Combining Resummed Higgs Predictions Across Jet Bins
Abstract
Experimental analyses often use jet binning to distinguish between different kinematic regimes and separate contributions from background processes. To accurately model theoretical uncertainties in these measurements, a consistent description of the jet bins is required. We present a complete framework for the combination of resummed results for production processes in different exclusive jet bins, focusing on Higgs production in gluon fusion as an example. We extend the resummation of the jet cross section into the challenging low transverse momentum region, lowering the uncertainties considerably. We provide combined predictions with resummation for cross sections in the jet and jet bins, and give an improved theory covariance matrix for use in experimental studies. We estimate that the relevant theoretical uncertainties on the signal strength in the analysis are reduced by nearly a factor of 2 compared to the current value.
DESY 13244 
I Introduction
The Higgs program at the LHC requires exquisite experimental measurements coupled with precise theoretical predictions. These predictions include inclusive cross sections as well as cross sections with experimental selection cuts. One example is the analysis, where the events are binned by exclusive jet multiplicity Aad:2012tfa (); Aad:2012uub (); Chatrchyan:2012ufa (); Chatrchyan:2012ty (). The power of the analysis comes from the 0jet and 1jet bins, where the background contamination is small and the jet binning allows for a reduction in the Standard Model (SM) background. The exclusive jet cross sections are selected with a transverse momentum veto on final state jets found with a jet algorithm such as anti Cacciari:2008gp (), where jets with are vetoed. Because the Higgs mass peak cannot be reconstructed, a prediction for the SM cross section that includes the experimental event selection cuts, including the jet veto, is used in the measurement of the Higgs signal strength.
Fixedorder predictions, nexttonexttoleading order (NNLO) for the 0jet bin and nexttoleading order (NLO) for the 1jet bin, are currently used to determine the perturbative uncertainties in the expected signal cross section. Predictions at fixed order in perturbation theory can suffer from large uncertainties when selection cuts are applied due in part to unresummed logarithms involving the relevant scales in the process: the veto scale , the Higgs mass , and the of the final state jet, (in the 1jet bin). By resumming these logarithms to all orders the perturbative uncertainties can be considerably reduced.
Whether fixedorder or resummed predictions are used for the cross sections in the 0jet and 1jet bins, the inputs to the experimental analysis require a consistent treatment of the cross sections and uncertainties in the different jet bins since their combination is used in the measurement. Defining
(1)  
simple consistency conditions relate these cross sections:
(2) 
These conditions imply that nontrivial correlations exist between the uncertainties in the different jet bins; for example, scale variation on the 0jet cross section will feed through to the 1jet cross section. This is addressed by maintaining control of the correlations between the exclusive and inclusive jet bins in both the 0jet and 1jet predictions, allowing one to determine all of the entries in the covariance matrix , which can be used to calculate the perturbative theory uncertainties for any quantity built from these cross sections.
Two issues prevent the upgrade of the covariance matrix from a fixedorder one to a resummed one with reduced uncertainties. The first issue is that the resummation of the 1jet bin is only known when , which leaves a large part of the 1jet spectrum unresummed. The second is that no method of consistently combining the resummations of the 0jet and 1jet bins that accounts for all correlations has been given. In this work we solve both of these outstanding problems. We first show how to improve the challenging low region of the 1jet bin by resummation. We do so by using the inclusive 1jet cross section, supplemented with a fixedorder correction from the 2jet cross section, to provide a resummed prediction in the low regime. We provide several crosschecks of this resummation, showing that it smoothly matches onto the resummed predictions at large . We then give a prescription for how to determine the covariance matrix for both fixedorder and resummed predictions. We numerically illustrate our results using the analysis at the LHC. We estimate that the switch from a fixedorder covariance matrix to a resummed one reduces the theoretical uncertainty on the signal strength extracted by the experimental analyses by a factor of two. This is a dramatic reduction, one which will significantly improve our ability to uncover the underlying nature of the Higgs boson.
