Making Digital Objects FAIR in High Energy Physics: An Implementation for
Universal FeynRules Output (UFO) Models

Mark S. Neubauer1, Avik Roy1$\star$ and Zijun Wang1

1 University of Illinois at Urbana-Champaign

⋆<EMAIL_ADDRESS>
## Abstract

Research in the data-intensive discipline of high energy physics (HEP) often
relies on domain-specific digital contents. Reproducibility of research relies
on proper preservation of these digital objects. This paper reflects on the
interpretation of principles of Findability, Accessibility, Interoperability,
and Reusability (FAIR) in such context and demonstrates its implementation by
describing the development of an end-to-end support infrastructure for
preserving and accessing Universal FeynRules Output (UFO) models guided by the
FAIR principles. UFO models are custom-made python libraries used by the HEP
community for Monte Carlo simulation of collider physics events. Our framework
provides simple but robust tools to preserve and access the UFO models and
corresponding metadata in accordance with the FAIR principles.

###### Contents

  1. 1 Introduction
  2. 2 The Need to FAIRify UFO Models
  3. 3 Cyberinfrastructure for FAIRifying UFOs
    1. 3.1 UFOManager
    2. 3.2 UFOMetadata
    3. 3.3 FAIRifying UFOManager and UFOMetadata
  4. 4 Outlook and Conclusion
  5. A Example Content of Enriched Metadata
  6. B Demonstration of Usage of UFODownload
  7. C List of UFO models FAIRified via UFOManager and UFOMetadata

##  1 Introduction

Much of ongoing research in the discipline of high energy physics (HEP)
require using high-end computational resources. Examples include analyzing
petabyte scale data collected at the Large Hadron Collider (LHC) [1] or
obtaining precise theoretical predictions that may require taking into account
matrix element calculation from thousands of Feynman diagrams [2]. Being such
a computationally intensive research discipline, HEP research uses different
kinds of digital objects (DOs). These DOs used in HEP include large datasets
obtained from detector operation or Monte Carlo (MC) simulations, data
analysis software like ROOT [3], MC simulation software like Pythia [4],
Sherpa [5], Herwig [6], and MadGraph [7], dedicated libraries like LHAPDF [8]
for calculating the parton distribution functions, as well as numerous
privately developed codes and software packages, documentations, tutorials and
notebooks. While collaborations facilitate the preservation of their data and
common software frameworks for usage both within and outside of the
collaboration111For example, the ATLAS collaboration supports dedicated data
storage facility [9] and maintenance of data processing software [10] for its
members, preservation of digital resources independently developed by smaller
research groups or individuals is equally important to be able to reproduce
the results from HEP research. Hence, a significant amount of community-wide
effort and resources has been put forward in order to preserve these DOs. For
instance, the Durham High-Energy Physics Database (HEPData) [11] is an open-
access repository established for preserving and sharing scattering data from
HEP experiment, containing digitized details of plots and tables from
thousands of physics analysis publications. Similar efforts have been put
forward to preserve and reuse data analysis code and frameworks as well as
statistical models (see Refs. [12, 13, 14] for example). These efforts
emphasize the importance of a holistic approach in preserving different kinds
of digital objects. The importance of such preservation has been repeatedly
iterated in literature, especially in the context of reinterpretation and
reproduction of analysis results in HEP [13, 15, 16, 17].

In order to make datasets Findabile, Accessibile, Interoperable, and Reusable
(FAIR), a set of data principles have been defined so that scientific datasets
could be readily reused by both humans and machines [18]. Originally
envisioned for preservation of scientific datasets, the FAIR principles have
been interpreted in the context of different kinds of digital objects,
including research software [19], notebooks [20], and machine learning models
[21, 22]. Interpretation and application of FAIR principles for HEP datasets
has been explored in Ref. [23]. Exploring FAIR principles in the context of
DOs other than datasets is also becoming popular in HEP. For instance, the
NNPDF collaboration has developed a FAIR-inspired open-source framework for
parton distribution analyses [24]. Making DOs FAIR (i.e. FAIRification)
requires dedicated efforts on two fronts- (i) establishing guidelines for
developing new digital contents so that they conform to the FAIR principles
and (ii) developing tools to allow FAIRification of existing digital contents.
Given the diversity of digital resources used in HEP research, it is in
general expected that the exact manifestation of FAIR principle-driven tools
will depend on the nature of the digital object itself.

