Direct photon production and PDF fits reloaded
John M. Campbell, Juan Rojo, Emma Slade, and Ciaran Williams.
Fermilab, P.O. Box 500, Batavia, IL 60510, USA.
[0.1cm] Department of Physics and Astronomy, VU University, NL-1081 HV Amsterdam,
and Nikhef Theory Group, Science Park 105, 1098 XG Amsterdam, The Netherlands.
[0.1cm] Rudolf Peierls Centre for Theoretical Physics, 1 Keble Road,
University of Oxford, OX1 3NP Oxford, United Kingdom.
[0.1cm] Department of Physics, University at Buffalo,
The State University of New York, Buffalo 14260, USA.
Direct photon production in hadronic collisions provides a handle on the gluon PDF by means of the QCD Compton scattering process. In this work we revisit the impact of direct photon production on a global PDF analysis, motivated by the recent availability of the next-to-next-to-leading (NNLO) calculation for this process. We demonstrate that the inclusion of NNLO QCD and leading-logarithmic electroweak corrections leads to a good quantitative agreement with the ATLAS measurements at 8 TeV and 13 TeV, except for the most forward rapidity region in the former case. By including the ATLAS 8 TeV direct photon production data in the NNPDF3.1 NNLO global analysis, we assess its impact on the medium- gluon. We also study the constraining power of the direct photon production measurements on PDF fits based on different datasets, in particular on the NNPDF3.1 no-LHC and collider-only fits. We also present updated NNLO theoretical predictions for direct photon production at 13 TeV that include the constraints from the 8 TeV measurements.
The determination of parton distribution functions (PDFs) of the proton [1, 2, 3, 4] is an important component of the LHC program for many analyses, from precision tests of the Standard Model to searches for new physics beyond it. Within the global fitting framework, the gluon PDF has been traditionally constrained by the scaling violations of deep-inelastic scattering (DIS) structure functions and from inclusive jet production . More recently, a number of additional collider observables have demonstrated their constraining power on the gluon PDF, from differential distributions in top-quark pair production  to the boson transverse momentum  and meson production in the forward region [8, 9]. In this respect, the recent NNPDF3.1 global analysis  demonstrated how a robust determination of the medium and large- NNLO gluon PDF can be achieved by the combination of LHC measurements of top-quark pair, , and inclusive jet production — see also the discussion in .
Another process that has been advocated to constrain the gluon in a global PDF analysis is direct (or “prompt”) photon production at hadron colliders. Indeed, direct photon production, , probes the gluon directly at leading order through the QCD Compton scattering process shown in Fig. 1.1. Taking into account the kinematics of available LHC data, direct photon measurements provide information on the gluon in the range between and [12, 13]. In addition, direct photons can also be produced via quark-antiquark annihilation (also shown in Fig. 1.1), such that this process also allows us to probe the contribution of different quark flavours in the same region.
However, exploiting collider measurements of direct photon production to constrain the gluon PDF is complicated by the fact that high- photons can also be produced via the collinear splitting of a final-state quark. These emissions have associated collinear singularities that are absorbed into non-perturbative quark-to-photon and gluon-to-photon fragmentation functions (FFs). This fragmentation component is only loosely constrained by LEP data , therefore inducing a potentially large source of theoretical uncertainty.
In spite of these complications, direct photon production data from fixed-target experiments were used in early global PDF fits, such as those of [15, 16, 17]. However, the increased availability of jet production data from the Tevatron, together with the difficulties in reconciling NLO QCD theory with some fixed-target measurements, led to the abandonment of using photon data to constrain the large- gluon. However, this general feeling that direct photon production data was not suitable for PDF fits was demonstrated to be incorrect by the analysis of Ref. . There it was shown that a good agreement between NLO theory and direct (isolated) photon production measurements could be obtained for a wide range of collider energies from RHIC and SPS to the Tevatron and the LHC at TeV. This analysis also found that the LHC measurements lead to a moderate reduction of the gluon PDF uncertainties in the region around .
Despite the results of this study, none of the most recently-updated global PDF fits [18, 10, 19, 20] include collider direct photon measurements. The reason for this is twofold. On the one hand, the NLO QCD calculations are affected by large scale uncertainties, thus making direct photon production inappropriate for NNLO global analyses that require precision theoretical predictions. On the other hand, in order to relate theory calculations with experimental measurements one needs to account for the poorly-understood fragmentation component.
The first of these objections was removed by the availability of the NNLO QCD calculation , which together with the corresponding electroweak corrections  was found to provide a good quantitative description of the ATLAS measurements at TeV  at central photon rapidities . The second objection can be somewhat alleviated by applying the smooth cone isolation prescription proposed by Frixione . This isolation condition removes the need for fragmentation functions from the theoretical calculation, at the cost of introducing a difference between the isolation definitions used in the theoretical and the experimental analyses. However, as will be discussed later, this difference has been studied at NLO in great detail and found to be of limited practical consequence.
