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DTSTART:20231105T020000
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DTSTART:20230312T020000
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BEGIN:VEVENT
UID:calendar.813.field_slac_event_date.0@theory.slac.stanford.edu
DTSTAMP:20230603T214950Z
CREATED:20230204T221805Z
DESCRIPTION:Distribution is a ubiquitous data type in high energy physics (
HEP)\, numerous other sciences\, and our daily life. When the space of dis
tributions is equipped with a suitable metric\, previously ad-hoc notions
of similarity can now be formulated in a precise way\, opening up many new
applications with profound theoretical implications. Optimal Transport (O
T) is the mathematical theory that provides such well-defined distances be
tween distributions. In this talk\, I will introduce the theory of optimal
transport and explain how to linearize two special OT distances. I will t
hen discuss recent applications of OT in collider physics and dark matter
astrophysics to showcase the power of this novel geometric framework. As t
he adoption of optimal transport in HEP is still in its infancy\, my talk
invites everyone to think of other potential use cases in their own resear
ch.
DTSTART;TZID=America/Los_Angeles:20230407T123000
DTEND;TZID=America/Los_Angeles:20230407T143000
LAST-MODIFIED:20230403T184247Z
SUMMARY:Tianji Cai - UC Santa Barbara -“Do you need a distance?” Optimal Tr
ansport for High Energy Physics
URL;TYPE=URI:https://theory.slac.stanford.edu/events/tianji-cai-uc-santa-ba
rbara-%E2%80%9Cdo-you-need-distance%E2%80%9D-optimal-transport-for-high-en
ergy-physics
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