Developing dedicated cyberinfrastructure is a novel paradigm in facilitating
open and FAIR science. For instance, the Cookiecutter tool [25] allows
structural organization of machine learning model repositories, development of
containers, and publishing such codebases with persistent identifiers like
digital object identifiers (DOIs). In this paper, we demonstrate the
development of dedicated FAIRification tool in order to preserve Universal
FeynRules Output (UFO) [26] models. These models are customized python
libraries with a predefined format, often used to store information about
beyond standard model (BSM) physics models, and can be used as plug-in
libraries for MC simulation of BSM physics with event generator software. In
the following section, we briefly describe the content and format of UFO
models and motivate the necessity of their FAIRification. Section 3 introduces
the proposed framework for making UFO models FAIR and finally, the broader
outlook inspired by this work in FAIRifying UFO models is discussed in the
final remarks in Scction 4.

##  2 The Need to FAIRify UFO Models

The physics program of large collider experiments like the LHC spends major
efforts in search of BSM physics. These searches for BSM physics are motivated
by novel theoretical extensions of the standard model (SM). The UFO model
format was first introduced in Ref. [26] in order to streamline the process of
matrix element calculations for BSM physics models in a generator independent
way.

The UFO model format organizes the contents of the new physics as a self-
contained python library. It contains a collection of model-independent and
model-dependent python scripts (Table 1). While the model-indpendent scripts
include general technical functionalities of the model, the model-dependent
files contain physics-specific information. For instance, the script
particles.py contains information about all fundamental particles defined
within the scope of the model and their corresponding properties like color,
charge, and spin quantum numbers, PDG identifier [27], parameters representing
their mass and widths etc.

Model-independent files | Model-dependent files
---|---
| particles.py
__init__.py | coupling_orders.py
object_library.py | parameters.py
function_library.py | vertices.py
write_param_card.py | couplings.py
| lorentz.py
Table 1: List of model-independent and model-dependent files traditionally
included in the UFO format

The primary motivation of developing the UFO format philosophically coincides
with the FAIR principles. Content of BSM physics Lagrangians were generally
organized as text files, whose format depended on the choice of MC generation
software. Developing new physics models as python libraries enabled using the
same digital format to be interoperable across different MC generation
platforms like MadGraph, Herwig, and Sherpa [7, 28, 6]. Since its
introduction, the UFO format has been widely used to develop phenomenological
BSM physics models. At the LHC experiments, these models are regularly used to
generate MC events for BSM physics searches. In many cases, these models are
developed in association with physics publications that explain and validate
the underlying theoretical models. However, the preservation of these models
as persistent digital contents has not been ideal. Since its inception, many
of the UFO models have typically been hosted in the FeynRules Model Database
[29]. Most of these models are simply hosted as compressed containers like a
.tar or .zip file, without any persistent identifier, trackable version
controlling, or well-documented machine readable metadata. Some models like
the SMEFTsim [30] package are now maintained with modern software management
tools like git based version controlling [31] and hosted as Github
repositories. However, the standard FAIRification practices like use of
persistent digital identifiers or developing machine-readable metadata are yet
to be normative within the community. Moreover, hosting a project on Github or
similar platforms alone does not make DOs FAIR as these repositiories are not
persistent and often offer additional challenges to maintain the reliability
and integrity of the DOs they host [32]. Without any well-defined guideline on
community-wide agreed upon practices to preserve such digital contents, it can
be difficult to validate, reproduce, reinterpret, or recast any research that
relies on these models. For instance, the analysis performed by the ATLAS
collaboration in Ref. [33] uses a number of UFO models for generating MC
events for dark matter signal. These models were hosted by CERN’s svnweb
service222It used to be hosted on http://svnweb.cern.ch/. Currently, this web
service is discontinued and this link is no longer active that used the
subversion version controlling tool [34]. Since the discontinuation of this
service and a complete shift to gitlab (another git based version controlling
system) as the designated DO repository for CERN, the URLs pointed to by the
corresponding references are no longer valid. Moreover, those references
neither identify the authors of the model nor refer to any metadata that might
allow a reader to access any information about the construction of the model.
In situations like this, having no persistent identifiers associated with
these contents makes it virtually impossible to identify the content or
version of a UFO model used in a certain physics analysis, track changes
across versions, or attribute citation credit to developers of these digital
contents. Also, reusing these models to reproduce validation results or
reinterpret physics analyses can become challenging. Given these UFO models
directly contribute to a large number of HEP publications, ensuring
reproducibility of these results require these models to be preserved in an
open and FAIR way.

