Skip to content
Monte Carlo For Physicists episode artwork

EPISODE · Mar 12, 2015 · 8 MIN

Monte Carlo For Physicists

from Linear Digressions · host Katie Malone

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.

Episode metadata supplied by the publisher feed · Published Mar 12, 2015

Embed this episode

Ready to play

Monte Carlo For Physicists

0:00 8:13

No transcript for this episode yet

We transcribe on demand. Request one and we'll notify you when it's ready — usually under 10 minutes.

No similar episodes found.

Frequently Asked Questions

How long is this episode of Linear Digressions?

This episode is 8 minutes long.

When was this Linear Digressions episode published?

This episode was published on March 12, 2015.

Can I download this Linear Digressions episode?

Yes. Use the download control on the episode player to save the publisher-provided media file.
URL copied to clipboard!