# variables to investigate Monte Carlo methods of t t production

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2 Caitlin Jones Page 2 of the parent top quark the correct daughter lepton and jet must be identified for both the t and t. he first section of this report discusses the use of a variables called M lb and M 2, [3], achieve the correct lepton-jet pairings. he second half of this report focuses on the variable. is an angular variable which has a sensitivity to the top quark p. he table shows that requiring more b-tagged jets improves the purity but does not significantly improve the e ciency Defining the M 2 variable he implementation of the second, pairing algorithm is based on that of [3]. he value of M 2 is found as follows: Create a range of partitions of the missing transverse momentum and assigning that momentum to two neutrinos as p d i. For each possible combination of the jet and lepton for the top and anti-top quark calculate the value the transverse mass of the combination of : M 2 i = m 2 i,vis + 2(E vis i E d i!! p d i ), (3) p vis i Figure : Feynman diagram of t t! ` `+b b 2. Pairing with M 2 and M lb 2.. Pairing with only M lb wo methods to find lepton-jet pairings were considered, the first using one variable named M lb and the second using two variables M lb and M 2. M lb is defined as the combined invariant mass of the lepton and jet. he first pairing algorithm worked as follows: Randomly select two of the jets in the event and calculate the value of M lb = 2 (m l +,b i + m l,bj ) where m l±,i is the invariant mass of the Lorentz vector of the lepton-jet pair. Repeat this for every possible pair of jets and take the lepton and jet combination that gives the minimum value of M lb If this value is less than 55 GeV then take the pair that produced that value as the b quark jets. his method exploits the fact that the value of m l ±,i cannot be greater than the top mass and is normally much less as momentum is carried away by the neutrino. herefore placing a cut on the value of M lb removes incorrect events and biases the selection towards the correct pairing. he e ciency, number of events matched over number of events considered, and purity, number of correctly matched events over number of matched events, of the method are shown in table. It was checked if a pair was correctly matched by comparing to the parton level information. able : E ciencies and Purity for the M lb algorithm. Number of b tagged 2 No Requirement E ciency Purity where: E 2,vis i = m 2 vis +! i, E i = p! d i. (4) p 2,vis Where m i,vis, p vis i is the mass and transverse momentum of the combined Lorentz vector of the lepton and jet. p d i is the transverse momentum of the neutrino. he the value of M 2 is the minimum over di erent partitions of missing momentum of the maximum of the pair of transverse masses: M 2 =min pt {max{m,m 2 }} (5) herefore the interpretation of M 2 is the reconstructed transverse mass of the parent particle that is minimised with respect to the partition of the missing transverse momentum. herefore for any combination of leptons and jets to be physically possible its value of M 2 must be less than or equal to the mass of the parent particle, in this case the top quark Performance of the M 2 algorithm o investigate the performance of the algorithm, for each event the value of M 2 and M lb were calculated for all possible lepton-jet combinations. wo cuts at 76 GeV and 58 GeV for M 2 and M lb respectively were performed (values chosen as the optimised values from [3]). wo types of selection were performed. he first was a tight selection required that only one combination passed both cuts. he second selection was looser and required that either one or two combinations passed either the M 2 or the M lb cut and took the combination with the minimum M 2 value.

