1. EachPod

Monte Carlo For Physicists

Author
[email protected] (Ben Jaffe and Katie Malone)
Published
Thu 12 Mar 2015
Episode Link
https://soundcloud.com/linear-digressions/monte-carlo-for-physicists

This is another physics-centered podcast, about an ML-backed particle identification tool that we use to figure out what kind of particle caused a particular blob in the detector. But in this case, as in many cases, it looks hard at the outset to use ML because we don't have labeled training data. Monte Carlo to the rescue!

Monte Carlo (MC) is fake data that we generate for ourselves, usually following certain sets of rules (often a Markov chain; in physics we generate MC according to the laws of physics as we understand them) and since you generated the event, you "know" what the correct label is.

Of course, it's a lot of work to validate your MC, but the payoff is that then you can use Machine Learning where you never could before.

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