##  3 Cyberinfrastructure for FAIRifying UFOs

Facilitating FAIRification of UFO models must consider certain aspects of
current practices of developing and using UFO models. Given that the UFO
format is widely used, any tool to facilitate their FAIRification must not
interfere with the processes of how to develop or use them. Also, the tool
should be capable of FAIRifying pre-existing UFO models and allow distinct and
persistent identification of different versions of the same model.
Additionally, these tools should facilitate generation and preservation of
rich metadata with proper context and details regarding the model while allow
users to make use of this metadata to search for and download these models.
Finally, any tool dedicatedly developed to FAIRify UFO models should itself be
made FAIR.

Keeping these criteria in mind, the cyberinfrastructure for FAIRification of
UFO models has been developed in two independently maintained public
repositories- UFOManager and UFOMetadata. The following subsections address
the functionality of each of these repositories.

###  3.1 UFOManager

The UFOManager repository contains a collection of python scripts that can be
used to-

  * i.

perform validation checks on a UFO model

  * ii.

develop enriched machine-readable metadata for each model

  * iii.

publish these models with persistent DOIs and independently preserve their
metadata

  * iv.

upload a new version of the previously uploaded model

  * v.

search for models with keywords

  * vi.

download models according to user’s choice

Among the aforementioned functionalities, (i)-(iv) are facilitated by the
script UFOUpload.py while the remaining functionalities are supported by the
script UFODownload.py. Many of the existing UFO models were developed using
Python 2\. Hence, the module UFOUpload.py has been developed to be compatible
with both versions of Python. The UFODownload script, however, is only
compatible with Python 3\. The instructions for creating the appropriate
environments and installing dependencies are included in the README of the
package.

The UFOUpload and UFODownload scripts can be run as standalone scripts to
perform the desired task. The UFOUpload script can be run in five independent
modes, which has to be mentioned as a command line argument when running the
script in standalone mode. The script can be run on the command-line interface
as a simple Python script using either of the following commands-

python UFOUpload.py <operation-mode> python -m UFOManager.UFOUpload
<operation-mode>

where <operation-mode> refers to one of the following five strings- Validation
Check, Generate metadata, Upload model, Update new version, and Upload
metadata to GitHub. The functionality provided by each of these operation
modes can be easily understood from their names. The script is designed to run
interactively, so necessary inputs are requested from the user at different
stages of executing the script. In order to use the UFOUpload script, the user
must provide a list of locally accessible directories in a .txt file where
each directory houses a single UFO model along with an initial metadata file
called metadata.json, in the format of a json file. Storing metadata in the
format of json files ensures that it is simultaneously human and machine-
readable, and also compatible with multiple programming platforms ensuring its
interoperability. In the process of FAIRifying these models with persistent
DOIs, they are uploaded to Zenodo [35]. This also allows trackable version
controlling for the models since Zenodo provides unique DOIs for different
versions of the same entry as well as a unique concept DOI that can be used to
locate all versions of a given content.

UFOManager can also be used as a dedicated Python package and can be imported
and used as a Python package using the following syntax-

from UFOManager import UFOUpload UFOUpload.UFOUpload(<operation-mode>,<model-
list>)

where <operation-mode> represents one of the previously mentioned operation
modes and <model-list> is the text file with a list of UFO models.

Successful publishing of model relies on creation of enriched metadata, which
eventually relies on the successful completion of validation checks. Hence,
any attempt to upload a new model or update the version of an existing model
will automatically perform validation checks and create enriched metadata.
This enriched metadata is built upon the information provided by the user in
the initial metadata.json file. This initial metadata must contain at least
three fields- (i) the names of the authors of the model along with contact
information (an email address) for at least one of the authors, (ii) a brief
description of the model, and (iii) a digital identifier (an arxiv ID or a
DOI) for an associated publication that explains the underlying model and
provides physics validation. The initial metadata can also contain additional
information like the link to the webpage that hosts the model (e.g. a Github
repository or the link to a model’s location within FeynRules Model Database).
The content provided in the metadata.json file to register one of the UFO
models used to describe the physics of Vector-like Quarks (VLQs) [36] using
our tool is given in Table 2.

