https://github.com/scikit-hep/particle

Package to deal with particles, the PDG particle data table, PDGIDs, etc.
https://github.com/scikit-hep/particle
analysis hep high-energy-physics particle particle-physics pdg pid scikit-hep
Last synced: about 2 months ago
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Package to deal with particles, the PDG particle data table, PDGIDs, etc.
Host: GitHub
URL: https://github.com/scikit-hep/particle
Owner: scikit-hep
License: bsd-3-clause
Created: 2018-11-20T09:32:10.000Z (over 6 years ago)
Default Branch: main
Last Pushed: 2025-05-12T09:32:47.000Z (2 months ago)
Last Synced: 2025-05-12T10:41:41.122Z (2 months ago)
Topics: analysis, hep, high-energy-physics, particle, particle-physics, pdg, pid, scikit-hep
Language: Python
Homepage:
Size: 1.86 MB
Stars: 154
Watchers: 6
Forks: 25
Open Issues: 10
Metadata Files:
- Readme: README.md
- Contributing: CONTRIBUTING.md
- License: LICENSE
- Citation: CITATION.cff
- Zenodo: .zenodo.json
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README

        

# Particle: PDG particle data and identification codes

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Particle provides a pythonic interface to the [Particle Data Group](http://pdg.lbl.gov/) (PDG)

particle data tables and particle identification codes,

with extended particle information and extra goodies.

The PDG defines the standard particle identification (ID) numbering scheme.

The package provides the `PDGID` class implementing queries on those PDG IDs.

The queries are also accessible through free standing functions mimicking,

and expanding from, the HepPID/HepPDT C++ interface.

The `Particle` class wraps the information in the PDG particle data tables and

provides an object-oriented interface and powerful search and look-up utilities.

## Installation

Install `particle` like any other Python package:

```bash

python -m pip install particle

```

or similar (use `--user`, `virtualenv`, etc. if you wish).

## Strict dependencies

- [Python](http://docs.python-guide.org/en/latest/starting/installation/) (3.8+)

- [importlib_resources backport](http://importlib-resources.readthedocs.io/en/latest/) if using Python < 3.9

- [attrs](http://www.attrs.org/en/stable/) provides classes without boilerplate (similar to DataClasses in Python 3.7)

- [hepunits](https://github.com/scikit-hep/hepunits)\_ provides units for the Scikit-HEP packages

## Changelog

See the [changelog](https://github.com/scikit-hep/particle/blob/main/docs/CHANGELOG.md) for a history of notable changes.

## Getting started: PDG IDs

```python

>>> from particle import PDGID

>>>

>>> pid = PDGID(211)

>>> pid

>>> pid.is_meson

True

>>> pid = PDGID(99999999)

>>> pid

```

For convenience, all properties of the `PDGID` class are available as standalone functions that work on any SupportsInt (including `Particle`):

```python

>>> from particle.pdgid import is_meson

>>>

>>> is_meson(211)

True

```

These composable functions qualifying PDG IDs make it easy to classify particles.

For the sake of example, quarkonia can be specified with the following user-defined functions:

```python

>>> is_heavy_flavor = lambda x: has_charm(x) or has_bottom(x) or has_top(x)

>>> is_quarkonium = lambda x: is_meson(x) and is_heavy_flavor(x) and Particle.from_pdgid(x).is_self_conjugate

```

PDG ID literals provide (`PDGID` class) aliases for all particles loaded, with easily recognisable names.

For example:

```python

>>> from particle.pdgid import literals as lid

>>>

>>> lid.pi_plus

>>>

>>> from particle.pdgid.literals import Lambda_b_0

>>> Lambda_b_0

>>> Lambda_b_0.has_bottom

True

```

You can quickly display `PDGID` info from the command line with:

```bash

$ python -m particle pdgid 323

A              None

J              1.0

L              0

S              1

Z              None

abspid         323

charge         1.0

has_bottom     False

...

