A FAIR and AI-ready Higgs boson decay dataset

Chen, Yifan; Huerta, E. A.; Duarte, Javier; Harris, Philip; Katz, Daniel S.; Neubauer, Mark S.; Diaz, Daniel; Mokhtar, Farouk; Kansal, Raghav; Park, Sang Eon; Kindratenko, Volodymyr V.; Zhao, Zhizhen; Rusack, Roger

doi:10.1038/s41597-021-01109-0

Title: A FAIR and AI-ready Higgs boson decay dataset

Journal Article · 13 February 2022 · Scientific Data

DOI: https://doi.org/10.1038/s41597-021-01109-0 · OSTI ID:1845043

;

; Harris, Philip;

;

; Zhao, Zhizhen;

Abstract To enable the reusability of massive scientific datasets by humans and machines, researchers aim to adhere to the principles of findability, accessibility, interoperability, and reusability (FAIR) for data and artificial intelligence (AI) models. This article provides a domain-agnostic, step-by-step assessment guide to evaluate whether or not a given dataset meets these principles. We demonstrate how to use this guide to evaluate the FAIRness of an open simulated dataset produced by the CMS Collaboration at the CERN Large Hadron Collider. This dataset consists of Higgs boson decays and quark and gluon background, and is available through the CERN Open Data Portal. We use additional available tools to assess the FAIRness of this dataset, and incorporate feedback from members of the FAIR community to validate our results. This article is accompanied by a Jupyter notebook to visualize and explore this dataset. This study marks the first in a planned series of articles that will guide scientists in the creation of FAIR AI models and datasets in high energy particle physics.

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Sponsoring Organization:: USDOE

Grant/Contract Number:: SC0021258; SC0021396; SC0021225; SC0021395

OSTI ID:: 1845043

Journal Information:: Scientific Data, Journal Name: Scientific Data Journal Issue: 1 Vol. 9; ISSN 2052-4463

Publisher:: Nature Publishing GroupCopyright Statement

Country of Publication:: United Kingdom

Language:: English

References (44)