{ |  |
---|---|---
| "Author": [ |
|  | {"name" : "Luca Panizzi",
|  | "affiliation": "Uppsala University",
|  | "contact"<EMAIL_ADDRESS>
|  | {"name" : "Benjamin Fuks",
|  | "affiliation": "Sorbonne University",
|  | "contact"<EMAIL_ADDRESS>
| ], |
| "Paper_id": | {"doi": "10.1140/epjc/s10052-017-4686-z",
|  | "arXiv" : "1610.04622"},
| "Description": | "Vector-like Quark UFO Model at NLO QCD
|  |  with four flavour scheme",
| "Model Homepage" : | "https://feynrules.irmp.ucl.ac.be/wiki/NLOModels"
} |  |
Table 2: Content of initial metadata.json file used to FAIRify the UFO model
in Ref. [36]

The validation check looks for the presence of required files in the UFO
model, inspects the initial metadata for the necessary content and their
validity (e.g. if the provided arxiv ID represents a valid entry). Then, it
checks if the model can be imported as a standalone python package, since that
is the intended mode of usage for these models. Afterwards, it inspects each
of the independent scripts within the UFO model. These inspections include
tests on whether the script can be imported as a Python module, each essential
script contains a non-zero count of required objects, and some basic
validation checks. These checks include validating the uniqueness and validity
of the PDG IDs assigned to the particles as well as whether the model supports
Next-to-Leading-Order (NLO) calculations. Validation of PDG IDs is performed
using the Particles package [37]. During these checks, it also collects
information for the enriched metadata.

Besides the fields provided with the initial metadata, the enriched metadata,
which also is stored as a json file, contains additional information about the
number of parameters, couplings, coupling orders, vertices, lorentz tensors,
propagators, and decays contained in different scripts within the model. It
also contains maps of fundamental particles and their PDG IDs defined in the
model. The enriched metadata also records the version of Python the model has
been validated with and the version identifier of the model itself. A field
for storing the model’s DOI is created. If the user wishes to upload the model
or update an existing model with the current content, the model is uploaded to
Zenodo using its REST-API service. The DOI generated during uploading the
model to Zenodo is stored in the enriched metadata. The content of the
enriched metadata generated by the tool for the previously mentioned VLQ UFO
model [36] is given in Table A1.

The enriched metadata is finally uploaded in the UFOMetadata repository. To
perform these uploads the user needs to have registered accounts with both
Zenodo and Github and obtain secure access tokens for the respective accounts.
These access tokens allow validating the registered user accounts and use the
APIs in a secure manner.

The final piece of the UFOManager tool is the UFODownload script, which allows
the users to search for and access these models. It can be run as a standalone
Python script from the command line interface using either of the following
commands-

python UFODownload.py <operation-mode> python -m UFOManager.UFODownload
<operation-mode>

where operation-mode refers to one of the following strings- Search for model,
Download model, and Search and Download. To use it within a facilitator
script, it can be run as-

from UFOManager import UFODownload UFODownload.UFODownload(<operation-mode>)

The UFODownload script allows the user to search for UFO models based on a
number of keywords, including arxiv ID or DOI of associated publication, PDG
ID of new elementary particles, DOI of the model, and model name. Table B2
shown an example of the usage of this script using the interactive command
line interface to search for models with a certain PDG ID. When searching for
models, it lists all available versions of the models whose metadata are
available in UFOMetadata. It uses the zenodo_get package [38] to allow users
to download the desired models. The script interfaces with the latest version
of the UFOMetadata repository and offers the user a set of options based on
the search criteria. Upon request, the metadata and corresponding model are
downloaded by this script.

