Do Neural Nets Learn Statistical Laws behind Natural Language?

The performance of deep learning in natural language processing has been spectacular, but the reasons for this success remain unclear because of the inherent complexity of deep learning. This paper provides empirical evidence of its effectiveness and of a limitation of neural networks for language engineering. Precisely, we demonstrate that a neural language model based on long short-term memory (LSTM) effectively reproduces Zipf's law and Heaps' law, two representative statistical properties underlying natural language. We discuss the quality of reproducibility and the emergence of Zipf's law and Heaps' law as training progresses. We also point out that the neural language model has a limitation in reproducing long-range correlation, another statistical property of natural language. This understanding could provide a direction for improving the architectures of neural networks.Comment: 21 pages, 11 figure

Tetraquark and Pentaquark Systems in Lattice QCD

Motivated by the recent experimental discoveries of multi-quark candidates, e.g., the $\Theta^+(1540)$, we study multi-quark systems in lattice QCD. First, we perform accurate mass measurements of low-lying 5Q states with $J=1/2$ and I=0 in both positive- and negative-parity channels in anisotropic lattice QCD. The lowest positive-parity 5Q state is found to have a large mass of about 2.24GeV after the chiral extrapolation. To single out the compact 5Q state from $NK$ scattering states, we develop a new method with the hybrid-boundary condition (HBC), and find no evidence of the compact 5Q state below 1.75GeV in the negative-parity channel. Second, we perform the first study of the multi-quark potential in lattice QCD to clarify the inter-quark interaction in multi-quark systems. The 5Q potential $V_{\rm 5Q}$ for the QQ-${\rm \bar{Q}}$-QQ system is found to be well described by the ``OGE Coulomb plus multi-Y Ansatz": the sum of the one-gluon-exchange (OGE) Coulomb term and the multi-Y-type linear term based on the flux-tube picture. The 4Q potential $V_{\rm 4Q}$ for the QQ-${\rm \bar{Q}\bar{Q}}$ system is also described by the OGE Coulomb plus multi-Y Ansatz, when QQ and $\rm \bar Q \bar Q$ are well separated. The 4Q system is described as a "two-meson" state with disconnected flux tubes, when the nearest quark and antiquark pair is spatially close. We observe a lattice-QCD evidence for the ``flip-flop'', i.e., the flux-tube recombination between the connected 4Q state and the ``two-meson'' state. On the confinement mechanism, the lattice QCD results indicate the flux-tube-type linear confinement in multi-quark hadrons.Comment: 22 pages, 3 tables, 16 figures. Talk given at International Workshop on Quark Nuclear Physics 2005 (QNP05), Phoenix Park, Korea, 22-24, Feb., 200

THE STEREOSCOPIC EFFECT OF A SPINNING BATON FLIGHT

INTRODUCTION: In baton twirling, catching a spinning baton is one of fundamental skills. For successful baton-catching, baton twirlers acquire the efficient visual search behavior setting their gaze not only to parabolic flight but spin of baton (Takahashi et al., 2007). Mazyn et al. (2007) reported that the learning to catch a ball is affected by stereo vision providing accurate depth perception of the ball’s movement. We consider a CAVE Automatic Virtual Environment system, 3D virtual reality display with stereoscopic effect, may be used as a training tool for baton-catching. This preliminary study aimed to examine the stereoscopic effect on the virtual reality simulation of baton-catching in a CAVE system. We reconstructed stereo- and monoscopic stimuli of spinning baton flight simulated by 3D motion capture data and assessed observer’s impression of them