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SIMIS-APCTP meeting: AI methods in Theoretical Physics
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Asia/Shanghai
18F Conference Hall (SIMIS)
18F Conference Hall
SIMIS
Shanghai Institute for Mathematics
and Interdisciplinary Sciences
Block A, International Innovation Plaza
No. 657 Songhu Road, Yangpu District
Shanghai, China
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Description
Artificial intelligence (AI), machine learning (ML), and deep learning (DL) provide a broad range of powerful tools that can be used to tackle a wide variety of problems in theoretical high-energy physics. The two-day (mini) SIMIS-APCTP workshop on “AI Methods in Theoretical Physics” will bring together theoretical physics researchers whose current work focuses on the application and development of AI methods in high-energy theoretical physics. Indicative topics include the identification and classification of geometric structures in string theory (such as Calabi–Yau manifolds and quantum geometries), the reconstruction of holographic spacetimes from boundary data, the study of strongly coupled quantum field theories, the exploration of fundamental structures and observables in quantum and conformal field theories (such as scattering amplitudes), as well as the solution of key equations in theoretical physics (such as the Bethe and Yang–Baxter equations).
Invited speakers
Robert de Mello Koch (Huzhou U.)
Xin Gao (Sichuan U.)
Koji Hashimoto (Kyoto U.)
Song He (Ningbo U.)
Yuji Hirono (Tsukuba U.)
Keun-Young Kim (GIST)
Nakwoo Kim (Kyung Hee U.)
Seong-Jin Lee (IBS-CGP)
Yuanche Liu (USTC Hefei)
Rak-Kyeong Seong (UNIST)
Benjamin Suzzoni (UNIST)
Norihiro Tanahashi (Kyoto U.)
Jiahua Tian (East China Normal U.)
Ashutosh Tripathi (APCTP)
Juntao Wang (BIMSA)
Yuan Xin (SIMIS)
Yang Zhang (USTC Hefei)
Organizers
George Linardopoulos (SIMIS)
Zhesen Yang (APCTP)
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Participants