I use a dataset containing simulated events of semileptonic $t\bar{t}$ decays ($t\bar{t} \rightarrow W⁺b W⁻ \bar{b} \rightarrow q\bar{q}bl\nu_l\bar{b}$) at CMS, LHC. For each event, the four-momenta of the particles in the final state are stored in the dataset. The algorithm to reconstruct the event now has 24 possibilities to assign (match) the jets originating from the quarks in the final state. As I have simulated data, I know whether this worked out or not. Events can be classified into correctly matched (the algorithm managed to assign each jet to its original particle) or wrong matched. The wrong matched events can be further classified into those, were the two $b$ quarks were swapped, those, where the two other quarks were swapped or some other combinations.
When I sort the events by the matching type of the jets - all jets correctly matched, $b$ quarks swapped, hadronic branches from one of the $W$ bosons swapped, other stuff mixed up,... - and plot their $m_t$ distributions I see, that:
- those events have clearly a much broader $m_t$ distribution even than those, where some of the jets were not matched at all
- those events have top masses reaching far higher on the scale, than other events (again, even than those completely unmatched).
Does someone have a clue, why this is so?
Or, maybe firstly more important: Is it a physical problem? Or does it maybe arise from the reconstruction algorithm.