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2 changes: 1 addition & 1 deletion .pre-commit-config.yaml
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Expand Up @@ -40,7 +40,7 @@ repos:
rev: v2.4.1
hooks:
- id: codespell
args: ["-LOnd,HEP,Leary"]
args: ["-LOnd,HEP,Leary,Paret,Parma"]
exclude: ^docs/usage/intro.ipynb$

- repo: https://github.com/rbubley/mirrors-prettier
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190 changes: 190 additions & 0 deletions paper/paper.bib
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Expand Up @@ -221,3 +221,193 @@ @inproceedings{Ansel:2024
url = {https://pytorch.org/assets/pytorch2-2.pdf},
year = {2024}
}

@software{hepvector,
author = {Henry Schreiner},
title = {{HEPvector}: NumPy based vectors for general purpose calculation and physics},
url = {https://github.com/henryiii/hepvector},
}

@software{LorentzVectorHEP:2023,
author = {Jerry Ling and Moritz Terwissen and Graeme A Stewart},
title = {LorentzVectorHEP.jl: x, y, z, t and pt, eta, phi, M Lorentz Vectors as used in collider experiments at CERN and other places},
url = {https://github.com/JuliaHEP/LorentzVectorHEP.jl},
version = {0.1.16},
year = {2023},
}

@article{Held:2022sfw,
author = "Held, Alexander and Shadura, Oksana",
title = "{The IRIS-HEP Analysis Grand Challenge}",
doi = "10.22323/1.414.0235",
journal = "PoS",
volume = "ICHEP2022",
pages = "235",
month = "11",
year = "2022"
}

@book{Aberle:2749422,
author = "Aberle, O. and Béjar Alonso, I and Brüning, O and
Fessia, P and Rossi, L and Tavian, L and Zerlauth, M and
Adorisio, C. and Adraktas, A. and Ady, M. and Albertone, J.
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and Ambrosio, G. and Andreu Munoz, P. and Anerella, M. and
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M. and Zurbano Fernandez, I.",
title = "{High-Luminosity Large Hadron Collider (HL-LHC): Technical
design report}",
publisher = "CERN",
address = "Geneva",
series = "CERN Yellow Reports: Monographs",
year = "2020",
url = "https://cds.cern.ch/record/2749422",
doi = "10.23731/CYRM-2020-0010",
}
40 changes: 22 additions & 18 deletions paper/paper.md
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Expand Up @@ -62,34 +62,38 @@ high energy physics experiments.

# Statement of need

Vector is the only actively developed Lorentz vector library with
a Pythonic interface but a compiled (through Awkward Array [@Pivarski:2018])
computational backend. Vector integrates seamlessly with the existing high energy
physics ecosystem and the broader scientific Python ecosystem, including libraries
like Dask [@rocklin:2015] and Numba [@lam:2015]. The library implements a variety
of backends for several purposes. Although vector was written with high energy
physics in mind, it is a general-purpose library that can be used for any
scientific or engineering application. The library houses a set of diverse
backends, 3 numerical backends for experimental physicists and 1 symbolic
backend for theoretical physicists. These backends include:
Vector is one of the few Lorentz vector libraries that offer
a Pythonic interface but a compiled computational backend, with the others
being Coffea's vector module (depends on vector), PyROOT [@root:2020]'s
LorentzVectors and TLorentzVector classes, and hepvector [@hepvector] (deprecated
in favor of vector). Although vector was written with high energy physics in mind,
it is a general-purpose library that can be used for any scientific or engineering
application. The library houses a set of diverse backends, three numerical backends
for experimental physicists and one symbolic backend for theoretical physicists.
These backends are:

- a pure Python object (builtin) backend for scalar computations,
- a NumPy backend for computations on regular collection-type data,
- a SymPy [@Meurer:2017] backend for symbolic computations, and
- an Awkward backend for computations on ragged collection-type data
- an Awkward [@Pivarski:2018] backend for computations on ragged collection-type data

There also exists implementations of the Object and the Awkward backend in Numba
for just-in-time compilable operations. Further, support for JAX [@Bradbury:2018]
and Dask is provided through the Awkward backend, which enables vector
functionalities to support automatic differentiation and parallel computing.
Moreover, vector is the first Lorentz vector library to offer multiple
computational backends, as well as both numerical and symbolic backends. Furthermore,
akin to PyROOT and LorentzVectorHEP.jl [@LorentzVectorHEP:2023], vector supports
just-in-time compilation through Numba extensions [@lam:2015], implemented for both
the Object and Awkward backends. Vector also includes support for JAX [@Bradbury:2018]
and Dask [@rocklin:2015] for the Awkward backend, enabling the library to support
automatic differentiation and parallel computing, which are required for introducing
automatic differentiation in Analysis Grand Challenge [@Held:2022sfw] and to meet
the computational needs of High Luminosity LHC [@Aberle:2749422].

## Impact

Besides PyROOT's LorentzVectors and TLorentzVector [@root:2020], vector has
Besides PyROOT's LorentzVectors and TLorentzVector, vector has
become a popular choice for mathematical manipulations in Python based high energy
physics analysis pipelines. Along with being utilized directly in
analysis pipelines at LHC [@Kling:2023; @Held:2024; @Qu:2022], the library is
being used in other high energy physics experiments asn as a dependency in other
analysis pipelines at LHC [@Kling:2023; @Held:2024; @Qu:2022], the library is also
being used in other high energy physics experiments and as a dependency in other
user-facing frameworks, such as, Coffea, MadMiner [@Brehmer:2020], FastJet
[@aryan:2023], Spyral [@spyral-utils:2024], Weaver [@weaver-core:2024], and pylhe
[@pylhe]. The library is also used in multiple teaching materials for graduate
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