###  3.2 UFOMetadata

FAIRification of DOs require their metadata to include qualifying reference to
the original content and be stored independently of the data [18]. Hence, the
enriched metadata generated by the UFOManager is stored as independent json
files in the UFOMetadata repository. Every time a user decides to upload their
model using the UFOManager tool, the corresponding metadata is sent to the
UFOMetadata repository. However, it is also possible for users to
independently register their model and submit the corresponding metadata for
addition to the repository. Every request to add metadata must be done via a
pull request, which triggers an automated Github workflow for continuous
integration. The workflow performs a validation check on the new content to
ensure- (i) none of the previously existing files has been renamed, modified,
or deleted, (ii) the newly added metadata files have all the fields that are
generated with the UFOManager tool, and (iii) newly added models have unique
and valid DOIs. These pull requests are currently merged by the maintainers of
repository in a regular interval to keep the repository updated with the
latest additions. It should be noted that the UFODownload script makes use of
the latest version of the main branch of the UFOMetadata repository, so access
to any mew metadata is only made available after the pull requests are merged.

###  3.3 FAIRifying UFOManager and UFOMetadata

While the tools facilitated via UFOManager and UFOMetadata enable
FAIRification of UFO models, it is only expected to have these tools made
available as FAIR DOs themselves. The latest stable releases of these
repositories are made available with persistent DOIs via Zenodo. The metadata
can for these repositories can be accessed via URLs and obtained with JSON
Schema with Zenodo’s REST API. The use of JSON Schema provides clear human and
machine readable documentation. The following table gives the DOIs for the
latest versions of these packages.

Content | Latest Version | DOI/URL
---|---|---
UFOManager | 2.0.0 |  10.5281/zenodo.7066042 [39]
Metadata for UFOManager | N/A | https://zenodo.org/api/records/7066042
UFOMetadata | 2.0.0 |  10.5281/zenodo.7066046 [40]
Metadata for UFOMetadata | N/A | https://zenodo.org/api/records/7066046
Table 3: DOIs for the latest stable releases of UFOManager and UFOMetadata and
URLs to access their corresponding metadata

##  4 Outlook and Conclusion

With an ever-increasing volume of DOs required in mainstream HEP research,
FAIR management and preservation of these contents is necessary to ensure
transparent, reliable, and reproducible results. We discussed in this paper in
the context of UFO models why having standardized FAIRification practices is
necessary and developed a set of simple, customized tools to facilitate such
practices. UFOManager and UFOMetadata rely on well-established and widely used
programming tools and practices and offer a unified approach to save UFO
models as FAIR DOs. Our work additionally serves as an example on developing
customized, automatic FAIRification tools for DOs used in HEP research that
can serve as a guide to establishing similar practices in orthodox DO
management.

## Acknowledgements

We thank Benjamin Fuks for permitting the use of publicly available UFO models
authored by him. We also thank Olivier Mattelaer for encouraging discussions
and suggestions on improving the content of enriched metadata for UFO models.
A.R.: This work was supported by the FAIR Data program of the U.S. Department
of Energy, Office of Science, Advanced Scientific Computing Research, under
contract number DE-SC0021258. M.S.N: This work was supported by the National
Science Foundation under OAC-1841456. Z.W.: This work was supported by the
National Science Foundation under Cooperative Agreement OAC-1836650.

