/Neutrino_Cross_Sections. Default is ct18nlo.

  2. -p or –pn_model: photonuclear interaction energy loss model used. For now, can be either bb (Bezrukov-Bugaev), allm (Abramowicz, Levin, Levy, Maor), bdhm (Block, Durand, Ha, McKay) or ckmt (Capella, Kaidalov, Merino, Tran). Default is allm.

  3. -f or –fac_nu: rescaling factor for SM cross-sections. Default is 1.

  4. -s or –stat: statistics. Default is 1e7 particles.

[STRIKEOUT:WARNING: Running the code will replace the results of the output.h5 file. Backing up previous output files is recommended (or just ask me for a pre-populated output file if need be, for now, since the pre-populated output file is >25 MB). Future fixes include overwrite warnings for the user.] Fixed!

Viewing output results: output_*.h5 will contain the results of the code after it has finished running. In the terminal, run vitables and open the output_*.h5 file to view the output results.

output_*.h5 naming convention is as follows: output_A_B_C_D_E_F_G, where

A = Neutrino type: nu is for neutrino & anu is for anti-neutrino. B = Lepton_type: tau is for tau leptons & muon is for muons. C = idepth: depth of water layer in km. D = Neutrino (or anti-neutrino) cross-section model. E = Lepton photonuclear energy loss model. F = Energy loss type: can be stochastic or continuous. G = Statistics (ie. no. of neutrinos/anti-neutrinos injected).

Code Execution Timing Table for Taus:

Charged Lepton

Energy Loss Type

E|nu| [GeV]

Angles

N|nu|;;in

Time (hrs)

τ

Stochastic

107

1-35

108

1.07*, 0.26***

τ

Continuous

107

1-35

108

0.88*

τ

Stochastic

108

1-35

108

6.18*, 1.53***

τ

Continuous

108

1-35

108

5.51*

τ

Stochastic

109

1-35

108

27.96*, 5.08***

τ

Continuous

109

1-35

108

19.11*

τ

Stochastic

1010

1-35

108

49.80*, 12.43***

τ

Continuous

1010

1-35

108

35.59*

τ

Stochastic

1011

1-35

108

12.73***

τ

Continuous

1011

1-35

108

Code Execution Timing Table for Muons:

Charged Lepton

Energy Loss Type

E|nu| [GeV]

Angles

N|nu|;;in

Time (hrs)

μ

Stochastic

106

1,2,3,5,7,10,12,15,17,20,25,30,35

108

μ

Continuous

106

1,2,3,5,7,10,12,15,17,20,25,30,35

108

0.95*

μ

Stochastic

107

1,2,3,5,7,10,12,15,17,20,25,30,35

108

μ

Continuous

107

1,2,3,5,7,10,12,15,17,20,25,30,35

108

3.19*

μ

Stochastic

108

1,2,3,5,7,10,12,15,17,20,25,30,35

108

μ

Continuous

108

1,2,3,5,7,10,12,15,17,20,25,30,35

108

5.17*

μ

Stochastic

109

1,2,3,5,7,10,12,15,17,20,25,30,35

108

111.77**

μ

Continuous

109

1,2,3,5,7,10,12,15,17,20,25,30,35

108

7.42*

μ

Stochastic

1010

1,2,3,5,7,10,12,15,17,20,25,30,35

108

98.17*

μ

Continuous

1010

1,2,3,5,7,10,12,15,17,20,25,30,35

108

9.76*

μ

Stochastic

1011

1,2,3,5,7,10,12,15,17,20,25,30,35

108

μ

Continuous

1011

1,2,3,5,7,10,12,15,17,20,25,30,35

108

* - Intel Core i7-8750H; 6 cores & 12 threads. ** - Intel Core i5-10210; 4 cores & 8 threads. *** - UIowa Argon cluster; 56 cores.

For debugging/development: The correct order to look at the code is in the following order:

  1. data.py: contains the reading/writing modules from/to the hdf5 files.

  2. geometry_py.py: contains the Earth geometry modules (including PREM) for use with python.

  3. cross_section.py: contains neutrino/anti-neutrino cross_section models.

  4. energy_loss.py: contains lepton energy loss models.

  5. propagate.f90: heart of the code; contains fortran modules to interpolate between geometry variables, cross-sections, energy loss parameters & propagate neutrinos and leptons through the Earth.

  6. main.py: forms the main skeleton of the code; propagates the neutrinos and leptons, and calculates the p_exit and collects outgoing lepton energies.

  7. run.py: contains all the run parameters and variables needed for all the other .py files.

UML Diagram

UML Diagram

Developing the code on Ubuntu

These notes should help developers of this code build and install the package locally using a pep518 compliant build system (pip).

  1. Install the non-pypi required dependencies as described for users above.

  2. Install a fortran compiler. ex: sudo apt-get install gfortran

  3. git clone the source code: git clone git@github.com:NuSpaceSim/nupyprop.git

  4. cd nupyprop

  5. build and install the package in ‘editable’ mode python3 -m pip install -e .

Developing the code on MacOS

These notes should help developers of this code build and install the package locally using a pep518 compliant build system (pip). Currently we do not support the default system python3 on MacOS which is out of date and missing critical functionality. Use the homebrew python instead, or a virtualenv, or a conda environment.