Two other aspects of our results warrant emphasis. First, the framework we introduce for the combination of the 0jet and 1jet bins is systematically improvable, and can incorporate improved perturbative information as it becomes available. We demonstrate that point in this manuscript. For example, since we are now able to resum the entire 1jet spectrum and therefore include its dominant higherorder terms beyond NLO, we are able to use the NLO prediction for the inclusive 2jet spectrum, which is currently treated at LO in experimental studies Chatrchyan:2012ty (). Second, although we focus on the final state, the numerical improvement we find will hold for any Higgs analysis in which the inclusive 2jet bin is analyzed separately from the other jet bins. We also note that although we focus on Higgs production in this work, our framework is applicable to any other process in which the signal is divided according to jet multiplicity.
Our paper is organized as follows. In Sec. II, we discuss the general form of the theory covariance matrices for both fixedorder and resummed predictions. In Sec. III, we show how the 0jet resummed predictions along with fixedorder corrections may be used to make a resummed prediction for the low region of the exclusive 1jet cross section. In Sec. IV, we apply this framework to produce predictions for the cross section and uncertainties for the complete 0jet and 1jet bins. We present an illustrative example that is phenomenologically relevant to the current analysis, and show how the uncertainties are reduced in the measurement of the signal strength. Finally, in Sec. V we conclude.
Ii Perturbative Uncertainties in Jet Binning
Whether cross section predictions are fixedorder or resummed, scale variation is the primary tool for assessing theoretical uncertainties due to unknown higherorder perturbative corrections. In this section we discuss the general parametrization of perturbative uncertainties in exclusive jet bins in terms of the full theory covariance matrix. We then give the methods for how the uncertainties can be reliably estimated and how to determine the full covariance matrix for both fixedorder and resummed predictions.
ii.1 General Parametrization
A convenient way to describe the perturbative uncertainties involved in the jet binning is in terms of fully correlated and fully anticorrelated components. Following Refs. Stewart:2011cf (); Gangal:2013nxa (), for a single jet bin boundary between and jets, this amounts to parametrizing the covariance matrix for as
(3) 
where the first contribution, denoted with a superscript “y”, is interpreted as an overall yield uncertainty which by definition is 100% correlated between the two bins and . The second contribution is the migration uncertainty which is anticorrelated between the bins. It corresponds to the uncertainty introduced by the binning which separates from jets, and by definition drops out in the sum .
For the combination of the exclusive 0jet, exclusive 1jet, and inclusive 2jet bins, we choose to write the covariance matrix in the basis . We then have the general parametrization
(4) 
The yield uncertainties described by are fully correlated between all jet bins,
(5) 
where , , and are the yield uncertainties for each jet bin. The migration uncertainties are
(6) 
A priori, the migration uncertainties of the 0jet boundary and of the 1jet boundary can have a nontrivial correlation, which is encoded in the additional parameter . The structure of is fixed by the requirement that in the sum any dependence on the 1jet boundary must drop out, while in the sum any dependence on the 0jet boundary must drop out. Together this automatically implies that in the total cross section any migration uncertainties drop out as they must, i.e., all elements of must sum to zero.
ii.2 FixedOrder Predictions
At fixed order, a direct scale variation is typically used, where the renormalization and factorization scales are varied around central values. Using a common (correlated) scale variation for all jet bins amounts to setting and . However, this can lead to artificial cancellations in exclusive cross sections in the regime where the logarithmic corrections are not small and the migration uncertainties cannot be neglected Stewart:2011cf ().
One method to ameliorate this cancellation and obtain a more reliable uncertainty estimate in exclusive jet bins is to explicitly take into account an estimate of the migration uncertainty using the ansatz
(7) 
where the uncertainties in the inclusive cross sections are determined by the usual direct scale variation. This socalled “ST method” was proposed in Ref. Stewart:2011cf (), and has been adopted in various exclusive analyses at the LHC and Tevatron including the ATLAS and CMS Higgs analyses. An alternative approach, the “efficiency method”, was proposed in Ref. Banfi:2012yh ().
This ansatz assumes the dominance of the large logarithmic corrections in the perturbative expansion. Since the yield and migration uncertainties are independent, the limit implies that the inclusive fixedorder uncertainties and are treated as uncorrelated. The inclusive jet and inclusive jet cross sections are sensitive to different logarithms. The former depends on the cut separating the jet and ()jet bins, while the latter depends on the cut dividing the jet and ()jet bins, which are independent parameters for . As long as the logarithms are the dominant source of corrections, it is justified to treat these uncertainties as independent, which implies that and are assumed to be uncorrelated so .
