6 papers
Machine-Learning Search for Lax Connections
Osamu Fukushima, Tomohiro Shigemura, Ryosuke Suda +2
We apply a machine learning framework to search for Lax connections in two-dimensional non-linear sigma models using local current data. For the principal chiral model and…
Probing Black Hole Thermal Effects in the Dual CFT via Wave Packets
Norihiro Tanahashi, Seiji Terashima, Shiki Yoshikawa
We investigate how the gravitational effects of a black hole manifest themselves as thermal behavior in the dual finite-temperature conformal field theory (CFT). In the holographic…
Wasserstein Space of Quantum Chaos
Koji Hashimoto, Norihiro Tanahashi, Kentaroh Yoshida
We find that the effective dimension of the Wasserstein space of energy eigenstates decreases as a quantum system becomes more chaotic. To demonstrate this, we study a quantum coup…
Holography and Optimal Transport: Emergent Wasserstein Spacetime in Harmonic Oscillator, SYK and Krylov Complexity
Koji Hashimoto, Norihiro Tanahashi
Optimal transport and Wasserstein distance are prominent tools to quantify the space of probability distributions. From a novel viewpoint of manifold hypothesis in machine learning…
Physics-informed neural network solves minimal surfaces in curved spacetime
Koji Hashimoto, Koichi Kyo, Masaki Murata +2
We develop a flexible framework based on physics-informed neural networks (PINNs) for solving boundary value problems involving minimal surfaces in curved spacetimes, with a partic…
Gluon scattering amplitudes with instantons and minimal surfaces with topology change
Koji Hashimoto, Koichi Kyo, Masaki Murata +2
We study the instanton effect on the gluon scattering amplitudes at strong coupling and large for the supersymmetric Yang-Mills theory. According to Alday and Mald…