##  Appendix A Example Content of Enriched Metadata

{ |  |
---|---|---
| "Model name": | "UFO model for Vector-like Quarks at NLO QCD with four flavor scheme",
| "Model Doi": | ""10.5281/zenodo.6977663"",
| "Author": [ |
|  | {"name" : "Luca Panizzi",
|  | "affiliation": "Uppsala University",
|  | "contact"<EMAIL_ADDRESS>
|  | {"name" : "Benjamin Fuks",
|  | "affiliation": "Sorbonne University",
|  | "contact"<EMAIL_ADDRESS>
| ], |
| "Paper_id": | {"doi": "10.1140/epjc/s10052-017-4686-z",
|  | "arXiv" : "1610.04622"},
| "Description": | "Vector-like Quark UFO Model at NLO QCD
|  |  with four flavour scheme",
| "Model Homepage" : |  "https://feynrules.irmp.ucl.ac.be/wiki/NLOModels",
| "Number of decays": | 10,
| "Number of coupling orders": | 3,
| "Number of coupling tensors": | 97,
| "Number of lorentz tensors": | 39,
| "Number of parameters": | 98,
| "Number of vertices": | 125,
| "Number of propagators": | 4,
| "Model Python Version": | 2,
| "Model Version": | 1.0,
| "Allows NLO calculations": | true,
| "All Particles": | {"ve": 12, "ghG$\scriptstyle\mathtt{\sim}$": -82, "y$\scriptstyle\mathtt{\sim}$": -6000008,
|  | "u$\scriptstyle\mathtt{\sim}$": -2, "vm$\scriptstyle\mathtt{\sim}$": -14, "vt": 16, "s": 3,
|  | "c$\scriptstyle\mathtt{\sim}$": -4, "t$\scriptstyle\mathtt{\sim}$": -6, "G0": 250, "u": 2,
|  | "ve$\scriptstyle\mathtt{\sim}$": -12, "tp": 6000006,
|  | "x$\scriptstyle\mathtt{\sim}$": -6000005, "G-": -251,
|  | "ta+": -15, "G+": 251, "vt$\scriptstyle\mathtt{\sim}$": -16, "e-": 11,
|  | "y": 6000008, "e+": -11, "H": 25, "t": 6,
|  | "vm": 14, "d$\scriptstyle\mathtt{\sim}$": -1, "s$\scriptstyle\mathtt{\sim}$": -3,
|  | "mu-": 13, "ghG": 82, "bp": 6000007, "a": 22,
|  | "x": 6000005, "ta-": 15,
|  | "b$\scriptstyle\mathtt{\sim}$": -5, "Z": 23,
|  | "d": 1, "g": 21,
|  | "W-": -24, "W+": 24,
|  | "tp$\scriptstyle\mathtt{\sim}$": -6000006, "mu+": -13,
|  | "bp$\scriptstyle\mathtt{\sim}$": -6000007, "c": 4, "b": 5, },
| "SM Particles": | {"ve": 12, "u$\scriptstyle\mathtt{\sim}$": -2, "vm$\scriptstyle\mathtt{\sim}$": -14, "vt": 16, "s": 3,
|  | "c$\scriptstyle\mathtt{\sim}$": -4, "t$\scriptstyle\mathtt{\sim}$": -6, "u": 2,"ve$\scriptstyle\mathtt{\sim}$": -12,
|  | "ta+": -15, "vt$\scriptstyle\mathtt{\sim}$": -16, "e-": 11,
|  | "e+": -11, "H": 25, "t": 6,
|  | "vm": 14, "d$\scriptstyle\mathtt{\sim}$": -1, "s$\scriptstyle\mathtt{\sim}$": -3,
|  | "mu-": 13, "a": 22, "ta-": 15,
|  | "b$\scriptstyle\mathtt{\sim}$": -5, "Z": 23,
|  | "d": 1, "g": 21,
|  | "W-": -24, "W+": 24,
|  | "tp$\scriptstyle\mathtt{\sim}$": -6000006, "mu+": -13,
|  | "bp$\scriptstyle\mathtt{\sim}$": -6000007, "c": 4, "b": 5, },
| "New elementary particles": | {"G0": 250, "y$\scriptstyle\mathtt{\sim}$": -6000008, "tp": 6000006,
|  | "bp": 6000007, "x$\scriptstyle\mathtt{\sim}$": -6000005, "x": 6000005,
|  | "y": 6000008, "tp$\scriptstyle\mathtt{\sim}$": -6000006, "G-": -251,
|  | "G+": 251, "bp$\scriptstyle\mathtt{\sim}$": -6000007 }
| "BSM particles with standard PDG codes": | {"G-": -251, "G+": 251,
|  | "tp": 6000006, "tp$\scriptstyle\mathtt{\sim}$": -6000006,
| "Particles with PDG-like IDs": | {"G0": {"charge": 0.0, "spin": 1, "id": 250},
|  | "bp": {"charge": -1/3, "spin": 2, "id": 6000007},
|  | "x ": {"charge": -5/3,"spin": 2,"id": -6000005 },
|  | "y ": {"charge": 4/3, "spin": 2, "id": -6000008 },
|  | "y": {"charge": -4/3, "spin": 2, "id": 6000008 },
|  | "x": {"charge": 5/3, "spin": 2, "id": 6000005 },
|  | "bp ": {"charge": 1/3, "spin": 2, "id": -6000007}}
} |  |

Table A1: Content of the enriched metadata file obtained from the Uploadv2.py
to FAIRify the UFO model in Ref. [36]