In terms of the full covariance matrix , the covariance matrix elements between two inclusive jet cross sections is then given by
InclusiveInclusive :  
(8) 
between inclusive and exclusive jet cross sections they are
InclusiveExclusive :  
(9) 
and between exclusive jet cross sections they are
ExclusiveExclusive :  
(10) 
For our case of interest, the resulting fixedorder covariance matrix in the basis is
(11) 
Here, each of the is determined by direct scale variation in the corresponding inclusive fixedorder cross section . The inclusive 1jet and 2jet cross sections, and , depend on the choice of as well as the jet algorithm.
ii.3 Resummed Predictions
Resummed predictions have more handles to estimate the perturbative uncertainties through scale variation of the various factorization and matching scales present in the resummed cross section. This means that one generally has finer control over the uncertainties, but also that care must be taken not to overestimate or underestimate them.
In a given resummed jet bin, one can identify two different types of uncertainties, which are defined precisely in Ref. Stewart:2013faa (): First, an overall fixedorder component of the uncertainty, , which is estimated by collectively varying all of the scales that appear in the resummed prediction. This variation is therefore insensitive to the logarithms of the various scale ratios in the result. Instead, it probes the nonlogarithmic contributions and reduces to the usual fixedorder scale variation in the limit of large . This component is identified with the yield uncertainty, , so
(12) 
Since the cross sections in these jet bins sum to the total cross section, the yield uncertainties sum to the uncertainty in the total cross section, :
(13) 
For our purposes this relation defines .
Second, the resummed component of the uncertainty, , is estimated by varying the individual resummation scales in separate directions and probes the impact of the logarithmic corrections in the cross section. Since the migration between jet bins is sensitive to the logarithm of the corresponding jetbin separation parameter (i.e., the value), this motivates the identification of the resummed component of the scale variation with the anticorrelated migration uncertainty,
(14) 
The precise determination of the elements , , and in our case is nontrivial and discussed further in Sec. III.
ii.4 Current Status of Predictions
The full covariance matrix in Eq. (4), determined either in fixed order as in Eq. (11) or via resummation, allows one to simultaneously describe the theoretical uncertainties associated with the perturbative expansion for the 0jet and 1jet bins. For Higgs production, we briefly summarize the results which are available to determine the elements of these matrices.
At fixed order, the jet cross section is known at NNLO Anastasiou:2005qj (); Catani:2007vq () and the jet cross section is known at NLO Glosser:2002gm (); Ravindran:2002dc (). The jet cross section at NNLO is currently being computed using new techniques Czakon:2010td (); Boughezal:2011jf (), with results available in the channel Boughezal:2013uia (). The full NNLO result can be expected to substantially lower the uncertainty of the NLO result. All of these results are in the effective theory obtained by integrating out the top quark. Several theoretical refinements beyond this approximation are also available for these cross sections, including electroweak effects Aglietti:2004nj (); Actis:2008ug (); Anastasiou:2008tj (); Keung:2009bs (); Brein:2010xj (); Passarino:2013nka () and finite quarkmass corrections Spira:1995rr (); Harlander:2009my (); Harlander:2012hf (). In our results we rescale the 0jet and 1jet cross sections by the ratio of the leadingorder jet cross section between the full and the effective theories, which is known to give a good approximation to the quarkmass effects. For simplicity we do not include electroweak corrections; they are small, at the percentlevel, and do not modify any conclusion of our study.
Predictions for the resummed 0jet cross section are available from several groups Banfi:2012yh (); Banfi:2012jm (); Becher:2012qa (); Becher:2013xia (); Tackmann:2012bt (); Stewart:2013faa (); Banfi:2013eda (). Each includes resummation at least through NNLL and fixedorder matching to NNLO, and the results are generally in good agreement. For the 1jet cross section an additional scale is present, complicating the factorization theorem. In the high regime, , the factorization theorem is known, resummation can be performed, and results for the 1jet cross section are available through the level Liu:2012sz (); Liu:2013hba (). We note that nonglobal logarithms Dasgupta:2001sh () first occur in the 1jet cross section at the level. Their numerical impact was estimated in Ref. Liu:2013hba () to be at or below the percent level of the exclusive jet cross section for the relevant values of and , and therefore do not affect phenomenology.
