Uncertainty of MonteCarlo Simulations: Weight and Error Bars

Click For Summary
SUMMARY

This discussion centers on the application of error bars in Monte Carlo simulations, specifically in the context of particle collisions at the LHC using Madgraph. The user seeks confirmation on calculating Poisson errors for weighted histograms, particularly regarding the treatment of weights and the formula for error bars. It is established that if original events are unweighted, the error bars should be calculated as the square root of the number of events (sqrt(N)), while the integrated luminosity serves only as a scaling factor without introducing additional uncertainty.

PREREQUISITES
  • Understanding of Monte Carlo simulations, particularly in high-energy physics.
  • Familiarity with Madgraph for simulating particle collisions.
  • Knowledge of statistical error analysis, specifically Poisson errors.
  • Basic principles of histogram normalization and integrated luminosity.
NEXT STEPS
  • Research the implications of weighted versus unweighted events in Monte Carlo simulations.
  • Learn about advanced statistical methods for error propagation in particle physics.
  • Explore the use of ROOT framework for data analysis and visualization in high-energy physics.
  • Study the impact of integrated luminosity on experimental results and uncertainties.
USEFUL FOR

Physicists, data analysts, and researchers involved in high-energy particle physics, particularly those working with Monte Carlo simulations and error analysis in experimental data.

Aleolomorfo
Messages
70
Reaction score
4
Hello everybody,
I need a help, primarly a confirmation about my reasoning. I have data from a MonteCarlo simulation of collisions between particles at LHC (made with Madgraph). I have plotted some variables, for example the angle between two final leptons. Then I have normalized the plot to a determined integrated luminosity, so I have applied a weight to the histogram. I'd like to put error bars due to the uncertainty of the generated event from the MonteCarlo, which is a poisson error. So I have taken the content of each bin and then made the square root. But I have some doubt. First of all, shouldn't I take into consideration the weight in some way? Secondly, I'm not so sure about ##\sqrt{N}##, because maybe it should be something like ##\frac{\sqrt{N}}{N-1}.##
Thanks in advance
 
Physics news on Phys.org
Are your original events without weights?
In that case the error bars on the original distribution should be sqrt(N). The luminosity is just a constant scaling for both central value and uncertainties (no uncertainty on the luminosity in MC).

If your original events have weights things can get more complicated. Luminosity stays a constant factor, however.
 
  • Like
Likes   Reactions: Aleolomorfo
Yes, my original events are without weights.
Thank you very much for the answer!
 

Similar threads

  • · Replies 4 ·
Replies
4
Views
1K
Replies
28
Views
4K
  • · Replies 37 ·
2
Replies
37
Views
5K
  • · Replies 1 ·
Replies
1
Views
2K
  • · Replies 0 ·
Replies
0
Views
2K
  • · Replies 3 ·
Replies
3
Views
8K
  • · Replies 4 ·
Replies
4
Views
2K
  • · Replies 6 ·
Replies
6
Views
5K
  • · Replies 1 ·
Replies
1
Views
2K
Replies
6
Views
5K