5 ms·

As already pointed out, detector efficiency is determined through extremely detailed simulations of the entire system. Those measurements are done in a complete

As already pointed out, detector efficiency is determined through extremely detailed simulations of the entire system. Those measurements are done in a completely orthogonal manner so the complexity of the model has nothing to do with the systematic uncertainties that arise from the selection efficiency.

konschubert 8y ago
> As already pointed out, detector efficiency is determined through extremely detailed simulations of the entire system. It depends on the experiment, LHCb for example does not use simulated background. In any case, the more complex your model gets (number of variables) the exponentially more simulated Monte Carlo events you need to fill that multidimensional space.
- Analog24 8y ago
  I'm not talking about simulating background. Every experiment uses simulation (an extremely accurate and well understood package called GEANT) to simulate the detector response to measure efficiencies. You're absolutely right about how the amount of data needed for statistical significance grows with the size of the parameter space you're searching.
- dukwon 8y ago
  > LHCb for example does not use simulated background. That depends on the analysis. If you're looking at a partially-reconstructed decay (common in semileptonics) then you can't rely on the regular trick of choosing a sideband sample to work as your combinatorial background. Also, it's very common to model specific misidentified or partially-reconstructed backgrounds using simulation. > In any case, the more complex your model gets (number of variables) the exponentially more simulated Monte Carlo events you need to fill that multidimensional space. I understand this argument if you're trying to model the efficiency in nD space (through splines, histograms, moments etc), but that's usually done when you're fitting to n variables, e.g. in an amplitude fit. If you just want the efficiency of a cut on the score from an MVA algorithm, I don't think it matters. What definitely matters is that the behaviour on simulation reproduces that of real signal as faithfully as possible.
  - konschubert 8y ago
    > I understand this argument if you're trying to model the efficiency in nD space (through splines, histograms, moments etc), but that's usually done when you're fitting to n variables, e.g. in an amplitude fit. If you just want the efficiency of a cut on the score from an MVA algorithm, I don't think it matters. What definitely matters is that the behaviour on simulation reproduces that of real signal as faithfully as possible. You might have a point there.

konschubert 8y ago

> As already pointed out, detector efficiency is determined through extremely detailed simulations of the entire system. It depends on the experiment, LHCb for example does not use simulated background. In any case, the more complex your model gets (number of variables) the exponentially more simulated Monte Carlo events you need to fill that multidimensional space.

Analog24 8y ago
I'm not talking about simulating background. Every experiment uses simulation (an extremely accurate and well understood package called GEANT) to simulate the detector response to measure efficiencies. You're absolutely right about how the amount of data needed for statistical significance grows with the size of the parameter space you're searching.
dukwon 8y ago
> LHCb for example does not use simulated background. That depends on the analysis. If you're looking at a partially-reconstructed decay (common in semileptonics) then you can't rely on the regular trick of choosing a sideband sample to work as your combinatorial background. Also, it's very common to model specific misidentified or partially-reconstructed backgrounds using simulation. > In any case, the more complex your model gets (number of variables) the exponentially more simulated Monte Carlo events you need to fill that multidimensional space. I understand this argument if you're trying to model the efficiency in nD space (through splines, histograms, moments etc), but that's usually done when you're fitting to n variables, e.g. in an amplitude fit. If you just want the efficiency of a cut on the score from an MVA algorithm, I don't think it matters. What definitely matters is that the behaviour on simulation reproduces that of real signal as faithfully as possible.
- konschubert 8y ago
  > I understand this argument if you're trying to model the efficiency in nD space (through splines, histograms, moments etc), but that's usually done when you're fitting to n variables, e.g. in an amplitude fit. If you just want the efficiency of a cut on the score from an MVA algorithm, I don't think it matters. What definitely matters is that the behaviour on simulation reproduces that of real signal as faithfully as possible. You might have a point there.