In the small regime (), a complete factorization theorem has not yet been derived and only fixedorder results are available so far. This complicates predictions for the combined 0jet and 1jet bins. The 1jet cross section is largest in the low regime, and the fixedorder prediction in that regime has large uncertainties. It is also challenging to combine the fixed order with the resummed predictions across the remainder of phase space, as a hybrid between Eq. (11) and Eqs. (12) and (14) would be needed to describe the uncertainties and correlations between jet bins. In the next section we will study this transition in more detail, using the 0jet results to provide a resummed prediction in the low regime.
Iii The Transition Between 0jet and 1jet Bins
iii.1 Construction of the 1jet Bin
As discussed in the previous section, the direct resummation of the exclusive 1jet bin can only be performed when is much larger than and of order . We therefore divide the low and high regimes using a parameter :
(15) 
If an event has then it is in the 0jet bin. In practice, is taken to be around . The second term in this relation can be directly resummed to NLL+NLO using the results of Refs. Liu:2012sz (); Liu:2013hba (). To obtain a result for the first term that is improved beyond fixed order by resummation, we note that the following identity can be used to relate the exclusive 1jet cross section to the inclusive 1jet and inclusive 2jet cross sections:
(16) 
The first bracketed set of terms give the cross section for one or more jets between and . The second bracketed set of terms provides a correction to have only one jet in this range. Using the relation in Eq. (16), we can construct a (partially) resummed prediction for , as the inclusive 1jet cross section in the first brackets can be obtained from the resummed 0jet cross section, which is known to high accuracy Banfi:2012yh (); Banfi:2012jm (); Becher:2012qa (); Becher:2013xia (); Tackmann:2012bt (); Stewart:2013faa (); Banfi:2013eda (). The inclusive 2jet cross sections in the second bracket can be calculated at fixed order up to NLO.
The difference of inclusive 1jet cross sections is the same as the following difference of 0jet cross sections,
(17) 
For the resummation of the 0jet terms, we use the NNLL+NNLO results of Ref. Stewart:2013faa (). Their difference describes the inclusive 1jet rate through NLO plus an allorders series of the inclusive 1jet logarithms of and . The 2jet terms are calculated at NLO. This means that the leading missing terms in the exclusive 1jet cross section appear at NNLO and come from the inclusive 1jet contribution. These corrections can contain at most a single logarithm of the ratios and as well as possibly large nonlogarithmic corrections. However, we will show that the resummation of the 0jet terms can capture NNLO 1jet terms that are known to be large, and our predictions may be tested against the complete jet NNLO cross section once the calculation is complete Boughezal:2013uia (). There are additional unresummed corrections in the logarithmic series of the exclusive 1jet cross section induced by the cut on the second jet. These are higherorder terms that convert the resummation from the inclusive to the exclusive 1jet cross section (or equivalently correspond to a resummation of the inclusive 2jet cross sections in Eq. (16)). These terms enter at NLO and beyond in the exclusive 1jet cross section, and we will provide evidence that their contribution is small.
We therefore have two approaches to obtain the exclusive 1jet rate, :

Direct evaluation of the exclusive 1jet cross section. The resummation can be reliably performed for , and is matched onto the fixedorder cross section at . The NLL+NLO resummation in Ref. Liu:2013hba () will be used for this direct approach.

Indirect evaluation of the exclusive 1jet cross section for . Eq. (16) is used in this case, with the inclusive 1jet (equivalently, the 0jet) terms resummed to NNLL+NNLO using the results of Ref. Stewart:2013faa (). The 2jet terms are calculated at NLO.