In addition to their relevance for PDF fits, photon production at the LHC is of great interest in searches for new physics beyond the standard model (BSM). For instance, recent searches for BSM physics with photons in the final state from ATLAS and CMS include searches for new particles by looking for high-mass resonances [25, 26, 27], anomalous couplings [28, 29, 30, 31], and by measuring missing distributions [32, 33, 34, 35]. These searches rely on a good understanding of the QCD background for photon production. It is therefore necessary to account for higher order QCD and electroweak corrections and to use recent global PDF fits that can properly model the background and signal events.
With this motivation, the goal of this paper is to revisit the impact of available LHC direct photon production measurements on a global NNLO PDF analysis. Specifically, we will include the ATLAS 8 TeV measurements  into the NNPDF3.1 analysis, in order to quantify the agreement between data and NNLO QCD theory and the corresponding impact on the gluon PDF. We find that a good description of this dataset is achieved, except for the most forward rapidity bin, and show that the inclusion of the photon data leads to a moderate reduction of the gluon PDF uncertainties at medium . These fit results are cross-checked with those of the Monte Carlo Bayesian reweighting procedure [36, 37]. In addition, we aim to study the constraining power of the direct photon production measurements on PDF fits based on different datasets, in particular on the NNPDF3.1 no-LHC and collider-only sets. We also show that using state-of-the-art theory and including the constraints from the 8 TeV direct photon measurements leads to an excellent description of the recent ATLAS 13 TeV data .
The paper is organised as follows. In Sect. 2 we review existing measurements of direct photon production, focusing on the ATLAS data used in the present study. In Sect. 3 we discuss the theoretical setup for computing the theoretical predictions for direct photon production. The impact of the photon data upon the gluon PDF is presented in Sect. 4, and in Sect. 5 we provide updated predictions for direct photon production at 13 TeV. Finally, in Sect. 6 we conclude with a summary of the results and outline possible future developments. The results of the fits with direct photon data are compared with those obtained with the Bayesian reweighting method in Appendix A.
2 Experimental data
There exist many measurements of direct photon production both at fixed-target and at collider experiments (we refer the reader to ref.  for a detailed list). The measurements performed at the highest centre-of-mass energies are those from the LHC and from the Tevatron. At the Tevatron, the CDF and DØ experiments have measured direct photon cross-sections at GeV [39, 40], 1.8 TeV [41, 42, 43, 44, 45] and 1.96 TeV [46, 47, 48]. More recently, the ATLAS and CMS experiments during Run I have performed similar measurements at 7 TeV [49, 50, 51, 52, 53] and at 8 TeV , while thus far during Run II only ATLAS has measured direct photon production at 13 TeV .
In this work, we will concentrate on the ATLAS measurements at 8 TeV and 13 TeV. The 8 TeV data exhibits reduced statistical and systematic uncertainties as compared to their 7 TeV counterparts [51, 53], and is thus suitable for inclusion in a global PDF analysis. The 13 TeV measurements will be used only to compare with our theoretical predictions, but will not be included in the fit since the experimental uncertainties are larger than the 8 TeV data due to the limited integrated luminosity, fb.
The ATLAS 8 TeV direct photon production measurement is presented as differential distributions in the photon transverse energy () in four photon pseudorapidity () bins:
The measurements cover the transverse energy range GeV, though the upper limit is reduced in the more forward bins. As we will discuss in Sect. 3, the kinematic cuts applied constrain the number of points included in the fit to . For each of the experimental bins, the information on the statistical, total systematic and luminosity uncertainties is provided by ATLAS. However, the experimental covariance matrix for this dataset is not publicly available, so we are therefore restricted to adding the total systematic and statistical uncertainties in quadrature. The luminosity uncertainty on the other hand is taken to be fully correlated among all the bins.
As will be discussed in Sect. 4, the most forward rapidity bin, , is excluded from the fit due to the tensions between the experimental data and the theoretical predictions. In this respect, the fact that the covariance matrix is not available implies that we cannot quantitatively study the origin of the tension in this forward bin. Therefore, we have taken a conservative approach and excluded the anomalous bin; in Sect. 4.1 we discuss the impact in the fit of this bin and motivate in more detail its exclusion from our analysis.
In Fig. 2.1 we show the kinematic coverage of the ATLAS 8 TeV data in the plane computed using LO kinematics, alongside with that of the dataset used in the global NNPDF3.1 fit. At LO one may write , so that each datapoint of the 8 TeV measurement corresponds to two points in the plane. From this comparison, we observe that the photon data probes a region only partly covered by other experiments; specifically the medium- range for over two orders of magnitude in . Therefore including the photon data allows one to constrain a new kinematic region beyond the range of previous PDF fits.
Concerning the ATLAS 13 TeV measurements, the data is presented in the same format as at 8 TeV and covers a range between GeV, for a total of datapoints. The covariance matrix is constructed in the same way as for the 8 TeV data, namely by adding statistical and total systematic uncertainties in quadrature, and treating the luminosity uncertainty as fully correlated among all the bins.
