Adaptive Learning Method of Recurrent Temporal Deep Belief Network to Analyze Time Series Data

Deep Learning has the hierarchical network architecture to represent the complicated features of input patterns. Such architecture is well known to represent higher learning capability compared with some conventional models if the best set of parameters in the optimal network structure is found. We have been developing the adaptive learning method that can discover the optimal network structure in Deep Belief Network (DBN). The learning method can construct the network structure with the optimal number of hidden neurons in each Restricted Boltzmann Machine and with the optimal number of layers in the DBN during learning phase. The network structure of the learning method can be self-organized according to given input patterns of big data set. In this paper, we embed the adaptive learning method into the recurrent temporal RBM and the self-generated layer into DBN. In order to verify the effectiveness of our proposed method, the experimental results are higher classification capability than the conventional methods in this paper.Comment: 8 pages, 9 figures. arXiv admin note: text overlap with arXiv:1807.03487, arXiv:1807.0348

Magnetogenesis from a rotating scalar: \`a la scalar chiral magnetic effect

The chiral magnetic effect (CME) is a phenomenon in which an electric current is induced parallel to an external magnetic field in the presence of chiral asymmetry in a fermionic system. In this paper, we show that the electric current induced by the dynamics of a pseudo-scalar field which anomalously couples to electromagnetic fields can be interpreted as closely analogous to the CME. In particular, the velocity of the pseudo-scalar field, which is the phase of a complex scalar, indicates that the system carries a global U(1) number asymmetry as the source of the induced current. We demonstrate that an initial kick to the phase-field velocity and an anomalous coupling between the phase-field and gauge fields are naturally provided, in a set-up such as the Affleck-Dine mechanism. The resulting asymmetry carried by the Affleck-Dine field can give rise to instability in the (electro)magnetic field. Cosmological consequences of this mechanism are also investigated.Comment: 35 pages, 1 figure; v2: extended discussions, comments and references added, matches version accepted for publication in JHE