The combination of the indirect approach for and the direct approach for will allow for a description of the complete 1jet bin, i.e.,
(18) 
Note that the uncertainty in this combination has to take into account the nontrivial correlations between the 0jet and 1jet resummation uncertainties due to the terms that make up the indirect contribution to the 1jet rate.
iii.2 Uncertainties
First, we must address how to treat the scale variation of the fixedorder 2jet components of Eq. (16). Should their scale variations be assigned to the fixedorder uncertainty or the resummation uncertainty, and how are their scale variations correlated with those of the resummed predictions? Here we follow the same arguments as in the original ST method and assign them to the migration uncertainty. To determine their correlation with the other pieces, we can consider the limit , which corresponds to resumming none of the exclusive 1jet bin. We demand that we reproduce the result of the ST method for pure fixedorder uncertainties in this limit. This leads to the conclusion that the scale variations of the 2jet cross sections are uncorrelated with the 0jet prediction. The correlations between the 2jet components of Eq. (16) and the resummed 1jet spectrum in the high region is not explicitly determined by these limits. For simplicity, we set this correlation to zero.
The yield uncertainties entering in Eq. (5) are then given by
(19) 
Since the yield uncertainties are fully correlated, the yield uncertainty in the 1jet bin is the linear sum from the two regions, and for the region below we used . The individual contributions are evaluated as follows:
(20) 
Next, the migration uncertainties entering in Eq. (6) are given by
(21) 
where the individual contributions are evaluated as follows:
(22) 
The inclusive 2jet uncertainty is given by scale variation of the 2jet fixedorder contributions in Eq. (16).
The first two terms in corresponds to the jet migration uncertainty for the region. Note that contributes to because it removes cross section from the fully inclusive making it more exclusive. The third term in is the jet migration uncertainty for the region. The migration uncertainties between the two regions of are uncorrelated. Finally, the result for in Eq. (III.2), encoding the correlation between and , is determined as follows: the high region of the 1jet bin is directly resummed, and is therefore uncorrelated with the 0jet bin. The low region of the 1jet bin contains a contribution from the difference of 0jet cross sections, as shown in Eq. (16), and and should be treated as correlated, which yields . To see this explicitly, only considering the contributions, the total 1jet migration uncertainty is
(23) 
Next, we will study the indirect approach to the cross section in the 1jet bin for low to show that it provides a valid description in that regime.
iii.3 Testing the Indirect Approach
To show that Eq. (16) improves upon the fixedorder description of the low region, we must demonstrate that a few criteria are fulfilled. First, the contributions from the inclusive 2jet cross section must be small compared to the 0jet terms, so that the resummation can be performed for the bulk of the contribution. Since we will switch to the direct resummation of the 1jet cross section above , we must also show that the two predictions smoothly match onto each other at that point. Finally, we must demonstrate that these first two points are insensitive to the exact numerical value chosen for .
To address the first point, we compute the relevant cross sections at fixed order using MCFM Campbell:2010ff (); Campbell:2010cz (). We use the following set of parameters:
(24) 
The choice of as the central scale choice has been previously argued to be the appropriate scale choice when evaluating Higgs cross sections at fixed order Dittmaier:2011ti (). We use MSTW NNLO PDFs Martin:2009iq (), and set the LHC collision energy to 8 TeV. Defining
(25) 
we plot in Fig. 1 these two contributions to the low 1jet region as a function of in the region . We have evaluated at NLO and at LO in the fixedorder perturbative expansion, so that both contain terms through . The inclusive 2jet correction remains a small fraction of , varying from 6% at GeV to 16% at GeV. This implies that the higherorder terms in the 2jet cross section, those required to convert the resummation of the inclusive 1jet logarithms to the exclusive rate, are small. We therefore conclude that resumming only the 0jet component of Eq. (16) may constitute an improvement of the low prediction.
We next study whether the improvement of the low region proposed in Eq. (16) smoothly matches onto the direct resummation of the high region near . For the 0jet component of Eq. (16) we use the results of Ref. Stewart:2013faa (), while for the 1jet prediction we use the results of Ref. Liu:2013hba (). The choices for the central values of the various scales which appear in each resummed calculation, together with the procedure for varying these scales around their central values to obtain uncertainties, are described in detail in the original papers. We use the NLO prediction for the inclusive 2jet piece of Eq. (16), now with since we are resumming the bulk of the cross section.
