Multidimensional Regression on LHC collision jets background cover

Multidimensional Regression on LHC collision jets

Model the behavior of particle jets from LHC collisions using advanced Quantum Algorithms to bridge theoretical predictions with observed data.

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Marcin
marcinj8

3

Posted

Score clarification

Hi, Just making sure - is the score which shows up on the leaderboard better when lower? So a score of 0 would be the best possible score?
Apologies for asking such a trivial question but I couldn't attend the AMA sessions!
Thanks, Marcin
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Yacine Haddad

3

Posted by yhaddad •

Hi Marcin,
Yes, you’re absolutely right. Lower scores are better. The leaderboard score is based on the Kullback-Leibler (KL) divergence, which measures the difference between your predicted distributions (In our scase the Jet Multiplicity Distribution and Leading & Subleading Jet pTp_T) and the ground truth. A perfect score of 0 would mean your predictions exactly match the true distributions (i.e P(i)=Q(i)P(i) = Q(i)), though that is very hard to achieve in practice, so it's very unlikely.
No worries at all about the question, happy to clarify, and thanks for checking in.
Cheers, Yacine
Jannes Stubbemann

1

Posted by stubbi •

Thanks for bringing this up! I think the overview is wrong in this case. Higher score is better.
Best, Jannes
Jannes Stubbemann

1

Posted by stubbi •

@marcinj8 actually my statement might be wrong. Waiting for official statement by @cern
Jagatheesan Kunasaikaran

2

Posted by jag •

I'm interested to know too. :)

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