```

Similarly, classes exist to express identification codes used by MC programs, see information on converters below.

## Getting started: Particles

You can use a variety of methods to get particles. If you know the PDG ID number or, say, the name used in EvtGen, you can get a particle directly.

```python

>>> from particle import Particle

>>> Particle.from_pdgid(211)

>>>

>>> Particle.from_evtgen_name("J/psi")

>>>

>>> Particle.from_nucleus_info(a=12, z=6)

```

A similar method exists to get a list of particles from a PDG style name:

```python

>>> Particle.findall(pdg_name="pi")

```

returns the list of matching particles whose PDG name is "pi",

which in this case comprises the three charged states of the pseudoscalar pion.

Else, and more generally, you can use a search. A basic example is the following:

```python

>>> next(Particle.finditer('pi'))  # first item in iterator of particles

>>>

>>> Particle.findall('pi')[0]  # Same as above but returning a list of particles

```

You can search for the properties using keyword arguments, which include

`pdg_name`, `name`, `mass`, `width`, `charge`, `three_charge`, `anti_flag`, `rank`,

`I`, `J`, `G`, `P`, `quarks`, `status`,

`mass_upper`, `mass_lower`, `width_upper`, and `width_lower`.

You can pass a callable or an exact match for any property.

The argument `particle` can be set to `True`/`False`, as well,

to limit the search to particles or antiparticles.

You can also build the search yourself with the first positional

argument, which accepts a callable that is given the particle object itself.

If the first positional argument is a string, that will match against the

particle's `name`.

Here are possible sophisticated searches, all of which work with either

`Particle.findall` or `Particle.finditer`, where the former method provides a list

whereas the latter returns an iterator.

```python

>>> # Print out all particles with asymmetric decay width uncertainties

>>> ps = Particle.finditer(lambda p: p.width_lower != p.width_upper)

>>> for p in ps:

...     print(p.name, p.pdgid, p.width_lower, p.width_upper)

>>>

>>> # Find all antiparticles with 'Omega' in the name

>>> Particle.finditer('Omega', particle=False)   # several found

>>>

>>> # Find all antiparticles of name=='Omega'

>>> Particle.finditer(name='Omega', particle=False)  # none found

>>>

>>> # Find all antiparticles of pdg_name=='Omega'

>>> Particle.findall(pdg_name='Omega', particle=False)  # only 1, of course

[]

>>>

>>> # Find all neutral beauty hadrons

>>> Particle.findall(lambda p: p.pdgid.has_bottom and p.charge==0)

>>>

>>> # Find all strange mesons with c*tau > 1 meter

>>> from hepunits import meter

>>> Particle.findall(lambda p: p.pdgid.is_meson and p.pdgid.has_strange and p.ctau > 1 * meter, particle=True)

[,

    ]

```

Once you have a particle, any of the properties can be accessed, along with several methods.

Though they are not real properties, you can access `is_name_barred`, and `spin_type`.

You can also `.invert()` a particle.

There are lots of printing choices for particles:

`describe()`, `programmatic_name`, `latex_name`, `html_name`, HTML printing outs in notebooks,

and of course `repr` and `str` support.

You can get the `.pdgid` from a particle, as well.

Sorting particles will put lowest `abs(PDGID)` first.

Particle literals provide (`Particle` class) aliases for the particles loaded,

with easily recognisable names. For example:

```python

>>> from particle import literals as lp

>>> lp.pi_plus

>>>

>>> from particle.literals import Lambda_b_0

>>> Lambda_b_0

>>> Lambda_b_0.J

0.5

```

You can quickly search for particles from the command line with

(note: quotes may be used/needed but only double quotes work as expected on Windows):

```bash

$ python -m particle search "K*0"