In order to distinguish prompt photons (produced in the hard-scattering process) from secondary photons (which occur copiously in decays of hadrons) the experimental analyses apply isolation criteria to the measured photons. Since secondary photons are predominantly associated with a large amount of hadronic activity, the experiments restrict the hadronic radiation that is present in a cone around the photon candidate. The isolation requirement used in the ATLAS analysis is -dependent, optimised to obtain the best signal-to-background ratio. The additional advantage of the relatively tight isolation applied by ATLAS is that it significantly reduces the contribution from prompt photons which are produced in the fragmentation of a hard parton. These contributions also have significant hadronic activity near the photon and are hence suppressed by the isolation condition.
3 Theoretical setup
In this section we outline the NNLO QCD and LL electroweak calculations that are used to compare with the ATLAS direct photon production data. We also describe the settings adopted in the calculation of the NLO QCD predictions, in particular the fast NLO APPLgrid interpolation  that is required to include the photon data in the global analysis.
As discussed in the introduction, direct photon production in hadronic collisions can proceed via two different types of processes. The photon can either be directly emitted as part of the hard-scattering interaction, as in Fig. 1.1, or alternatively can be produced via the collinear fragmentation of a parton. Taking into account these two contributions, the differential cross-section as a function of can be written as
where is the fragmentation function of a parton to a photon carrying momentum fraction and is the PDF of a parton . While and are the standard renormalization and factorization scales, note the appearance of a new scale , known as the fragmentation scale. The NNLO QCD corrections to the direct component of the partonic cross-section have been computed in , while the fragmentation component is only known at NLO.
The need to account for the fragmentation functions can be eliminated by adopting the smooth cone isolation criterion ,
with being the hadronic transverse energy contained in a cone of radius around a photon of , and where , and are parameters of the algorithm. Here the term suppresses the collinear singularity present as , but arbitrarily soft radiation is allowed inside the cone in order to preserve the cancellation of infrared poles in the calculation.
The granularity of an experimental calorimeter is such that this smooth cone isolation can never be directly replicated in experimental analyses, thereby introducing an unwelcome disconnect between theoretical calculations and the data. However, the parameters appearing in the above isolation definition, and , are arbitrary and this allows them to be tuned to replicate the features of a full calculation including fragmentation, Eq. (3.1). Such a study was first performed at NLO in , finding that the values and result in good agreement between the full calculation and the smooth cone result to within a few percent. A similar study was undertaken in the context of di-photon production at NNLO in , for which the parameters and were found to agree well with the fragmentation calculation.
The differences between the two types of isolation criteria were further studied recently at NLO in , finding a small ( correction that is independent of over a range of values similar to the one studied in this paper. In this work, we adopt the smooth cone isolation, Eq. (3.2), with parameters and , and motivated by the above studies we assume that the residual uncertainties due to the choice of isolation prescription are negligible and should not have a bearing on the PDF fits that we perform.
In order to account for the impact of Sudakov effects induced by virtual loops of heavy electroweak gauge bosons, we include the resummation of the electroweak Sudakov logarithms at leading-logarithmic (LL) accuracy. Following the procedure in [22, 58], we set the QED coupling constant to be in the calculation. The electroweak effects may be accounted for by an overall rescaling of the cross-section of the form
with , and being the hadronic center-of-mass energy expressed in TeV.
Since Eq. (3.4) is only valid for , we include in the fit only data such that GeV. This way, we can consistently use NNLO QCD and LL EW theory for all the data bins in the fit. In the central rapidity bin, this extra cut has the additional advantage of minimising the contribution from fragmentation photons, which are not included in our analysis, as the fragmentation contribution decreases with . After applying this kinematic cut, we have datapoints to include in the fit. In addition, after removing the data from the most forward rapidity bin due to the poor , as mentioned in Sect. 2, we are left with datapoints.
Concerning the calculation of the NNLO QCD cross-sections, we start by computing theoretical predictions at NLO accuracy using MCFM  interfaced with LHAPDF6  and APPLgrid using the NNPDF3.1 NNLO PDF set  with the dynamical renormalization and factorization scales set equal to . The output of this calculation is a fast NLO interpolation grid, as required for the inclusion of these measurements in a PDF fit. Subsequently, the NNLO QCD corrections from Ref.  are included in the form of bin-by-bin -factors, defined as:
so that only the perturbative order of the partonic cross-section is varied, but the PDFs are kept the same.
The technical details regarding this NNLO QCD computation can be found in the original publications [21, 57], and we refer the interested reader to these works for more detail. The only non-trivial change from these works is the manner in which the slicing variable is defined. In the original calculations this is set at a fixed value for the entire phase space, GeV. In the present analysis we instead use a dynamic cut that is determined by the photon transverse momentum, . We find that this improves the overall performance of the computation, particularly in the determination of the NNLO corrections at high .
We show in Fig. 3.1 the NNLO QCD -factors, Eq. (3.5), as well as the LL electroweak correction , Eq. (3.4), in the four rapidity bins of the ATLAS 8 TeV measurement . Both corrections become more important in the high regions, where they deviate significantly from 1. We also show in Fig. 3.1 the results of the multiplicative combination of the NNLO QCD -factor and of the LL EW effects, which represents the overall correction applied to the NLO QCD cross-section. We can observe that there is a partial cancellation between the two higher-order effects, since each pulls the NLO cross-section in an opposite direction.
