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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CERN

Posted 6 months ago

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

Order by:

Posted by yhaddad • 6 months ago

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

p_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)

), 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

Posted by stubbi • 6 months ago

Hi @marcinj8,

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

Best, Jannes

Posted by stubbi • 6 months ago

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

Posted by jag • 6 months ago

I'm interested to know too. :)

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