Publishing statistical models: Getting the most out of particle physics experiments

Cranmer, Kyle; Kraml, Sabine; Prosper, Harrison; Bechtle, Philip; Bernlochner, Florian Urs; Bloch, Itay M.; Canonero, Enzo; Chrzaszcz, Marcin; Coccaro, Andrea; Conrad, Jan; Cowan, Glen; Feickert, Matthew; Ferreiro, Nahuel; Fowlie, Andrew; Heinrich, Lukas Alexander; Held, Alexander; Kuhr, Thomas; Kvellestad, Anders; Madigan, Maeve; Mahmoudi, Farvah Nazila; Morå, Knut Dundas; Neubauer, Mark S.; Pierini, Maurizio; Rojo, Juan; Sekmen, Sezen; Silvestrini, Luca; Sanz, Veronica; Stark, Giordon Holtsberg; Torre, Riccardo; Thorne, Robert S.; Waltenberger, Wolfgang; Wardle, Nicholas; Wittbrodt, Jonas

doi:10.21468/SciPostPhys.12.1.037

SciPost Physics

Publishing statistical models: Getting the most out of particle physics experiments

Kyle Cranmer, Sabine Kraml, Harrison B. Prosper, Philip Bechtle, Florian U. Bernlochner, Itay M. Bloch, Enzo Canonero, Marcin Chrzaszcz, Andrea Coccaro, Jan Conrad, Glen Cowan, Matthew Feickert, Nahuel Ferreiro Iachellini, Andrew Fowlie, Lukas Heinrich, Alexander Held, Thomas Kuhr, Anders Kvellestad, Maeve Madigan, Farvah Mahmoudi, Knut Dundas Morå, Mark S. Neubauer, Maurizio Pierini, Juan Rojo, Sezen Sekmen, Luca Silvestrini, Veronica Sanz, Giordon Stark, Riccardo Torre, Robert Thorne, Wolfgang Waltenberger, Nicholas Wardle, Jonas Wittbrodt

SciPost Phys. 12, 037 (2022) · published 25 January 2022

doi: 10.21468/SciPostPhys.12.1.037
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Abstract

The statistical models used to derive the results of experimental analyses are of incredible scientific value and are essential information for analysis preservation and reuse. In this paper, we make the scientific case for systematically publishing the full statistical models and discuss the technical developments that make this practical. By means of a variety of physics cases -- including parton distribution functions, Higgs boson measurements, effective field theory interpretations, direct searches for new physics, heavy flavor physics, direct dark matter detection, world averages, and beyond the Standard Model global fits -- we illustrate how detailed information on the statistical modelling can enhance the short- and long-term impact of experimental results.

TY  - JOUR
PB  - SciPost Foundation
DO  - 10.21468/SciPostPhys.12.1.037
TI  - Publishing statistical models: Getting the most out of particle physics experiments
PY  - 2022/01/25
UR  - https://scipost.org/SciPostPhys.12.1.037
JF  - SciPost Physics
JA  - SciPost Phys.
VL  - 12
IS  - 1
SP  - 037
A1  - Cranmer, Kyle
AU  - Kraml, Sabine
AU  - Prosper, Harrison
AU  - Bechtle, Philip
AU  - Bernlochner, Florian Urs
AU  - Bloch, Itay M.
AU  - Canonero, Enzo
AU  - Chrzaszcz, Marcin
AU  - Coccaro, Andrea
AU  - Conrad, Jan
AU  - Cowan, Glen
AU  - Feickert, Matthew
AU  - Ferreiro, Nahuel
AU  - Fowlie, Andrew
AU  - Heinrich, Lukas Alexander
AU  - Held, Alexander
AU  - Kuhr, Thomas
AU  - Kvellestad, Anders
AU  - Madigan, Maeve
AU  - Mahmoudi, Farvah Nazila
AU  - Morå, Knut Dundas
AU  - Neubauer, Mark S.
AU  - Pierini, Maurizio
AU  - Rojo, Juan
AU  - Sekmen, Sezen
AU  - Silvestrini, Luca
AU  - Sanz, Veronica
AU  - Stark, Giordon Holtsberg
AU  - Torre, Riccardo
AU  - Thorne, Robert S.
AU  - Waltenberger, Wolfgang
AU  - Wardle, Nicholas
AU  - Wittbrodt, Jonas
AB  - The statistical models used to derive the results of experimental analyses are of incredible scientific value and are essential information for analysis preservation and reuse. In this paper, we make the scientific case for systematically publishing the full statistical models and discuss the technical developments that make this practical. By means of a variety of physics cases -- including parton distribution functions, Higgs boson measurements, effective field theory interpretations, direct searches for new physics, heavy flavor physics, direct dark matter detection, world averages, and beyond the Standard Model global fits -- we illustrate how detailed information on the statistical modelling can enhance the short- and long-term impact of experimental results.
ER  -

@Article{10.21468/SciPostPhys.12.1.037,
	title={{Publishing statistical models: Getting the most out of particle physics experiments}},
	author={Kyle Cranmer and Sabine Kraml and Harrison B. Prosper and Philip Bechtle and Florian U. Bernlochner and Itay M. Bloch and Enzo Canonero and Marcin Chrzaszcz and Andrea Coccaro and Jan Conrad and Glen Cowan and Matthew Feickert and Nahuel Ferreiro Iachellini and Andrew Fowlie and Lukas Heinrich and Alexander Held and Thomas Kuhr and Anders Kvellestad and Maeve Madigan and Farvah Mahmoudi and Knut Dundas Morå and Mark S. Neubauer and Maurizio Pierini and Juan Rojo and Sezen Sekmen and Luca Silvestrini and Veronica Sanz and Giordon Stark and Riccardo Torre and Robert Thorne and Wolfgang Waltenberger and Nicholas Wardle and Jonas Wittbrodt},
	journal={SciPost Phys.},
	volume={12},
	pages={037},
	year={2022},
	publisher={SciPost},
	doi={10.21468/SciPostPhys.12.1.037},
	url={https://scipost.org/10.21468/SciPostPhys.12.1.037},
}

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Authors / Affiliations: mappings to Contributors and Organizations

See all Organizations.

¹ Kyle Cranmer,
² Sabine Kraml,
³ Harrison Prosper,
⁴ Philip Bechtle,
⁴ Florian Urs Bernlochner,
⁵ Itay M. Bloch,
⁶ Enzo Canonero,
⁷ Marcin Chrzaszcz,
⁸ Andrea Coccaro,
⁹ Jan Conrad,
¹⁰ Glen Cowan,
¹¹ Matthew Feickert,
¹² ¹³ Nahuel Ferreiro,
¹⁴ Andrew Fowlie,
¹⁵ Lukas Alexander Heinrich,
¹ Alexander Held,
¹² ¹⁶ Thomas Kuhr,
¹⁷ Anders Kvellestad,
¹⁸ Maeve Madigan,
¹⁵ ¹⁹ Farvah Nazila Mahmoudi,
²⁰ Knut Dundas Morå,
¹¹ Mark S. Neubauer,
¹⁵ Maurizio Pierini,
⁸ Juan Rojo,
²¹ Sezen Sekmen,
²² Luca Silvestrini,
²³ ²⁴ Veronica Sanz,
²⁵ Giordon Holtsberg Stark,
⁸ Riccardo Torre,
²⁶ Robert S. Thorne,
²⁷ Wolfgang Waltenberger,
²⁸ Nicholas Wardle,
²⁹ Jonas Wittbrodt

Funders for the research work leading to this publication