As mentioned above, a fast interpolation of the NLO QCD calculation, required for the subsequent PDF fit, is constructed by interfacing APPLgrid with MCFM. These fast grids may be used to compute the cross-sections for any PDF set other than the one used in the original calculation with a very small calculational overhead. Specifically, we have used MCFM v6.8 interfaced with the MCFM/APPLgrid bridge code and with the HOPPET  PDF evolution program. Note that in this respect MCFM v6.8 had to be patched to reproduce the results of v8.0, which in turn correspond to the results of Ref. , as we verified explicitly.
In order to obtain sufficiently high numerical precision, we ran MCFM in 10 batches with different random seeds and combined the resulting grids using the applgrid-combine script. This MCFM/APPLgrid computation was successfully benchmarked with the NLO code of Ref. , finding excellent agreement. In Fig. 3.2 we plot the ratio of the APPLgrid computations of the NLO QCD cross-section to the corresponding MCFM v6.8 result for the kinematics of the first three rapidity bins of the ATLAS 8 TeV measurement, using in both cases the NNPDF3.1 set as input. We find good agreement between the two methods within the uncertainties from the finite MC integration statistics, which are typically at the permille level.111These fast NLO APPLgrids, matching the selection cuts and the binning of the ATLAS 8 and 13 TeV direct photon production measurements, are available from the authors.
In this section we present the main results of this work, namely the impact of the ATLAS direct photon production data at TeV on the NNPDF3.1 global analysis. NNPDF3.1 is the most up-to-date NNPDF release, including a wealth of new Tevatron and LHC datasets from processes such as Drell-Yan and pair-production and the transverse momentum of bosons. In contrast to previous fits, NNPDF3.1 independently parameterizes the charm content of the proton, eliminating any possible bias related to the assumption that the charm PDF is generated perturbatively .
In this context, an important difference of the present work as compared to the study of Ref.  is that the latter was based on the NNPDF2.1 fit, where the information on the gluon PDF was limited. This is not the case in NNPDF3.1, where the gluon PDF is already reasonably well constrained at medium and small- from the combination of jet, , and data, and therefore we expect the impact of the direct photon data on the gluon to be moderate.
Here we will also study the impact of the direct photon production data on fits based on reduced datasets, in particular the NNPDF3.1 no-LHC data and collider-only fits. We also compare other global PDF sets to the direct photon measurements, specifically MMHT14, CT14, and ABMP16. The corresponding comparisons with the ATLAS 13 TeV measurements as well as with the 13/8 cross-section ratio will then be presented in the next section.
4.1 Comparison to the experimental data
To begin with, using the NNLO QCD theory supplemented with LL electroweak corrections described in Sect. 3, we have computed the differential cross-sections for the distributions of the ATLAS 8 TeV measurement for different PDF sets. In all cases we use their default value for the strong coupling constant; for NNPDF3.1, MMHT14 and CT14 this is and for ABMP16, . In Fig. 4.1 we show the comparison of these theoretical predictions normalized to the central value of the ATLAS measurements, where the error bars on the experimental data are the sum in quadrature of the statistical and systematic uncertainties, while the error bands for the theory predictions include only the PDF uncertainties.
From the comparisons of Fig. 4.1 we see that across the first three rapidity bins, the various sets are in good agreement; in particular in the 3rd bin, NNPDF, CT14 and MMHT14 are very close to each other. We also find that the NNPDF3.1 and ABMP16 sets lead to a better description of the high region in the central bin. On the other hand, one can clearly observe in the most forward bin a large disagreement between theory and data, in particular for ABMP16.
These trends are further examined in Table 4.1, where we compare the total for the different PDF sets. We note that in this computation the experimental definition of the covariance matrix is used , as opposed to the definition  which is only used during the fitting. From Table 4.1 we see that none of the four PDF sets manage to describe the most forward rapidity bin in a satisfactory way. We have verified that this is still the case even when this bin is included in the PDF fit. Given that the full experimental covariance matrix is not available, it is difficult to further investigate the origin of the disagreement between data and theory, and to be conservative we exclude this 4th rapidity bin from the analysis.
Taking into account the contribution from the first three rapidity bins, we see that the best overall value is obtained with NNPDF3.1 with , followed by CT14 and then MMHT14 and ABMP both yielding . Therefore, even before the direct photon production measurements from ATLAS at 8 TeV are included in the fit, the quantitative description of the data using NNPDF3.1 is already reasonably good.