```

If you only select one particle, either by a search or by giving the PDG ID number,

you can see more information about the particle:

```bash

$ python -m particle search 311

Name: K0             ID: 311          Latex: $K^{0}$

Mass  = 497.611 ± 0.013 MeV

Width = -1.0 MeV

Q (charge)        = 0       J (total angular) = 0.0      P (space parity) = -

C (charge parity) = ?       I (isospin)       = 1/2      G (G-parity)     = ?

    SpinType: SpinType.PseudoScalar

    Quarks: dS

    Antiparticle name: K~0 (antiparticle status: Barred)

```

### Advanced: Loading custom tables

You can control the particle data tables if you so desire. You can append a new data table using the following syntax:

```python

>>> from particle import Particle

>>> Particle.load_table('new_particles.csv', append=True)

```

You can also replace the particle table entirely with `append=False` (the default).

If you want a non-default data file distributed with the package just proceed as follows:

```python

>>> from particle import data

>>> Particle.load_table(data.basepath / "particle2024.csv"))

>>> Particle.load_table(data.basepath / "nuclei2022.csv"), append=True)  # I still want nuclei info

>>> Particle.table_names()  # list the loaded tables

```

### Advanced: how to create user-defined particles

There are situations where it may be handy to create user-defined particles.

But do so with care and having in mind the limitations, many of which are discussed or exemplified below!

The simplest "particle" one may create is effectively a placeholder with no real information stored:

```python

>>> # A Particle instance the simplest possible. Contains basically no info

>>> p = Particle.empty()

>>> p

>>>

>>> print(p.describe())

Name: Unknown

```

A more useful particle definition will likely involve at least a name and a PDG ID.

It is important to keep in mind that a meaningful PDG ID encodes by construction internal quantum numbers

and other information. As such, the definition of a particle with a "random" PDG ID

will result in a particle with undefined and/or wrong properties such as quantum numbers or the quality of being a meson.

```python

>>> p2 = Particle(9912345, 'MyPentaquark')

>>> p2

>>>

>>> p2.pdgid.is_pentaquark

False

>>> print(p2.describe())  # J=2 is an example of something effectively encoded in the PDG ID.

Name: MyPentaquark   ID: 9912345      Latex: $Unknown$

Mass  = None

Width = None

Q (charge)        = None    J (total angular) = 2.0      P (space parity) = None

C (charge parity) = None    I (isospin)       = None     G (G-parity)     = None

Antiparticle name: MyPentaquark (antiparticle status: Same)

```

A yet more sophisticated definition:

```python

>>> p3 = Particle(pdgid=9221132,pdg_name='Theta',three_charge=3,latex_name='\Theta^{+}')

>>> p3

>>>

>>> print(p3.describe())

Name: Theta          ID: 9221132      Latex: $\Theta^{+}$

Mass  = None

Width = None

Q (charge)        = +       J (total angular) = 0.5      P (space parity) = None

C (charge parity) = None    I (isospin)       = None     G (G-parity)     = None

    SpinType: SpinType.NonDefined

    Antiparticle name: Theta (antiparticle status: Same)

```

### Advanced: Conversion

You can convert and update the particle tables with the utilities in `particle.particle.convert`. This requires the

`pandas` package, and is only tested with Python 3. Run the following command for more help:

```bash

$ python3 -m particle.particle.convert --help

```

## Getting started: Converters

You can use mapping classes to convert between particle MC identification codes

and particle names. See the `particle.converters` modules for the available

mapping classes. For example:

```python

>>> from particle.converters import Pythia2PDGIDBiMap

>>> from particle import PDGID, PythiaID

>>>

>>> pyid = Pythia2PDGIDBiMap[PDGID(9010221)]

>>> pyid

>>> pdgid = Pythia2PDGIDBiMap[PythiaID(10221)]

>>> pdgid

```

This code makes use of classes similar to `PDGID`, which hold

particle identification codes used by MC programs.

