QCD at the Femtoscale in the Era of Big Data
Event ID: INT-24-2a
Note: This is an in-person program. There will be an embedded workshop during the first week (June 10-14).
Disclaimer: Please be aware that, due to ongoing concerns regarding the COVID-19 pandemic, this program may be changed from in-person to hybrid, or to online-only if necessary.
Modern facilities around the world have been built to study the quark and gluon structure of matter, such as Jefferson Lab, RHIC, and the forthcoming EIC, which will produce many exabytes of data on the visible universe at the femtometer scale. This new era of big data in nuclear physics holds the promise of solving many of the mysteries in QCD, such as the origin of the nucleon’s mass and spin. However, analyzing this data to extract the required information is an extremely challenging task, since quarks and gluons are not directly accessible in experiment because of confinement in QCD.
To solve this challenge at scale requires nuclear physics to develop and adopt methods in data science, AI/ML, applied mathematics, and large scale computing from other fields and mold them to the needs faced in nuclear physics. Such a multi-disciplinary approach, that allows for cross field collaboration and exchange of ideas, is still in it infancy in the field of QCD phenomenology.
This multi-disciplinary 4 week program brings together QCD domain scientists with experts in computational science, data science, AI/ML, and applied mathematics to begin developing the ideas, methods, and tools to address these key challenges for nuclear physics in the era of big data.
A key goal for this program is to have a significant impact on the synergy between theory and experiment in nuclear physics, and drive collaboration with other fields, that over time could have a transformational impact on nuclear physics. A key outcome of this program will be a brief white paper that reports of the key ideas and next steps that are developed and explored in this program on QCD at the femtoscale in the era of big data.
There will be a $75 registration fee to attend the embedded workshop week (June 10-14). The registration fee includes participation in the workshop, lectures, and coffee breaks. Details on how to pay the registration fee will be sent via email to all workshop attendees.