Then in Table 4.2 we show the same comparison but now using only NLO QCD theory and without the LL electroweak corrections. In this case we find that the in all bins is rather poor. Interestingly, the most forward rapidity bin exhibits a slight improvement in the values, however, they are still large. For the three rapidity bins used in the fit, one finds a dramatic improvement in the description of the data upon including the higher-order QCD and EW effects. This comparison highlights the phenomenological importance of the recent NNLO QCD calculation, and why only now we can robustly include the direct photon measurements into the global PDF fits.
|1st bin||2nd bin||3rd bin||4th bin||Total||Total excluding|
|1st bin||2nd bin||3rd bin||4th bin||Total||Total excluding|
4.2 Impact on the global fit
In the following, we denote by NNPDF3.1+ATLAS the results of the fit obtained by adding the ATLAS 8 TeV direct photon production cross-sections to the NNPDF3.1 NNLO global analysis. In Table 4.3 we compare the resulting values of for each of the three rapidity bins included in the fit as well as for their total. We find that the inclusion of the ATLAS direct photon data improves the agreement between the theoretical predictions and the experimental measurements, with the total decreasing from 1.12 down to 0.96. This improvement is particularly marked in the second rapidity bin, where is reduced from 1.61 to 1.37.
|1st bin||2nd bin||3rd bin||Total|
These results suggest that the ATLAS photon measurements seem to be consistent with the rest of the datasets in NNPDF3.1. In order to further investigate this issue, and to determine if the ATLAS photon measurements are in tension with some of the other datasets included in the fit, In Table 4.4 we provide the breakdown of the values for the individual datasets, comparing the results from the NNPDF3.1 and NNPDF3.1+ATLAS sets.
|HERA I+II inclusive||1.16||1.16|
|CDF Run II jets||0.87||0.86|
|ATLAS 7 TeV 2010||0.96||0.96|
|ATLAS high-mass DY 7 TeV||1.54||1.61|
|ATLAS low-mass DY 2011||0.90||0.91|
|ATLAS 7 TeV 2011||2.14||2.05|
|ATLAS jets 2010 7 TeV||0.94||0.92|
|ATLAS jets 2.76 TeV||1.03||1.01|
|ATLAS jets 2011 7 TeV||1.07||1.07|
|ATLAS 8 TeV||0.93||0.93|
|ATLAS 8 TeV||0.94||0.88|
|CMS asy 840 pb||0.78||0.78|
|CMS asy 4.7 fb||1.75||1.76|
|CMS Drell-Yan 2D 2011||1.27||1.29|
|CMS rap 8 TeV||1.01||1.06|
|CMS jets 7 TeV 2011||0.84||0.82|
|CMS jets 2.76 TeV||1.03||1.00|
|CMS 8 TeV||1.32||1.33|
|LHCb 940 pb||1.49||1.49|
|LHCb 2 fb||1.14||1.16|
|LHCb 7 TeV||1.76||1.69|
|LHCb 8 TeV||1.37||1.30|
|Fixed-target lepton DIS||1.207||1.203|
|Fixed-target neutrino DIS||1.081||1.087|
|Top-quark pair production||1.065||1.049|
We observe that the overall fit quality upon inclusion of the photon data is unchanged within statistical fluctuations. In addition, we find that the direct photon data does not appear to exhibit any tensions with existing datasets. In particular, there are no tensions with other datasets which constrain the gluon, such as top-quark pair and inclusive jets production and the transverse momentum distributions. This stability is further highlighted by the comparison in Table 4.5, where we have grouped datasets together in families of related processes. We find that the largest improvements in the values of the indeed correspond to those processes with sensitivity to the gluon PDF. We can thus conclude that the constraints on the gluon from direct photon production are consistent with those of the rest of the datasets in NNPDF3.1.
In order to quantify the impact of the ATLAS direct photon data into the PDFs, in Fig. 4.2 we show the comparison of the gluon PDF at GeV between the NNPDF3.1 and NNPDF3.1+ATLAS fits, normalized to the central value of the former. In the same figure, we also compare the corresponding relative one-sigma PDF uncertainties in both cases. We find two main implications of adding the photon data into NNPDF3.1. The first one is a moderate reduction of the gluon PDF uncertainties in the region , which is consistent with the kinematic coverage spanned by the ATLAS measurements shown in Fig. 2.1.
The second is a downward shift of the gluon central value in the large- region, by an amount of up to two thirds of the PDF uncertainty. For instance at the gluon in NNPDF3.1+ATLAS is about 4% smaller than in NNPDF3.1. Interestingly, the same trend was observed when adding top-quark pair differential distributions to NNPDF3.0 . The overall consistency of the ATLAS direct photon data with the NNPDF3.1 dataset is highlighted by the fact that in the whole range of the two fits are consistent within uncertainties.
In addition to the impact of the photon data on the gluon, it is important to determine if the new data is consistent with the quark PDFs. In Fig. 4.3 we show the comparison of the quark PDFs at GeV between the NNPDF3.1 and NNPDF3.1+ATLAS fits. We find only rather small changes upon the addition of the photon data, both in terms of central values and of uncertainties, The exception is the charm PDF, which decreases in uncertainty across the full range, partly due to its relation to the gluon via perturbative evolution. We therefore conclude that the ATLAS data does not introduce tensions with the quark PDFs, and furthermore does not strongly impact the size of their respective uncertainties.
Finally, in Fig. 4.4 we show the same comparison between theory predictions and experimental data as in Fig. 4.1 now for the NNPDF3.1 and NNPDF3.1+ATLAS sets for the three rapidity bins of the ATLAS 8 TeV data included in the fit. We can see how in this case the predictions obtained with NNPDF3.1+ATLAS as an input move closer to the central values of the experimental data as compared to the NNPDF3.1 baseline, although by a small amount. These findings are consistent with the corresponding variations at the PDF level discussed in Figs. 4.2 and 4.3.
