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.post31-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.post31-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.post31-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.post31-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.post31-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.post31-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.post31-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for nupyprop-0.1.7.post31-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 25d1cb4ab89b8216b92f76cb881a424cb68d07a023f53416b33fe451a1de8b07
MD5 61a5e7a451e53865c8cc5e9a024fcfcb
BLAKE2b-256 513bb355ef7da698318b2e3de77281d7c4695769f6187bf2683a21dff81d416e

See more details on using hashes here.

File details

Details for the file nupyprop-0.1.7.post31-cp39-cp39-macosx_10_9_x86_64.whl.

File metadata

  • Download URL: nupyprop-0.1.7.post31-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.post31-cp39-cp39-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 e5c423ff93fdd9a5f983a1b127f87760297bd7f0138e64ca130f5aeb88caa570
MD5 ff0476901251cc2aa99b02a31840f9f4
BLAKE2b-256 96f8934fe54d123584a336155f8cc29a74ea35e9bf23dfdb5921fdcaab5bb364

See more details on using hashes here.

File details

Details for the file nupyprop-0.1.7.post31-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for nupyprop-0.1.7.post31-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 c57bf7e89341311f5b4b9372f16c4e84df43efe30f6a3ea5a7968a2e251b5847
MD5 c03b3bd21b17be4ef9cf181910c2d6a2
BLAKE2b-256 716a792d30cadb2e88dbdfeb4cd62f75f59dc00af84f9d73a044adb998d8c1e9

See more details on using hashes here.

File details

Details for the file nupyprop-0.1.7.post31-cp38-cp38-macosx_10_9_x86_64.whl.

File metadata

  • Download URL: nupyprop-0.1.7.post31-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.post31-cp38-cp38-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 851b36d3926eb33b429b956ba53bf33936a0a354a7a2dd36d44926aeddf4a63f
MD5 371b94278f50f371bc0cc925d6fb26b2
BLAKE2b-256 867e9a669f8c2b5d4da14631e2647cda7fa914b515c62e1cb26f6a0b74370713

See more details on using hashes here.

File details

Details for the file nupyprop-0.1.7.post31-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for nupyprop-0.1.7.post31-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 8d92882665718fffea7b02376bc5aa4fe41e3a1ef40b99d05030b826cc55b37b
MD5 0fef639c2c68ac9800d8fd3ddb3c1466
BLAKE2b-256 6fe78223b51dab0684b938715cc5de458d20bc300d5ca1325e9ef0e1448d33d6

See more details on using hashes here.

File details

Details for the file nupyprop-0.1.7.post31-cp37-cp37m-macosx_10_9_x86_64.whl.

File metadata

  • Download URL: nupyprop-0.1.7.post31-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.post31-cp37-cp37m-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 05deedbddc5d788386ce6abdc5b575b0cef26478d69a46d8153ca3641e328273
MD5 577676db6dbb5884156cf5f5a43fcd6e
BLAKE2b-256 cf67baf1ed94aab7762e15733a890d107022f3ec19d697a7490f89b9b21d396b

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