Advances in Machine and Deep Learning for Modeling and Real-Time Detection of Multi-messenger Sources Huerta, E. A.; Zhao, Zhizhen Handbook of Gravitational Wave Astronomy https://doi.org/10.1007/978-981-15-4702-7_47-1	book	January 2021
Identifying boosted objects with N-subjettiness Thaler, Jesse; Van Tilburg, Ken Journal of High Energy Physics, Vol. 2011, Issue 3 https://doi.org/10.1007/JHEP03(2011)015	journal	March 2011
Soft drop Larkoski, Andrew J.; Marzani, Simone; Soyez, Gregory Journal of High Energy Physics, Vol. 2014, Issue 5 https://doi.org/10.1007/JHEP05(2014)146	journal	May 2014
Towards an understanding of jet substructure Dasgupta, Mrinal; Fregoso, Alessandro; Marzani, Simone Journal of High Energy Physics, Vol. 2013, Issue 9 https://doi.org/10.1007/JHEP09(2013)029	journal	September 2013
End-to-End Physics Event Classification with CMS Open Data: Applying Image-Based Deep Learning to Detector Data for the Direct Classification of Collision Events at the LHC Andrews, M.; Paulini, M.; Gleyzer, S. Computing and Software for Big Science, Vol. 4, Issue 1 https://doi.org/10.1007/s41781-020-00038-8	journal	March 2020
Geant4—a simulation toolkit Agostinelli, S.; Allison, J.; Amako, K. Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment, Vol. 506, Issue 3 https://doi.org/10.1016/S0168-9002(03)01368-8	journal	July 2003
An introduction to PYTHIA 8.2 Sjöstrand, Torbjörn; Ask, Stefan; Christiansen, Jesper R. Computer Physics Communications, Vol. 191 https://doi.org/10.1016/j.cpc.2015.01.024	journal	June 2015
End-to-end jet classification of quarks and gluons with the CMS Open Data Andrews, M.; Alison, J.; An, S. Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment, Vol. 977 https://doi.org/10.1016/j.nima.2020.164304	journal	October 2020
Parton distributions with LHC data Ball, Richard D.; Bertone, Valerio; Carrazza, Stefano Nuclear Physics B, Vol. 867, Issue 2 https://doi.org/10.1016/j.nuclphysb.2012.10.003	journal	February 2013
Observation of a new particle in the search for the Standard Model Higgs boson with the ATLAS detector at the LHC Aad, G.; Abajyan, T.; Abbott, B. Physics Letters B, Vol. 716, Issue 1 https://doi.org/10.1016/j.physletb.2012.08.020	journal	September 2012
Observation of a new boson at a mass of 125 GeV with the CMS experiment at the LHC Chatrchyan, S.; Khachatryan, V.; Sirunyan, A. M. Physics Letters B, Vol. 716, Issue 1 https://doi.org/10.1016/j.physletb.2012.08.021	journal	September 2012
Deep learning LeCun, Yann; Bengio, Yoshua; Hinton, Geoffrey Nature, Vol. 521, Issue 7553 https://doi.org/10.1038/nature14539	journal	May 2015
Accelerated, scalable and reproducible AI-driven gravitational wave detection Huerta, E. A.; Khan, Asad; Huang, Xiaobo Nature Astronomy, Vol. 5, Issue 10 https://doi.org/10.1038/s41550-021-01405-0	journal	July 2021
Enabling real-time multi-messenger astrophysics discoveries with deep learning Huerta, E. A.; Allen, Gabrielle; Andreoni, Igor Nature Reviews Physics, Vol. 1, Issue 10 https://doi.org/10.1038/s42254-019-0097-4	journal	October 2019
The FAIR Guiding Principles for scientific data management and stewardship Wilkinson, Mark D.; Dumontier, Michel; Aalbersberg, IJsbrand Jan Scientific Data, Vol. 3, Issue 1 https://doi.org/10.1038/sdata.2016.18	journal	March 2016
A design framework and exemplar metrics for FAIRness Wilkinson, Mark D.; Sansone, Susanna-Assunta; Schultes, Erik Scientific Data, Vol. 5, Issue 1 https://doi.org/10.1038/sdata.2018.118	journal	June 2018
The anti- k _t jet clustering algorithm Cacciari, Matteo; Salam, Gavin P.; Soyez, Gregory Journal of High Energy Physics, Vol. 2008, Issue 04 https://doi.org/10.1088/1126-6708/2008/04/063	journal	April 2008
HEPData: a repository for high energy physics data Maguire, Eamonn; Heinrich, Lukas; Watt, Graeme Journal of Physics: Conference Series, Vol. 898 https://doi.org/10.1088/1742-6596/898/10/102006	journal	October 2017
Particle-flow reconstruction and global event description with the CMS detector Sirunyan, A. M.; Tumasyan, A.; Adam, W. Journal of Instrumentation, Vol. 12, Issue 10 https://doi.org/10.1088/1748-0221/12/10/P10003	journal	October 2017
Identification of heavy-flavour jets with the CMS detector in pp collisions at 13 TeV Sirunyan, A. M.; Tumasyan, A.; Adam, W. Journal of Instrumentation, Vol. 13, Issue 05 https://doi.org/10.1088/1748-0221/13/05/P05011	journal	May 2018
Pileup mitigation at CMS in 13 TeV data Sirunyan, A. M.; Tumasyan, A.; Adam, W. Journal of Instrumentation, Vol. 15, Issue 09 https://doi.org/10.1088/1748-0221/15/09/P09018	journal	September 2020
Jet flavour classification using DeepJet Bols, E.; Kieseler, J.; Verzetti, M. Journal of Instrumentation, Vol. 15, Issue 12 https://doi.org/10.1088/1748-0221/15/12/P12012	journal	December 2020