3 Caitlin Jones Page M_lb values for different Combinations Mlb pairing Combinations Mlb of all paired events Mlb combination of correctly paired events Mlb of all incorrectly paired events Pt purity and e ciency achieved from pairing using the M lb variable alone. he e ciency and purity for both types of selection was only negligibly changed by the number of b-tagged jets required to consider the event. his suggests that M 2 could be used for b-tagging as it is able to find the jets originating from b quarks without requiring prior b-tagging. Plots of the values of M 2 for combinations which passed each selection are shown in figures 3 and 4. By comparing the combination to the parton level, values were separated into those which were the correct and incorrect combination. he di ering purity for the two selections can be seen easily in the two figures ype of jet pairing Mt2 of correctly paired events 2 ype of jet pairing Mt2 of correctly paired events 4 Mt2 of incorrectly paired events 8 Mt2 of incorrectly paired events Mt2 Figure 2: Plot of the value of (m 2 l +bi + m l b j) for correct and incorrect lepton-jet pairings (above). Plot of the value of M 2 for correct and incorrect combinations (below) Mt2 Figure 3: Plot of the value of M 2 for combinations that passed tight selection; blue dashed- correct combinations, magenta dotted- incorrect combinations, red full-all combinations. he plot shows that nearly all combinations which passed were correct i.e the purity is high. Figure 2 shows the values of M lb and M 2 for correct and incorrect combinations of leptons and jets. A cuto can be seen at approximately 76 GeV and 58 GeV for the correct combinations, suggesting they were appropriate values at which to cut. Additionally, it can be seen that for the M 2 distribution the fraction of incorrect combinations that are above the cut is higher than for M lb, suggesting it is an better variable on which to cut. he e ciency and purity of the algorithm for each type of cut is show in tables 2 and 3. able 2: E ciencies and Purity for the M 2 algorithm with requirement only one jet to passes both cuts. Number of b tagged 2 No Requirement E ciency Purity able 3: E ciencies and Purity for the M 2 algorithm with requirement that either one or two jets passes one or both of the cuts Number of b tagged 2 No Requirement E ciency Purity For the tight selection the purity is very high although the e ciency is low, whereas for the loose selection the e ciency is much higher although the purity is lower. he loose selection is an improvement on both the ype of jet pairing Mt2 of correctly paired events Mt2 of incorrectly paired events Mt2 Figure 4: Plot of the value of M 2 of events that passed the looser selection; blue dashed- correct combinations, magenta dotted- incorrect combinations, red full-all combinations Discussion and further optimization he M 2 and M lb combined algorithm was an improvement on the M lb pairing alone, in particular it was able to o er much higher purity. However in [3] the optimum e ciency and purity were found to be.574 and.985, respectively, with the equivalent of the tight selection. he discrepancy between the e ciencies could be due to a di erent method of b-tagging, or a lower average number of jets per event. E ciencies could possibly be

4 Caitlin Jones Page 4 improved by increasing the number of partitions of the missing momentum, or optimizing the partition in some other way. 3. Analysing the behaviour of for different Monte Carlo simulations. In [4] the variable is introduced. It is constructed only from angular variables however it has a sensitivity transverse momentum p.currentlythereisatension between the observed data from the ALAS and CMS experiments in the measured top quark p and the MC simulations, and it is unclear why is this the case. Improved tuning of MC simulations, adjusting the parameters of the simulation to match with data, could improve understanding of p behaviour. In order to be able to tune MCs the di erence between MC predictions for a variable must be greater than the uncertainty of the measured variable. As is an angular variable it is measured much more precisely than energy-based variables; for example in the ALAS detector the resolution of momentum is approximately 3 GeV (O(%)) whereas for and the uncertainty is << %. his implies that is a suitable variable to compare MC simulations with. In this project the value of for the decay t t! ` `+b b for 4 types of MC simulation was investigated. is defined as: =sin tan acop 2, (6) where acop is p () transverse momentum and p (2) + p(2) where p () cos = tanh (2) () is the lepton is that of the jet and 2 (7) where () and (2) are the pseudorapidity of the lepton and jet respectively. Figure 5 shows a schematic of how the variables are defined. Figure 5: Sketch showing definition of. Here Q is the lepton-jet transverse momentum, p () is the lepton transverse momentum and p (2) is that of the jet. 3.. behaviour at parton level he values of were calculated from the products of each t and t for each type of MC simulation. Figure 6 shows the absolute values showing that the majority of are close to zero. he lower section of the plot shows the normalised ratio of the MC to Powheg+Pythia6. All three of the the Powheg based simulations o er very similar predictions however di ers by a maximum of 5%. Log Comparing φ* for different MC ypes MC ypes Powheg+Pythia6 Powheg+Herwig++ Powheg+Pythia8 2 φ* Figure 6: Normalised log log plot of for di erent MC simulations. he lower plot shows the ratio of each MC to Powheg+Pythia6.