##  Appendix B Demonstration of Usage of UFODownload

$ python -m UFOManager.UFODownload ’Search for model’
---
Please enter you Github access token:
You can search for model with Paper_id, Model Doi, pdg code, name (of certain
particles).
Please choose your keyword type: pdg code
Please enter your needed pdg code: 6000006
Based on your search, we find models below:
Metadata file | Model Name | Paper ID | Model DOI
VLQ_v5_5FNS_NLO_UFO.V2.0.json | UFO model for Vector-like Quarks at NLO QCD with five flavor scheme (third generation) | 1610.04622 | 10.5281/zenodo.7038823
VLQ_v5_4FNS_only3rd_NLO_UFO.json | UFO model for Vector-like Quarks at NLO QCD with four flavor scheme (third generation) | 1610.04622 | 10.5281/zenodo.7041539
vlq_v4_4fns.json | UFO model for Vector-like Quarks at NLO QCD with four flavor scheme | 1610.04622 | 10.5281/zenodo.6977663
VLQ_v4_5FNS_UFO.json | UFO model for Vector-like Quarks at NLO QCD with five flavor scheme | 1610.04622 | 10.5281/zenodo.6991118
VLQ_v5_4FNS_NLO_UFO.V2.0.json | UFO model for Vector-like Quarks at NLO QCD with four flavor scheme | 1610.04622 | 10.5281/zenodo.7038908
VLQ_v5_4FNS_NLO_UFO.V3.0.json | UFO model for Vector-like Quarks at NLO QCD with four flavor scheme | 1610.04622 | 10.5281/zenodo.7039382
VLQ_v5_5FNS_only3rd_NLO_UFO.json | UFO model for Vector-like Quarks at NLO QCD with five flavor scheme (third generation) | 1610.04622 | 10.5281/zenodo.7041528
Do you still want to search for models? Please type in Yes or No: No |

Table B2: Sample output from an interactive command line usage of the
UFODownload script

##  Appendix C List of UFO models FAIRified via UFOManager and UFOMetadata

The following table contains a set of example UFO models that were FAIRified
by using the UFOManager and UFOMetadata tools. These models are hosted at the
publicly available FeynRules Model Database [29].

Model Name | Version | DOI | Metadata
---|---|---|---
universal framework for t-channel | 1.0 | 10.5281/zenodo.6991108 [41] | DMSimpt_NLO_v1_2_UFO
dark matter models [42]
Spin-2 simplified model [43] | 1.0 |  10.5281/zenodo.6908818 [44] | DMspin2
NLO predictions in supersymmetric QCD [45] | 1.0 |  10.5281/zenodo.6991116 [46] | SUSYQCD_UFO
Vector-like Quarks at NLO QCD | 1.0 |  10.5281/zenodo.6991118 [47] | VLQ_v4_5FNS_UFO
with five flavor scheme [48] | 2.0 |  10.5281/zenodo.7038823 [49] | VLQ_v5_5FNS_NLO_UFO.V2.0
Vector-like Quarks at NLO QCD | 1.0 | 10.5281/zenodo.7041528 [50] | VLQ_v5_5FNS_only3rd_NLO_UFO
with five flavour scheme (third generation) [48]
Vector-like Quarks at NLO QCD | 1.0 |  10.5281/zenodo.6977663 [51] | vlq_v4_4fns
with four flavor scheme [48] | 2.0 |  10.5281/zenodo.7038908 [52] | VLQ_v5_4FNS_NLO_UFO.V2.0
Vector-like Quarks at NLO QCD | 1.0 | 10.5281/zenodo.7041539 [53] | VLQ_v5_4FNS_only3rd_NLO_UFO
with four flavour scheme (third generation) [48]
NLO predictions for sgluon pair production [54] | 1.0 |  10.5281/zenodo.6991112 [55] | sgluons_NLO
stop pair production to ttbar and missing energy [54] | 1.0 |  10.5281/zenodo.6991114 [56] | stop_ttmet_NLO
pseudo-Nambu-Goldstone Dark Matter [57] | 1.0 |  10.5281/zenodo.7065996 [58] | SM_with_pNG_UFO
2.0 |  10.5281/zenodo.7066011 [59] | SM_with_pNG_UFO_py3.V2.0

Table C3: DOIs for some of the UFO models made FAIR by the UFOManager and
UFOMetadata tools

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