54 citations · 85 across the 5 of their papers we have counts for
5 papers
Machine Learning Estimation on the Trace of Inverse Dirac Operator using the Gradient Boosting Decision Tree Regression
Benjamin J. Choi, Hiroshi Ohno, Takayuki Sumimoto +1
We present our preliminary results on the machine learning estimation of from other observables with the gradient boosting decision tree regression, where …
Deriving dilaton potential in improved holographic QCD from chiral condensate
Koji Hashimoto, Keisuke Ohashi, Takayuki Sumimoto
We derive an explicit form of the dilaton potential in improved holographic QCD (IHQCD) from the QCD lattice data of the chiral condensate as a function of the quark mass. This est…
Deriving dilaton potential in improved holographic QCD from meson spectrum
Koji Hashimoto, Keisuke Ohashi, Takayuki Sumimoto
We derive an explicit form of the dilaton potential in improved holographic QCD (IHQCD) from the experimental data of the meson spectrum. For this purpose we make use of the em…
Deep Learning and AdS/QCD
Tetsuya Akutagawa, Koji Hashimoto, Takayuki Sumimoto
We propose a deep learning method to build an AdS/QCD model from the data of hadron spectra. A major problem of generic AdS/QCD models is that a large ambiguity is allowed for the…
correction in holographic Wilson loop from quantum gravity
Koji Hashimoto, Wataru Sasaki, Takayuki Sumimoto
We study corrections to a Wilson loop in holographic duality. Extending the AdS/CFT correspondence beyond the large limit is an important but a subtle issue, as it needs…