ATLAS inclusive and sliced samples (eg W+jets)

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In summary, the conversation discusses the use of inclusive and sliced samples in MC generators for high-energy physics. The sliced samples are divided into mass slices for different processes, while the inclusive samples are not. This is done to reduce the number of events and improve statistics at high energies. However, the inclusive sample can be added to improve statistics at low energies, as long as it is independent and accounted for in the merging process.
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ChrisVer
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I have a small technical question, if anyone has ever worked with it...
What does inclusive and sliced samples mean (at a MC generator)? I have seen that the sliced samples are divided according to mass slices for the different processes, but the inclusive are not. Why would they give such samples seperated? I mean as I see it, wouldn't the sum of the sliced samples be the "inclusive" one?
Thanks.
 
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ChrisVer said:
I mean as I see it, wouldn't the sum of the sliced samples be the "inclusive" one?
Not necessarily. Imagine you want to describe some process in the range of 100 GeV to 4 TeV (pT, pT sum, invariant mass - doesn't matter here). To get a reasonable statistics at 4 TeV with an inclusive sample, you might need billions of events. Most of them are at low energy, where you have more events than you can ever hope to process: simulations of detector response are a significant fraction of the overall CPU hours used for high-energy physics.
Making multiple separate samples, each with appropriate size, reduces the number of events significantly. To get a single spectrum, you have to multiply them with some weight before you can add them.
 
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mfb said:
Not necessarily. Imagine you want to describe some process in the range of 100 GeV to 4 TeV (pT, pT sum, invariant mass - doesn't matter here). To get a reasonable statistics at 4 TeV with an inclusive sample, you might need billions of events

Agree on that, and somehow it helps me understand the inclusive samples. And I agree that at 4TeV you will need some billions of events too.

mfb said:
Most of them are at low energy, where you have more events than you can ever hope to process: simulations of detector response are a significant fraction of the overall CPU hours used for high-energy physics.

aha, nice... so getting the necessary events at high energies you will get several orders of magnitude more events at low ones too, making the generation of events extremely slow.

mfb said:
Making multiple separate samples, each with appropriate size, reduces the number of events significantly. To get a single spectrum, you have to multiply them with some weight before you can add them.

Yes I agree, the weight should take into account the different cross sections...
However if you add them in order to get the overall background you expect at let's say 0.1-4TeV , would you add appart from the sliced samples the inclusive one as well?
 
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ChrisVer said:
Agree on that, and somehow it helps me understand the inclusive samples. And I agree that at 4TeV you will need some billions of events too.
You don't need billions of events at high energy, but you need events everywhere.

To get 1000 around 4 TeV, you might need billions events in total. It is more effective to produce 10000 in the range of 4 TeV, 10000 in the range of 3 TeV and so on.
In terms of luminosity, the highest sample might correspond to something like 20+ times the data luminosity, the other samples can be lower as statistics is not so crucial there any more.

If the inclusive sample is independent, it can get added. It can improve the statistics in the low-energetic range.
 
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mfb said:
If the inclusive sample is independent, it can get added. It can improve the statistics in the low-energetic range.

Wouldn't that however count as a double-counting?
 
  • #6
mfb said:
If the inclusive sample is independent
!
 
  • #7
A sliced sample is a sub sample of the inclusive, so they are not independent.

Combining samples requires a correct merging, where certain events would be vetoed according to a double counting criterion.
 

1) What is an "inclusive sample" and how does it differ from a "sliced sample" in ATLAS?

An inclusive sample in ATLAS refers to a data sample that includes all possible events, regardless of specific selection criteria. This allows for a broad overview of the data and enables the study of rare processes. On the other hand, a sliced sample is a data sample that is divided into smaller subsets based on specific selection criteria, allowing for a more detailed analysis of a particular process or phenomenon.

2) How are the inclusive and sliced samples used in the study of W+jets in ATLAS?

The inclusive sample is used to identify the overall production rate of W bosons in association with jets (W+jets) in the data, while the sliced sample is used to study the kinematic properties of the W+jets events and to compare them to theoretical predictions. Both samples are crucial in understanding the behavior of W+jets and to test the Standard Model of particle physics.

3) What is the significance of the W+jets process in ATLAS?

The W+jets process is an important benchmark process in ATLAS, as it serves as a background for many other processes, such as top-quark production and Higgs boson production. It is also a key process in testing the accuracy of theoretical models and in searching for new physics beyond the Standard Model.

4) How are the inclusive and sliced samples selected in ATLAS?

The inclusive sample is selected using triggers, which are specialized software algorithms that identify events of interest in the data. The sliced sample is selected using a series of cuts, or selection criteria, on the kinematic properties of the events, such as the transverse momentum of the W boson or the number of jets in the event.

5) What are the challenges in analyzing the W+jets process in ATLAS?

One of the main challenges in analyzing the W+jets process is the high rate of background events from other processes, which can obscure the signal of interest. Another challenge is the accurate modeling of the W+jets process, which requires a good understanding of the detector and theoretical uncertainties. Additionally, the large amount of data collected by ATLAS poses challenges in terms of storage and processing.

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