4.3 Impact on fits based on reduced datasets
In addition to assessing the impact of the ATLAS direct photon production data when added to the NNPDF3.1 dataset, we have also studied its impact on fits using reduced datasets, specifically the NNPDF3.1 collider-only fit and no-LHC fits. The former excludes all DIS and Drell-Yan fixed-target data, with the motivation that collider observables might be cleaner and under better theoretical control, while the latter excludes all LHC measurements for specific applications such as in searches for BSM physics.
In the two cases, we find a good overall agreement between theory and data, as indicated in Table 4.6. For the fit without LHC data, the total is reduced from 1.49 to 1.00. Recall that in this fit the constraints on the medium and large- gluon are much looser, basically coming only from the Tevatron jet data, and thus one expects the impact of the ATLAS direct photon data to be more significant. For the collider only fit, the total is already very good to begin with, 0.94, and is further reduced to upon the addition of the photon data. This moderate improvement is consistent with the fact that the bulk of the gluon-sensitive datasets in NNPDF3.1 are already included in the collider-only dataset. Another interesting result from Table 4.6 is that in all cases an improved description of the three rapidity bins is obtained.
|1st bin||2nd bin||3rd bin||Total|
|NNPDF3.1 no LHC data||1.26||2.07||0.96||1.49|
|NNPDF3.1 no LHC data+ATLAS||0.66||1.39||0.84||1.00|
|NNPDF3.1 collider only||0.89||1.29||0.68||0.94|
|NNPDF3.1 collider only+ATLAS||0.92||1.15||0.64||0.87|
Next in Fig. 4.5 we show the same comparisons as in Fig. 4.2 but now for the NNPDF3.1 no-LHC and collider-only fits. In the case of the no-LHC fit, we find that the impact of adding the ATLAS photon data is larger than in the global fit, both in terms of the shift in the gluon central values and in the reduction of its PDF uncertainties. This is consistent with the fact that is less constrained in the no-LHC fit than in the global fit. The trend in central values is the same for the collider-only fits: moderate enhancement at medium followed by a suppression at large . The impact of the ATLAS photon data is also moderate at the level of PDF uncertainties in the collider-only fit.
To summarize, the results of this study demonstrate that the qualitative impact of the ATLAS 8 TeV direct photon production data on the gluon PDF in the fits based on reduced datasets is consistent with that of the global analysis. In all cases, we find an improvement in the quantitative description of the ATLAS data, as shown in Table 4.6. Interestingly, we also find that the direct photon data prefer a softer gluon at large irrespective of the input dataset used, a trend that is similar to the one induced by the top-quark pair differential cross-sections.
5 Direct photon production at 13 TeV
In this section we present the comparison between state-of-the-art theoretical predictions and experimental data for the recent ATLAS measurements of direct photon production at 13 TeV . The motivation is two-fold. On the one hand, we want to verify whether or not we can quantitatively describe direct photon production at 13 TeV, and in particular understand if the disagreement found for the most forward bin at 8 TeV (see Sect. 4.1) is also present at a higher center-of-mass energy. On the other hand, we aim to provide predictions for direct photon production at 13 TeV that include the constraints from the same process at 8 TeV: we will do this by using the NNPDF3.1+ATLAS fit constructed in the previous section.
To begin with, in Table 5.1 we provide the values for different NNLO PDF sets to the ATLAS 13 TeV measurements using the theory settings described in Sect. 3. We also include here the predictions using the NNPDF3.1+ATLAS set, which accounts for the constraints of the 8 TeV photon measurements. We find that the different PDF sets provide an equally satisfactory description of this dataset, with the total in all cases. In particular, we find an excellent description of the most forward rapidity bin (with the exception perhaps of ABMP16), in contrast to what was found at 8 TeV. One should note, however, that this measurement is based on a relatively small integrated luminosity, fb, and therefore its uncertainties are larger than for the 8 TeV case, explaining the reduced discrimination power.
|1st bin||2nd bin||3rd bin||4th bin||Total|
As can be seen from Table 5.1, the differences in the values of between NNPDF3.1 and NNPDF3.1+ATLAS are small. This may be further observed in Fig. 5.1, where we compare the theory predictions for the 13 TeV data with both NNPDF3.1 and NNPDF3.1+ATLAS. In addition to the PDF uncertainties shown in the previous cases (darker bands), here we also include the scale uncertainties associated with the NNLO QCD calculation (lighter bands), as discussed below. The two PDF sets are in good agreement with each other and the limited statistics of the measurement do not allow us to discriminate among them. This can also be seen from the fact that the experimental uncertainties are significantly larger than the differences between the two theoretical predictions. It is also interesting to take a closer look at the most forward rapidity bin of the 13 TeV measurement, which in the 8 TeV case had to be excluded from the fit. Here instead we find reasonably good agreement between theory and data, although again, there are larger experimental errors in this bin and therefore one cannot conclude that the description of the 13 TeV data is better than at 8 TeV.