One feature we wish to additionally demonstrate with this comparison is that the proposal of Eq. (16) represents a systematicallyimprovable framework that can incorporate future theoretical advances as they become available. We therefore include the 0jet component of Eq. (16) both with and without complex scale setting, which is known to resum large terms in the form factor relevant for Higgs production Parisi:1979xd (); Sterman:1986aj (); Magnea:1990zb (); Ahrens:2008qu (); Ahrens:2008nc (). Similarly, the NNLO hard function (see Ref. Gehrmann:2011aa ()) is known to induce a large correction to the gluonfusion channel of the jet cross section Boughezal:2013uia (). From these results we can find that for the scale choice , the hard function gives a correction to the NLO 1jet cross section of approximately 30%, compared to a total correction of 40% when going from NLO to NNLO. It is the dominant source of the NNLO correction for these parameter choices. Furthermore, the enhancement from the hard function is constant over a large range of , suggesting that its origin is a large constant term similar to the corrections that the complex scale setting resums for the 0jet cross section. We therefore extend the resummation of Ref. Liu:2013hba () to include the NNLO jet hard function. We compare the matching of the low and high regions in two schemes:

Scheme A: complex scale setting for the 0jet terms in the indirect approach, and the direct 1jet cross section with the NNLO hard function incorporated.

Scheme B: no complex scale setting for the 0jet terms in the indirect approach, and the direct 1jet cross section with only the NLO hard function.
Scheme A will lead to larger cross sections due to the corrections and the NNLO hard function, whose effects on the indirect and direct cross sections are roughly equivalent. Scheme A incorporates more known information than Scheme B, and is therefore our preferred choice for matching the 0jet and 1jet bins. We will show that it leads to a smoother matching, and that it is also more independent of the parameter that is used to separate the two regions.
To make predictions in bins of , we must extend Eq. (16), which is only valid for a bin whose lower boundary is the veto scale . The correct generalization comes from the difference of Eq. (16) with different values of :
(26) 
We compare the direct and indirect cross sections in bins of of 10 GeV width between 30 GeV and 80 GeV. The results are shown in Fig. 2.
In both schemes, the indirect and direct 1jet cross sections are in relatively good agreement. The large uncertainties at low in the direct evaluation of the 1jet cross section are reduced by resumming the inclusive 1jet logarithms in the indirect prediction. While these approaches agree within uncertainties for Scheme B, there is a sizable offset between them. Also, the uncertainties without complex scale setting in the 0jet result are large. The matching is significantly improved in Scheme A; the central values are closer, and the uncertainties of the indirect approach are smaller. We note that the scale variation of the direct approach increases below due to large logarithms appearing in the NNLO hard function at low . The smooth matching between these predictions suggests that the indirect evaluation of the 1jet cross section is valid. We will use it for and the direct approach for , as in Eq. (18).
Finally, we show the dependence of the 1jet bin in Fig. 3. The 1jet cross section and its uncertainties are very insensitive to , with the net dependence much smaller than the change in the direct and indirect contributions to the 1jet cross sections over the range of studied. This gives good confidence that the 1jet bin is being accurately described by our method. We note that the dependence on is significantly reduced in Scheme A, providing further motivation for the choice of this scheme as the preferred way to match the 0jet and 1jet predictions.
In the next section we will perform a detailed numerical study of the 0jet, 1jet, and inclusive 2jet cross sections, their uncertainties, and the covariance matrices for these predictions.
Iv Numerical Results for jets
We now have a consistent framework which incorporates resummationimproved predictions, and accounts for the correlations between their uncertainties, for the 0jet and 1jet bins of Higgs production. We summarize the ingredients below.

In the 0jet bin, we use the direct resummation of the cross section as implemented in Ref. Stewart:2013faa (), currently known to . We include the effect of complex scale setting in this prediction.

In the high region of the 1jet bin, we use the direct resummation of Ref. Liu:2013hba (), currently known to . We include the NNLO hard function in this prediction.

In the low region of the 1jet bin, we use Eq. (16). The 0jet components of this equation are obtained from the 0jet resummation, while the inclusive 2jet pieces are obtained from MCFM at NLO. We note that since we are now able to resum the entire 1jet cross section and consequently include its dominant corrections beyond NLO, it is consistent to use the NLO result for the inclusive 2jet piece rather than the LO one.
