Reporting Results in High Energy Physics Papers: a Manifesto

The complexity of collider data analyses has dramatically increased from early colliders to the LHC. Reconstruction of physics objects has reached a point that requires dedicated papers documenting the techniques, and periodic retuning of the algorithms themselves. Analysis methods evolved to account for the increased complexity of the final states sought and for the need of squeezing the last bit of sensitivity from the data; they often involve a full final state reconstruction—mostly relatively easy at lepton colliders, sometimes exceedingly difficult at hadron colliders—or the use of advanced statistical techniques such as statistical learning. The need of keeping the papers documenting results to a reasonable size implies nowadays a greater level of compression or even omission of information with respect to papers from twenty years ago. The need for compression should however not prevent sharing a reasonable amount of information that is essential to understanding a given analysis. Infrastructures like RIVET or HepData have been developed to host additional material, but the amount of material which is sent to these databases is still often insufficient. In this Letter I advocate for an increase in the information shared by the Collaborations, and try to define a minimum standard for acceptable level of information when reporting statistical procedures in High Energy

[1]  P. Clifford,et al.  How to combine correlated estimates of a single physical quantity , 1988 .

[2]  Simplified likelihood for the re-interpretation of public CMS results , 2017 .

[3]  T. Tuuva,et al.  Measurement and QCD analysis of double-differential inclusive jet cross-sections in pp collisions at sqrt(s) = 8 TeV and ratios to 2.76 and 7 TeV , 2016, 1609.05331.

[4]  G. Zanderighi,et al.  $$W^+W^-$$W+W-, $$WZ$$WZ and $$ZZ$$ZZ production in the POWHEG-BOX-V2 , 2013, 1311.1365.

[5]  Stefan Schmitt,et al.  Data Unfolding Methods in High Energy Physics , 2016, 1611.01927.

[6]  D. Zerwas,et al.  The Global Higgs Picture at 27 TeV , 2018, SciPost Physics.

[7]  P. Nason A new method for combining NLO QCD with shower Monte Carlo algorithms , 2004, hep-ph/0409146.

[8]  Luca Lista Combination of measurements and the BLUE method , 2016 .

[9]  Tom Melia,et al.  W+W−, WZ and ZZ production in the POWHEG BOX , 2011, 1107.5051.

[10]  R. Brenner,et al.  Measurement of the W⁺W⁻ production cross section in pp collisions at a centre-of-mass energy of √s = 13 TeV with the ATLAS experiment , 2017 .

[11]  M. Cristinziani Evidence for the production of three massive vectorbosons in $pp$ collisions with the ATLAS detector , 2019, Proceedings of XXVII International Workshop on Deep-Inelastic Scattering and Related Subjects — PoS(DIS2019).

[12]  Frank Krauss,et al.  Soft photon radiation in particle decays in SHERPA , 2008, 0810.5071.

[13]  F. Siegert,et al.  Event generation with SHERPA 1.1 , 2008, 0811.4622.

[14]  P. Nason,et al.  Matching NLO QCD computations with Parton Shower simulations: the POWHEG method , 2007, 0709.2092.

[15]  A. C. Aitken IV.—On Least Squares and Linear Combination of Observations , 1936 .

[16]  G. D'Agostini,et al.  A Multidimensional unfolding method based on Bayes' theorem , 1995 .

[17]  Lukas Heinrich,et al.  HEPData: a repository for high energy physics data , 2017, ArXiv.

[18]  Andy Buckley,et al.  Rivet user manual , 2010, Comput. Phys. Commun..

[19]  S. M. Etesami,et al.  Evidence for $$\text {W}\text {W}$$ production from double-parton interactions in proton–proton collisions at $$\sqrt{s} = 13 \,\text {TeV} $$ , 2019, The European Physical Journal C.

[20]  Tilman Plehn,et al.  The gauge-Higgs legacy of the LHC Run I , 2016, SciPost Physics.

[21]  E. Re,et al.  A general framework for implementing NLO calculations in shower Monte Carlo programs: the POWHEG BOX , 2010, 1002.2581.

[22]  P. Gras,et al.  Les Houches 2015: Physics at TeV colliders - new physics working group report , 2016, 1605.02684.

[23]  D. Rathlev,et al.  W±Z production at the LHC: fiducial cross sections and distributions in NNLO QCD , 2016, 1703.09065.

[24]  G. G. Stokes "J." , 1890, The New Yale Book of Quotations.

[25]  G. D'Agostini,et al.  Improved iterative Bayesian unfolding , 2010, 1010.0632.

[26]  F. Garwood,et al.  i) Fiducial Limits for the Poisson Distribution , 1936 .