Possible use cases are the following:

```python

>>> from particle import Particle

>>> from particle import Corsika7ID, Geant3ID, PythiaID

>>>

>>> g3id = Geant3ID(8)

>>> p = Particle.from_pdgid(g3id.to_pdgid())

>>>

>>> (p,) = Particle.finditer(pdgid=g3id.to_pdgid())  # syntax (p,) throws an error if < 1 or > 1 particle is found

>>> p.name

'pi+'

>>> pythiaid = PythiaID(211)

>>> p = Particle.from_pdgid(pythiaid.to_pdgid())

>>> (p,) = Particle.finditer(pdgid=pythiaid.to_pdgid())

>>> p.name

'pi+'

>>> cid = Corsika7ID(5)

>>> p = Particle.from_pdgid(cid.to_pdgid())

>>> p.name

'mu+'

```

### Corsika7

The `Corsika7ID` class implements features to make it easier to work with Corsika7 output.

For a full feature set, please refer to the `particle.corsika` submodule.

`Corsika7ID.from_particle_description(from_particle_description: int)` returns `(Corsika7ID, bool)`

to automatically parse the `particle_description` from the Corsika7 particle data sub-block.

`Corsika7ID.is_particle()` checks if the ID refers to an actual particle or something else (like additional information).

`Corsika7ID.to_pdgid()` converts the `Corsika7ID` to a `PDGID` if possible.

## Getting started: experiment-specific modules

Experiment-specific submodules are welcome if they tie in nicely with the functionality of the package while providing

add-ons of particular relevance to experiments.

### LHCb-specific module

Available via

```python

>>> from particle import lhcb

```

it contains the following converter and functions:

```python

>>> dir(lhcb)

['LHCbName2PDGIDBiMap', 'from_lhcb_name', 'to_lhcb_name']

```

```python

>>> n, e, l = Particle.from_pdgid(-531).name, Particle.from_pdgid(531).evtgen_name, lhcb.to_lhcb_name(Particle.from_pdgid(-531))

>>> print(f"Name: {n}\nEvtGen name: {e}\nLHCb name: {l}")

Name: B(s)~0

EvtGen name: B_s0

LHCb name: B_s~0

>>> p = Particle.from_pdgid(-531)

>>> p

>>>to_lhcb_name(p)

'B_s~0'

```

Conversions PDG ID <-> LHCb name are available via a predefined bidirectional map

similarly to what is available in the standard (i.e. non-experiment-specific) converters:

```python

>>> name = LHCbName2PDGIDBiMap[PDGID(-531)]

>>> name

'B_s~0'

>>> pdgid = LHCbName2PDGIDBiMap['B_s~0']

>>> pdgid

```

## Contributors

We hereby acknowledge the contributors that made this project possible ([emoji key](https://allcontributors.org/docs/en/emoji-key)):

  

    

      
_{Eduardo Rodrigues}
🚧 💻 📖

      
_{Henry Schreiner}
🚧 💻 📖

      
_{Hans Dembinski}
💻

      
_{Ludwig Neste}
💻 📖

      
_{Tamas Gal}
💻

      
_{Matthew Feickert}
💻

      
_{Jost Migenda}
📖

    

    

      
_{Jonas Eschle}
💻

      
_{Chris Burr}
💻

      
_{Adam Morris}
💻

      
_{Doron Behar}
📖

      
_{Alexander Puck Neuwirth}
💻 📖

      
_{Aman Desai}
💻

      
_{Jonathan Tellechea}
📖

    

    

      
_{Remco de Boer}
💻

      
_{Maximilian Linhoff}
💻

    

  

This project follows the [all-contributors](https://github.com/all-contributors/all-contributors) specification.

## Acknowledgements

The UK Science and Technology Facilities Council (STFC) and the University of Liverpool

provide funding for Eduardo Rodrigues (2020-) to work on this project part-time.

Support for this work was provided by the National Science Foundation cooperative agreement OAC-1450377 (DIANA/HEP) in 2016-2019

and has been provided by OAC-1836650 (IRIS-HEP) since 2019.

Any opinions, findings, conclusions or recommendations expressed in this material

are those of the authors and do not necessarily reflect the views of the National Science Foundation.
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