For the covariance matrix, we can directly use the results of Eqs. (12) and (14). The relations we have between the 0jet and 1jet cross sections allow us to determine the covariance matrices and . This has been discussed in detail in the previous section, where all entries in the matrices have been given explicitly. In this section, we will give the numerical cross sections in each jet bin, their uncertainties, and the covariance matrices that will allow for the calculation of the uncertainties in any observable based on these rates. We will compare the results of the resummed predictions to those obtained at fixed order, to demonstrate the improvement obtained. We perform this study for the ATLAS and CMS parameters, taking :
(27) 
As in our previous numerical study we use MSTW NNLO PDFs, and assume an 8 TeV LHC.
iv.1 Results at Fixed Order
We now present numerical results at fixed order using the ST method as discussed in Sec. II.2. Since this is how the uncertainties in the 0jet and 1jet bins are currently evaluated, the values we give here are intended to be benchmarks for comparison to our resummed results. Recall that the cross sections for exclusive jet bins are obtained from differences of inclusive cross sections, meaning that we need inclusive cross sections with their scale variations. These and the exclusive cross sections are listed in Table 1.
rate [pb]  ATLAS ()  CMS () 

19.27 1.50  19.27 1.50  
7.85 1.41  6.47 1.27  
2.42 1.80  1.73 1.31  
11.69 2.06  12.80 1.97  
5.16 2.29  4.75 1.82 
We obtain the result for the total inclusive cross section from the Higgs cross section working group LHCXS (), while the results for the inclusive 1jet and 2jet cross sections are obtained from MCFM. As discussed previously, we use the central scale choice for these fixedorder quantities. We find the following numerical values for the entries of the covariance matrices, in the basis of the 0jet, 1jet, and inclusive 2jet cross sections: for ATLAS,
(28)  
while for CMS,
(29) 
We note that the relative uncertainties on the exclusive 0jet and 1jet bins are and respectively for ATLAS, and and respectively for CMS. The relative uncertainty on the sum of 0jet and 1jet bins is obtained by summing the upper block of the covariance matrix, taking the square root, and then dividing by the sum of the cross sections given in Table 1. The numerical result is for ATLAS and for CMS.
iv.2 Results with Resummation
When resummation is used to make predictions for the jet bins, the uncertainties are reduced compared to fixed order. The same parameters as in Eq. (27) are used, with the resummation schemes outlined in Sec. III. The yield and migration uncertainties in the 0jet bin are determined through scale variation, and are provided by the results in Ref. Stewart:2013faa (). The uncertainties in the 1jet bin are given in Sec. III, as is the correlation between the 0jet and 1jet bins, allowing us to completely determine the covariance matrix.
rate [pb]  ATLAS ()  CMS () 

21.69 1.49  21.69 1.49  
12.67 0.87 0.86 ()  13.86 0.70 0.52 ()  
5.68 0.30 0.89 ()  4.97 0.43 0.61 ()  
3.34 0.32 0.47 ()  2.86 0.36 0.44 () 
In Table 2 we show the total, 0jet, 1jet, and inclusive 2jet cross sections in Scheme A, along with their uncertainties. These can be compared with the results in Table 1. As a comparison, the inclusive cross section and its uncertainty in Scheme B is , the 0jet cross sections are (ATLAS) and (CMS), the 1jet cross sections are (ATLAS) and (CMS), and the inclusive 2jet cross sections are (ATLAS) and (CMS).
The uncertainties in Scheme B improve on those at fixed order while the uncertainties in Scheme A are approximately a factor of two smaller than the fixed order ones. We note that the cross section in Scheme A, our preferred matching scheme, is higher than the value obtained by the Higgs cross section working group LHCXS (). We believe that the inclusive cross section used in experimental analyses will eventually have to be updated to a value closer to the number found here, which accounts for newer perturbative information that has recently become available and provides a better matching between the best predictions for the 0jet and 1jet bins. Not only does the effectivefield theory framework used here give a value higher than the current result, recent approximate NLO evaluations of the cross section Ball:2013bra () that feature an improved treatment of the singular limits find a cross section in better agreement with our Scheme A value. As a temporary way of rendering our analysis consistent with the currentlyassumed total cross section, we advocate a global rescaling of the Scheme A numbers in Table 2 with the ratio of the Higgs cross section working group cross section over our .
