I Which machine learning model is best for detecting bottom quarks?

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which machine learning model to use to detect bottom quark, and on what basis the segregation should be done
 
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It looks like you've only posted a fragment of the question you want to ask. Can you provide more information on what you are asking?
 
I am working on a project:-
Machine learning for identifying B measons
I have LHC data for processing (data generated through pythia)
I am not able to understand which machine learning model to use
and since I am new to this, I don't know the characteristic of the bottom quark, through which I can separate the bottom quark from other particles
 
There are tons of options. Which one is best will depend on too many details to tell in general.
Dhananjay said:
and since I am new to this, I don't know the characteristic of the bottom quark, through which I can separate the bottom quark from other particles
Which input parameters to use is different from the question which machine learning algorithm to use. It depends on the experiment and the specific study you want to do.

The bottom quark is heavier but shorter-living than charm, which is typically the largest background, so variables will often focus on decay energies in one way or another.
Check previous publications and ask your supervisor or other contact in the experiment you work for.
 

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