Identification of b-quark jets with the CMS experiment collaboration, The CMS Journal of Instrumentation, Vol. 8, Issue 04 https://doi.org/10.1088/1748-0221/8/04/P04013	journal	April 2013
Deep transfer learning for star cluster classification: I. application to the PHANGS– HST survey Wei, Wei; Huerta, E. A.; Whitmore, Bradley C. Monthly Notices of the Royal Astronomical Society, Vol. 493, Issue 3 https://doi.org/10.1093/mnras/staa325	journal	February 2020
Star cluster classification in the PHANGS– HST survey: Comparison between human and machine learning approaches Whitmore, Bradley C.; Lee, Janice C.; Chandar, Rupali Monthly Notices of the Royal Astronomical Society, Vol. 506, Issue 4 https://doi.org/10.1093/mnras/stab2087	journal	July 2021
Exploring the space of jets with CMS open data Komiske, Patrick T.; Mastandrea, Radha; Metodiev, Eric M. Physical Review D, Vol. 101, Issue 3 https://doi.org/10.1103/PhysRevD.101.034009	journal	February 2020
Jet tagging via particle clouds Qu, Huilin; Gouskos, Loukas Physical Review D, Vol. 101, Issue 5 https://doi.org/10.1103/PhysRevD.101.056019	journal	March 2020
Interaction networks for the identification of boosted H → b b ¯ decays Moreno, Eric A.; Nguyen, Thong Q.; Vlimant, Jean-Roch Physical Review D, Vol. 102, Issue 1 https://doi.org/10.1103/PhysRevD.102.012010	journal	July 2020
Jet substructure studies with CMS open data Tripathee, Aashish; Xue, Wei; Larkoski, Andrew Physical Review D, Vol. 96, Issue 7 https://doi.org/10.1103/PhysRevD.96.074003	journal	October 2017
Jet Substructure as a New Higgs-Search Channel at the Large Hadron Collider Butterworth, Jonathan M.; Davison, Adam R.; Rubin, Mathieu Physical Review Letters, Vol. 100, Issue 24 https://doi.org/10.1103/PhysRevLett.100.242001	journal	June 2008
Exposing the QCD Splitting Function with CMS Open Data Larkoski, Andrew; Marzani, Simone; Thaler, Jesse Physical Review Letters, Vol. 119, Issue 13 https://doi.org/10.1103/PhysRevLett.119.132003	journal	September 2017
Metric Space of Collider Events Komiske, Patrick T.; Metodiev, Eric M.; Thaler, Jesse Physical Review Letters, Vol. 123, Issue 4 https://doi.org/10.1103/PhysRevLett.123.041801	journal	July 2019
Large Mass Hierarchy from a Small Extra Dimension Randall, Lisa; Sundrum, Raman Physical Review Letters, Vol. 83, Issue 17 https://doi.org/10.1103/PhysRevLett.83.3370	journal	October 1999
ImageNet: A large-scale hierarchical image database Deng, Jia; Dong, Wei; Socher, Richard 2009 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops (CVPR Workshops), 2009 IEEE Conference on Computer Vision and Pattern Recognition https://doi.org/10.1109/CVPR.2009.5206848	conference	June 2009
Deep Residual Learning for Image Recognition He, Kaiming; Zhang, Xiangyu; Ren, Shaoqing 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) https://doi.org/10.1109/CVPR.2016.90	conference	June 2016
DeepDriveMD: Deep-Learning Driven Adaptive Molecular Simulations for Protein Folding Lee, Hyungro; Turilli, Matteo; Jha, Shantenu 2019 IEEE/ACM Third Workshop on Deep Learning on Supercomputers (DLS) https://doi.org/10.1109/DLS49591.2019.00007	conference	November 2019
FastJet user manual: (for version 3.0.2) Cacciari, Matteo; Salam, Gavin P.; Soyez, Gregory The European Physical Journal C, Vol. 72, Issue 3 https://doi.org/10.1140/epjc/s10052-012-1896-2	journal	March 2012
Event generator tunes obtained from underlying event and multiparton scattering measurements Khachatryan, V.; Sirunyan, A. M.; Tumasyan, A. The European Physical Journal C, Vol. 76, Issue 3 https://doi.org/10.1140/epjc/s10052-016-3988-x	journal	March 2016
The Machine Learning landscape of top taggers Kasieczka, Gregor; Plehn, Tilman; Butter, Anja SciPost Physics, Vol. 7, Issue 1 https://doi.org/10.21468/SciPostPhys.7.1.014	journal	January 2019
root-project/root: v6.18/02 Brun, Rene; Rademakers, Fons; Canal, Philippe https://doi.org/10.5281/zenodo.3895860	software	August 2019
/VBF1Parked/Run2012C-22Jan2013-v1/AOD Collaboration, Cms CERN Open Data Portal https://doi.org/10.7483/OPENDATA.CMS.4P88.F4RS	dataset	January 2017
/QCD_Pt_300to470_TuneCUETP8M1_13TeV_pythia8/RunIISummer16MiniAODv2-PUMoriond17_80X_mcRun2_asymptotic_2016_TrancheIV_v6-v1/MINIAODSIM Collaboration, Cms CERN Open Data Portal https://doi.org/10.7483/OPENDATA.CMS.DAY1.ZIQE	dataset	January 2019
Sample with jet, track and secondary vertex properties for Hbb tagging ML studies HiggsToBBNTuple_HiggsToBB_QCD_RunII_13TeV_MC Duarte, Javier CERN Open Data Portal https://doi.org/10.7483/OPENDATA.CMS.JGJX.MS7Q	dataset	January 2019
/BulkGravTohhTohbbhbb_narrow_M-600_13TeV-madgraph/RunIISummer16MiniAODv2-PUMoriond17_80X_mcRun2_asymptotic_2016_TrancheIV_v6_ext1-v1/MINIAODSIM Collaboration, Cms CERN Open Data Portal https://doi.org/10.7483/OPENDATA.CMS.R5U7.WV97	dataset	January 2019

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