  1. Install the non-pypi required dependencies as described for users above.

  2. Install a fortran compiler. ex: brew install gcc

  3. git clone the source code: git clone git@github.com:NuSpaceSim/nupyprop.git

  4. cd nupyprop

  5. build and install the package in ‘editable’ mode python3 -m pip install -e .

https://hitcounter.pythonanywhere.com/count/tag.svg?url=https%3A%2F%2Fgithub.com%2FNuSpaceSim%2Fnupyprop

Project details


Release history Release notifications | RSS feed

Download files

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

Source Distributions

No source distribution files available for this release.See tutorial on generating distribution archives.

Built Distributions

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

nupyprop-0.1.7.post29-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (4.8 MB view details)

Uploaded CPython 3.9manylinux: glibc 2.17+ x86-64

nupyprop-0.1.7.post29-cp39-cp39-macosx_10_9_x86_64.whl (4.8 MB view details)

Uploaded CPython 3.9macOS 10.9+ x86-64

nupyprop-0.1.7.post29-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (4.8 MB view details)

Uploaded CPython 3.8manylinux: glibc 2.17+ x86-64

nupyprop-0.1.7.post29-cp38-cp38-macosx_10_9_x86_64.whl (4.8 MB view details)

Uploaded CPython 3.8macOS 10.9+ x86-64

nupyprop-0.1.7.post29-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (4.8 MB view details)

Uploaded CPython 3.7mmanylinux: glibc 2.17+ x86-64

nupyprop-0.1.7.post29-cp37-cp37m-macosx_10_9_x86_64.whl (4.8 MB view details)

Uploaded CPython 3.7mmacOS 10.9+ x86-64

File details

Details for the file nupyprop-0.1.7.post29-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for nupyprop-0.1.7.post29-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 5e5cbb0b10df17b625f3b4d16003ab27d18e1cfe80c6d4e2afdf2269245b84e7
MD5 02a68d6456b443f0fd8bb0abc9e1cd64
BLAKE2b-256 1bd8b9ebc072b7767bf4e31b7133941a9b9c34f1c18be2ce79be69df52da1e74

See more details on using hashes here.

File details

Details for the file nupyprop-0.1.7.post29-cp39-cp39-macosx_10_9_x86_64.whl.

File metadata

  • Download URL: nupyprop-0.1.7.post29-cp39-cp39-macosx_10_9_x86_64.whl
  • Upload date:
  • Size: 4.8 MB
  • Tags: CPython 3.9, macOS 10.9+ x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.4.2 importlib_metadata/4.6.1 pkginfo/1.7.1 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.61.2 CPython/3.9.6

File hashes

Hashes for nupyprop-0.1.7.post29-cp39-cp39-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 f2fbc890b424538944954a92670ada7aec9d0c978c63a63e1d24a514dcae0c0b
MD5 04ebc97db064cef6065dd8359dec7a8a
BLAKE2b-256 8a331d800be39997a78e506e657e182390223eb03cb05654a0177ca297dd5450

See more details on using hashes here.

File details

Details for the file nupyprop-0.1.7.post29-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for nupyprop-0.1.7.post29-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 31441b1f83e68199c65d79271fcec5fe3b364908c74168d92c86014a9c41cff3
MD5 a48205a13034211315d99874f5e3906a
BLAKE2b-256 0bb643d1047cdb405de7208f385ae16095d54ba6ba5a73890d3b6bc0b35fabf6

See more details on using hashes here.

File details

Details for the file nupyprop-0.1.7.post29-cp38-cp38-macosx_10_9_x86_64.whl.

File metadata

  • Download URL: nupyprop-0.1.7.post29-cp38-cp38-macosx_10_9_x86_64.whl
  • Upload date:
  • Size: 4.8 MB
  • Tags: CPython 3.8, macOS 10.9+ x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.4.2 importlib_metadata/4.6.1 pkginfo/1.7.1 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.61.2 CPython/3.9.6

File hashes

Hashes for nupyprop-0.1.7.post29-cp38-cp38-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 e8568c0873725a3f0807f8c5167aa882fb7db80566119a6b7db198c1bb802d9e
MD5 cfced73fb26af8e0093e8fe7db6c62d7
BLAKE2b-256 517550e6c39d80a9f6a2ffc02c334844b3231648f2149d72e767a8457c689887

See more details on using hashes here.

File details

Details for the file nupyprop-0.1.7.post29-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for nupyprop-0.1.7.post29-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 1a6ecaa96eca62077ebebac74fae62f5bb00d7f1cf4a418db6feb9a6781d8016
MD5 9503eb577faf5b4a4f88d99e2114bac9
BLAKE2b-256 fc0713543ca122863e50182a5f8d23828fcd812f22b04d40c3b49fa6f1ebae93

See more details on using hashes here.

File details

Details for the file nupyprop-0.1.7.post29-cp37-cp37m-macosx_10_9_x86_64.whl.

File metadata

  • Download URL: nupyprop-0.1.7.post29-cp37-cp37m-macosx_10_9_x86_64.whl
  • Upload date:
  • Size: 4.8 MB
  • Tags: CPython 3.7m, macOS 10.9+ x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.4.2 importlib_metadata/4.6.1 pkginfo/1.7.1 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.61.2 CPython/3.9.6

File hashes

Hashes for nupyprop-0.1.7.post29-cp37-cp37m-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 6fb0f94cb65c5abd2106301f7f2297f9931f4bc44717aba3258a19bc7ec88868
MD5 bdb0357500fc0864bfe62c1132463e25
BLAKE2b-256 2e8ee0c15765a83dd0fbea5d004336dd5031aeef18d281f8ed44062d4326ae66

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