As mentioned above, we also indicate in Fig. 5.1 the scale uncertainties associated with the NNLO QCD calculation (shown as the lighter error bands) in addition to the standard PDF uncertainties. These scale uncertainties have been estimated using the standard practice of independently varying the renormalization and factorization scales by a factor of two. For the majority of bins, the scale uncertainty is , reaching a maximum of in the most forward rapidity bin at high . At NLO, we find the typical size of the scale uncertainty to be approximately double that of the NNLO one, thus compounding the requirement to have the NNLO predictions in order to adequately describe the direct photon data.
One of the main differences that arises in the comparison between data and theory at 8 TeV and 13 TeV, as we discussed, is that the most forward rapidity bin is poorly described in the former case, while it is reasonably well described in the latter. A possible way forward to understand the origin of this discrepancy is to take ratios of the cross-section measurements at the two centre-of-mass energies. Such ratios are useful since many theoretical and experimental systematic uncertainties cancel out , allowing us to elucidate possible issues arising for individual center-of-mass energies. With this motivation, we have constructed the following ratio
for those bins where both and overlap between the two center of mass energies, corresponding to a total of 47 bins. Since the experimental covariance matrix is not available at either of the two center-of-mass energies, the uncertainty on the ratio Eq. (5.1) is obtained by adding in quadrature the total experimental errors in the numerator and the denominator. For the theoretical calculation of Eq. (5.1), the correlation between the PDF uncertainties at 8 TeV and 13 TeV is accounted for.
In Fig. 5.2 we show a comparison between the experimental measurements of the ratio, Eq. (5.1), with the corresponding calculations using the NNPDF3.1 and NNPDF3.1+ATLAS sets, normalized to the central value of the experimental data. Here the theoretical uncertainty band includes only the contribution from the PDF uncertainties. From this comparison we find that there is good agreement between data and theory for all the bins, including for the most forward rapidity bin which was problematic at 8 TeV. The results of Fig. 5.2 suggest that the underlying reason for the disagreement at 8 TeV in the most forward bin, either an inadequacy of the theory calculation or some issue with the experimental measurement, is a common effect between the two center of mass energies which mostly cancels out when computing their ratio.
In order to further understand how the cross-section ratio Eq. (5.1) behaves as a function of and , in Fig. 5.3 we show the same comparison as in Fig. 5.2 but this time without normalizing to the experimental data. We can see that there is excellent agreement between theory and data in all rapidity bins, both at low and high values of ; moreover, we can also observe that the trend in the data-theory agreement is consistent across all the rapidity bins. These results therefore compound the argument that there is some inadequacy in either the theory or the experimental analysis for the most forward bin at TeV.
In order to substantiate this point, in Table 5.2 we provide the values for the ratio of cross-sections between 13 TeV and 8 TeV, Eq. (5.1), with different input PDFs. As we can see from this comparison, all PDF sets are in agreement with the cross-section ratios, both for the total dataset and for the individual rapidity bins. In particular, we find that the description of the cross-section ratio in the most forward bin is the best with NNPDF3.1+ATLAS. Table 5.2 provides further evidence that the origin of the disagreement between theory and data at 8 TeV in this bin is common with the 13 TeV case, since it mostly cancels in the ratio.
|1st bin||2nd bin||3rd bin||4th bin||Total|
The quantitative understanding of the detailed features of photon production at the LHC is of crucial importance for a wide range of analyses, from searches for Higgs decays and BSM resonances to precision Standard Model measurements. In this work, we have revisited the possibility of using direct photon production from the LHC to constrain the parton distribution functions of the proton within a global QCD fit. By using state-of-the-art NNLO QCD calculations combined with LL electroweak corrections, we have quantified the impact of the ATLAS 8 TeV photon production data on the gluon PDF from the NNPDF3.1 global analysis.
Our results indicate that the LHC direct photon production data leads to both a moderate reduction of the gluon uncertainties at medium- and a preference for a somewhat softer central value at large-. These effects are more marked when the direct photon data is added on top of fits based on reduced datasets, in particular the NNPDF3.1 no-LHC fit. We have also demonstrated that including both NNLO QCD and LL electroweak corrections is required in order to achieve a quantitative agreement with the experimental data for the entire kinematic range in and . Moreover, we find that the constraints from the direct photon data are consistent with those of other gluon-sensitive measurements included in NNPDF3.1 such as the , inclusive jets, and differential distributions.
Here we have also provided theoretical predictions for the ATLAS measurements of direct photon production at 13 TeV as well as for the ratio of cross-sections between 13 TeV and 8 TeV. In this case, we find that due to the relatively small integrated luminosity used for the 13 TeV measurement, its discrimination power is rather limited. It would therefore be important to repeat the 13 TeV analysis using the full integrated luminosity of Run II, in order to complement the information provided by the 8 TeV data. In this respect, it is essential that the experimental collaborations make public the covariance matrices of their measurements, else their lack of availability limits the physics output that can be extracted from their own data.
Our results demonstrate that there is no reason, neither in principle
nor in practice, for excluding collider direct photon data
from a global PDF analysis.
