16–17 Jul 2020
Virtual
Europe/Berlin timezone

Despite an impressive and extensive effort by the LHC collaborations, there is currently no convincing evidence for new particles produced in high-energy collisions. At the same time, there has been a growing interest in machine learning techniques to enhance potential signals using all of the available information.

Following the successful conclusion of the LHC Olympics 2020: Winter Games (at the ML4Jets Workshop at NYU in January 2020), we are announcing a two day mini workshop devoted to anomaly detection: LHC Olympics 2020: Summer Games. With this mini-workshop we hope to continue progress on the topic of model independent discovery of new physics at the LHC.

The key goal of this workshop is to discuss progress and new methods for new physics searches at the LHC using unsupervised machine learning. We will also unblind results for the remaining LHC Olympics 2020 black-box datasets. But you are encouraged to give a talk on anomaly detection regardless of your participation level in the LHCO2020.

For more information on the LHC Olympics see the page. Please do not hesitate to ask questions: we will use the ML4Jets slack channel to discuss technical questions related to this challenge. You are also encouraged to sign up for the mailing list lhc-olympics@cern.ch using the e-groups.cern.ch interface for infrequent announcements and communications.


The workshop is a satellite of the (virtual) BOOST conference.

For this informal and virtual workshop, there will be no registration fee. However, please register so we can plan appropriately.

The workshop will take place virtually on Thursday 16.7.2020 and Friday 17.7.2020.

The Zoom link for the workshop is at:
https://uni-hamburg.zoom.us/j/93758369770?pwd=Tzc2M3cxTU42TzV6d2FoMFZKK05Gdz09
(Password: lhco2020!!)

 

Best,
Ben Nachman(benjamin.philip.nachman@cern.ch),
David Shih (shih@physics.rutgers.edu), and
Gregor Kasieczka (gregor.kasieczka@uni-hamburg.de)

Starts
Ends
Europe/Berlin
Virtual