#author("2023-06-12T18:00:13+09:00","default:wikiadm","wikiadm") *2023年 [#j9910e85] ***[[Seminar]] [#hccb4bec] 日時: July 4 (Tue) 14:00 - 15:00 場所: Workshop room at CCS/Zoom 講演者: Daiki Ueda (KEK) タイトル: TBD 概要: -[http://www-het.ph.tsukuba.ac.jp/Seminar/tsukuba-only/2023/seminar20230704_Ueda.pdf 2023/07/04:slides(pdf)] 日時: June 20 (Tue) 13:30 - 14:30 場所: Workshop room at CCS/Zoom 講演者: Shinichiro Akiyama (University of Tsukuba) タイトル: Bond-weighting method for the Grassmann tensor renormalization group 概要: The bond-weighted tensor renormalization group (BTRG) is a novel tensor network algorithm to evaluate the partition functions of two-dimensional classical spin systems. We extend the BTRG to make it applicable to the fermionic system, benchmarking with the two-dimensional massless Wilson fermion. We show that the accuracy with the fixed bond dimension is improved also in the fermionic system and provide numerical evidence that the optimal choice of the hyperparameter is not affected by whether the system is bosonic or fermionic. In addition, we find that the scale-invariant structure of the renormalized Grassmann tensor is successfully kept by the bond-weighting technique by monitoring the singular value spectrum. -[http://www-het.ph.tsukuba.ac.jp/Seminar/tsukuba-only/2023/seminar20230620_Akiyama.pdf 2023/06/20:slides(pdf)] 日時: June 7 (Wed) 16:30-17:30 場所: Workshop room at CCS/Zoom 講演者: Takayuki Sumimoto (University of Tsukuba) タイトル: Data-driven construction of holographic QCD model 概要: We propose a novel construction method for holographic QCD models and validate its effectiveness using ρ meson spectrum data. Holographic QCD models are effective models of hadron physics that are constructed based on insights from gauge-gravity duality. The construction of these models can be approached from two directions: top-down, based on reduction from string theory, and bottom-up, based on insights from gauge-gravity duality. However, both methods have their problems. In the top-down approach, it is generally difficult to reduce to hadron physics as a low-energy effective model of QCD. The bottom-up approach, although based on the properties of QCD, requires the assumption of a simple model. In contrast, we propose a data-driven approach. In this method, we construct complex holographic models from physical quantities through spacetime emerging via deep learning based on AdS/DL and the derivation of the corresponding gravitational action. In particular, we construct the model using ρ meson spectrum data. This study opens up new possibilities for the construction and application of holographic QCD models, and could potentially provide a new way to bridge the gap between string theory and experimental facts. -[http://www-het.ph.tsukuba.ac.jp/Seminar/tsukuba-only/2023/seminar20230607_Sumimoto.pdf 2023/06/7:slides(pdf)]