Indeed, the most precise LHC measurements available agree well with state-of-the-art
theoretical predictions, and the latter can be included in global PDF analyses using fast interpolation tables.
The information provided by the ATLAS 8 TeV direct photon measurements
turns out to be consistent with the constraints provided by other gluon-sensitive datasets included in
NNPDF3.1, and leads to a moderate
reduction of the gluon uncertainties.
For these reasons, collider direct photon production should be rightfully restored to its
well-deserved position as a full member of the global PDF analysis toolbox.
The main output of this work, the NNPDF3.1+ATLAS NNLO fit, is available in the LHAPDF6 format  from the NNPDF collaboration webpage
with the file name NNPDF31_nnlo_as_0118_directphoton. In addition, the fast NLO tables computed using MCFM and APPLgrid for the ATLAS 8 TeV and 13 TeV direct photon measurements produced in this work, together with the corresponding NNLO/NLO -factors Eq. (3.5), are also publicly available from the same website.
We thank Ulla Blumenschein, Ana Cueto Gómez, Jan Kretzschmar, Claudia Krueger, Matthias Schott, and Juan Terrón Cuadrado for information and discussions concerning the ATLAS direct photon measurements. J. R. and E. S. are grateful to our colleagues of the NNPDF collaboration for their support and useful discussions. E. S. thanks Rhorry Gauld for providing useful scripts and Alberto Guffanti for help with the production of APPLgrids. J. R. and E. S. are supported by the ERC Starting Grant “PDF4BSM”. The work of J. R. is also supported by the Dutch Organization for Scientific Research (NWO). C.W. is supported by a National Science Foundation CAREER award PHY-1652066. This manuscript has been authored by Fermi Research Alliance, LLC under Contract No. DE-AC02-07CH11359 with the U.S. Department of Energy, Office of Science, Office of High Energy Physics.
Appendix A Reweighting study
An alternative strategy to quantify the impact of the ATLAS direct photon production measurements on the NNPDF3.1 global analysis is the Bayesian reweighting procedure [36, 37]. This technique allows one to determine the effects of a new dataset onto a Monte Carlo PDF set without refitting, and is therefore less computationally intensive. The only required inputs are the values of the figure of merit to the new dataset computed using each of the replicas of the prior PDF set.
Given a dataset with data points, the Bayesian reweighting procedure assigns a weight to the -th Monte Carlo replica given by
so that replicas that lead to theoretical predictions in disagreement with the new dataset (and that thus lead to larger ) receive a small weight and are thus effectively discarded. The reweighting procedure also defines the effective number of replicas, , given by the Shannon entropy:
which allow us to quantify how strongly the new data restricts the prior PDF set by how many replicas are left. The interpretation of Eq. (A.2) is that the smaller the ratio , the higher the amount of new information that is being added by this specific experiment into the fit.
Using identical experimental data, kinematic cuts, and theoretical settings adopted to produce the NNPDF3.1+ATLAS set described in Sect. 4, we have reweighted the NNPDF3.1 NNLO set with replicas using Eq. (A.1). The resulting reweighted PDF set is denoted by NNPDF3.1+ATLAS(rw). This reweighted set has been subsequently unweighted to a reduced number of replicas equal to the effective number of replicas , which can then be directly compared with the results of Sect. 4. For the total ATLAS direct photon production 8 TeV dataset, we find that . In other words, , reflecting the moderate impact of the direct photon data on the NNPDF3.1 analysis
In Table A.1 we provide the same comparison as in Table 4.3, now adding as well the values corresponding to NNPDF3.1+ATLAS(rw) set. We also indicate the value for corresponding to the total dataset. Note that we evaluate the reweighted in each of the rapidity bin using the weights computed from the full dataset. The overall agreement between the fitted the reweighted versions of NNPDF3.1+ATLAS(rw) is reasonably good, with residual differences traced back to the moderate loss of information involved in the reweighting. From Table A.1 we observe that the value of for the ATLAS direct photon data is 1.12 before the fit, reduced to 0.96 in the fit and 1.03 after reweighting, so both methods yield consistent results taking into account the statistical fluctuations of the itself.
|NNPDF3.1||NNPDF3.1+ATLAS (fit)||NNPDF3.1+ATLAS (rw)|
Concerning the comparison between fitting and reweighting at the PDF level, in Fig. A.1 we show an updated version of Fig. 4.2 now adding also the results of the NNPDF3.1+ATLAS(rw) set. We see that the results of both gluons are close to each other, and in particular that both the fitted and reweighted versions of NNPDF3.1+ATLAS(rw) exhibit the clear preference for a somewhat softer gluon at large . In terms of the gluon PDF uncertainty, also here the results of the fitted and reweighted sets are reasonably similar. Note that in particular in the large- region, , the reduction of the PDF uncertainties as compared to the baseline determined using the two methods is identical.
To summarize, the fitted and the reweighted versions of the NNPDF3.1+ATLAS PDF set are in good agreement with each other. This agreement could be further improved if a larger prior would have been used, specifically the NNPDF3.1 NNLO set with replicas. This is however not required here, since our goal was limited to providing a validation of the qualitative features of the fit results by means of an independent technique.
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