In Fig. 4, we plot the cross sections in each jet bin against the fixedorder cross sections. The agreement between fixed order and the two matching schemes, as well as the reduced uncertainties when moving beyond fixed order, are clearly visible in the plot. We note that these results, weighted by experimental efficiencies in each jet bin, may directly be used in analyses of the detailed properties of Higgs events. In particular, they can be used to compare to the recent ATLAS measurements of fiducial jetbin cross sections ATLASCONF2013072 (), after taking into account experimental efficiencies and the branching ratio.
Finally, we give the covariance matrices for matching Scheme A: for ATLAS,
(30) 
and for CMS,
(31) 
Like the fixedorder covariance matrices in Eqs. (28) and (29), these results may be used to determine the correlations in any observable built from the 0jet, 1jet, and inclusive 2jet cross sections. The relative uncertainties on the exclusive 0jet and 1jet bins have decreased to and respectively for ATLAS and and respectively for CMS, while the numerical uncertainty on the sum of 0jet and 1jet bins is now for ATLAS and for CMS.
iv.3 Impact on the Determination of the Signal Strength
A key measurement in every given production/decay channel is the coupling of the Higgs boson to other Standard Model particles. In the simplest case, this corresponds to a measurement of the signal strength , the ratio of the experimentally observed cross section to the SM expectation. For the decay channel the theoretical uncertainties discussed here, which are those for the expected signal in the sum of jet bins, are a major component of the theory systematics on . Using the cross sections and the covariance matrices given above, we can estimate the reduction in theoretical uncertainties on that is gained by using resummed results for the cross sections.
The signal strength is defined as the ratio of observed and expected cross sections that pass a set of analysis cuts,
(32) 
ssThe relative theory uncertainty in the signal strength is then equal to the relative theory uncertainty of the expected signal cross section:
(33) 
These expected and observed rates can be written as the sum of cross sections in each jet bin, with acceptances that depend on the cuts in each bin. For the expected rate,
(34) 
The efficiencies are particular to a given analysis, and include the effects of both kinematic selection cuts in the analysis (e.g. cuts on the leptonic final state) as well as all experimental efficiencies (such as from trigger, reconstruction, and particle identification).
Because the measurement sums over contributions from different numbers of jets, the final perturbative uncertainty is reduced compared to that of the individual jet bins due to the anticorrelations between the bins. For the same reason the relative uncertainty on the total cross section is lower than the relative uncertainty in individual jet bins. If the efficiencies in each jet bin are the same, then the uncertainty squared is proportional to the sum over all elements of the covariance matrix, which cancels the migration effects. If the measurement is dominated by the 0jet and 1jet bins (as is the case for gluon fusion), then the sum of entries in the 0jet and 1jet block of the covariance matrix determines the uncertainty. For the fixedorder and resummed results above, this implies that the relative uncertainty in the combined (0+1)jet cross section is 6.9% for ATLAS and 6.5% for CMS using the resummed results and 13.9% for ATLAS and 11.3% for CMS using fixedorder results.
Of course, in general the 0jet and 1jet bins will have different acceptances for a given analysis. As an illustrative example, we use the ATLAS analysis results to estimate the uncertainty on for the resummed results ATLAS:2013wla (). We also perform the analysis using the fixedorder cross section predictions, which allows us to compare the uncertainty in against the value determined by ATLAS (which uses the fixedorder results). We expect that the results of this exercise will be similar for the CMS analysis CMS:bxa ().
The analysis uses leptonic final states with electrons and muons, and divides these final states into two channels: those with two electrons or two muons (), and those with one electron and one muon (). The cuts in each channel are different, with more stringent cuts in the channel to suppress the DrellYan background. Therefore, the efficiency in jet bin is
(35) 
with
(36) 
and analogously for the channel. The efficiencies to be in the or channels include the branching ratio for the decays into the allowed final states as well as the selection cuts for the channel. The efficiencies for the same leptonic channel can differ between jet bins, since the selection cuts depend on the final state lepton kinematics (which change if there are high