5 Caitlin Jones Page 5 In order to investigate this further the parton level events where spilt along the value of Ht VIS. Ht VIS is the scalar sum of all the visible products of the t t decay: H VIS t = X p. (8) `,jets he ratio plots of this splitting are shown in figure 7. he events were split such that the number of events in each plot was roughly equal. he values of for each simulation for low and high Ht VIS di ered at low and high. his could be used as a further way to determine if physical data agrees with one simulation over the others. Although the di erences at parton level suggest that is a good variable to distinguish MC simulations, comparisons at particle and reconstruction level are more important as parton level cannot be rigorously constructed from real data for di erent MC. Additionally, at the parton level the di erence in behaviour of the three Powheg based simulations is so small that it would not be possible to say if one fitted the data better than the others behaviour at particle and reconstructed level In order to calculate for the particle and reconstructed level data, the M 2 algorithm with loose selection was used to find the lepton and jet pair for each top decay. he ratio plots of each level can be seen in figure 8.Only events where an electron and a muon were produced were considered. he histogram binning is coarser for the reconstructed and particle level ratio plots as some events are lost to the ine ciency of the M 2 pairing algorithm and due to not recovering all events from parton level. However, it is still possible to see that di erence between the MC simulations is around 5%. he shape of the particle and reconstructed level plot is different for large values than the parton level. his could be due to how showering was simulated. In particular the high of the simulation differed between the particle and parton levels. Additionally, for parton and reconstruction levels there is good agreement between the Powheg+Herwig++, and Powheg+Pythia8 simulations but not between Powheg+Pythia6, which may be due to the former simulations being created more recently. Figure 7: he ratio plot of parton level values of spilt along high, middle and low values of the visible H t showing di erent behaviour for di erent simulations.

6 Caitlin Jones Page 6 Parton Level Particle Level Reconstructed Level Figure 8: Comparison of behaviour for parton, particle and reconstructed level. Particle and recon level have much larger di erences between MCs. he similarity between the particle and reconstructed levels is due to the good resolution of angular variables in the detector so the value of is not significantly altered by detector e ects. Figure 9 is a migration matrix for for the particle against reconstructed level. he figure confirms this good agreement between the two levels as there is is very little smearing. For comparison figure shows a migration matrix of parton against reconstructed level showing less agreement between the two levels. Both figures 9 and used from the Powheg+Pythia6 simulation and the other simulations have very similar behaviour. he varying bin sizes in each histogram are to maximise the resolution of each plot. Powheg+Pythia6 Reconstructed Particle Level Figure 9: A log-log normalised migration matrix of for the particle versus reconstructed level. he data is an good agreement particularly at low where most of the statistics are.

7 Caitlin Jones Page 7 Phi* Values rue Values Reconstructed Values Figure : A log-log normalised migration matrix of for the parton versus reconstructed level. here is some symmetric smearing. 4. Conclusion and Extensions In this project two variables M lb and M 2 were used to resolve pairing ambiguities at the particle and reconstructed level in Monte Carlo data for the event t t! ` `+b b. It was found that pairing with both variables was an improvement on pairing with M lb alone and the optimum selection gave a e ciency of.56 and a purity of.79. Further work could optimise the position of the cuts for MC used here instead of taking them from [3]. he variable was considered for di ering MC simulations at parton, particle and reconstructed level. At parton level it was found that the maximum di erence between MC simulations was 5% between Powheg+Pythia6 and Variation in di erences was found when the parton level was spilt along Ht vis, confirming at is sensitive to p.at particle and reconstructed level the di erence between MCs was also at a maximum of 5%. here was also good agreement between the particle and reconstructed level as show in figure 9. hese results suggest that is a good variable to tune Monte Carlos to as it is sensitive to p and generates di erences in Monte Carlo data that are large enough that the measured data could be sensitive to the di erences. An extension of this work could be to repeat this work with at much large number of MC statistics and with optimised binning to improve the resolution of the ratio plots to better extract information on the behaviour of the MCs. References [] Weinzierl, Stefan. Introduction to monte carlo methods. arxiv preprint hep-ph/ [2] Aad, Georges, et al. he ALAS experiment at the CERN large hadron collider. Journal of Instrumentation 28. [3] Baringer, Philip, et al. Revisiting combinatorial ambiguities at hadron colliders with M 2 Journal of High Energy Physics 2. [4] Vesterinen, M., and. R. Wyatt. A novel technique for studying the Z boson transverse momentum distribution at hadron colliders. Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment 29.

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