| Co-Investigator(Kenkyū-buntansha) |
須鎗 弘樹 東京理科大学, 理工学部, 助手 (70246685)
明石 重男 新潟大学, 理学部, 助教授 (30202518)
WATANABE N Faculity of Science and Technology, Science University of Tokyo, Lecturer, 理工学部, 講師 (70191781)
LUBEC G University of Vienna, Professor, 医学部, 教授
OJIMA I Research Institute for Mathematical Sciences, Kyoto University, Associate Profes, 数理解析研究所, 助教授 (60150322)
LU Y.G. バリ大学, 数学科, 助教授
HAAG R Univ.Hamburg, a professor emeritus, 理論物理第2研究所, 教授
MRUGALA R Institute of Physics, Nicholas Copernicus University, Associate Professor, 理論物理学科, 助教授
STASZEWSKI S Institute of Physics, Nicholas Copernicus University, Associate Professor, 理論物理学科, 助教授
MILBURN G.J Department of Physics, The University of Queensland, Professor, 物理学科, 教授
VOLOVICH I Steklow Mathematical Institute, Professor of Mathematical Physics, 教授
BELAVKIN V.P Mathematics Department, University of Nottingham, Professor, 数学科, 客員教授
VON WALDENFELS W Institute fur Angewandte Mathematik, Universitat Heidelberg, Professor, 応用数学科, 教授
SALAMON P Department of Mathematical Sciences, San Diego State University, Professor, 数理科学科, 教授
PETZ D Mathematical Institute, Technical University Budapest, Professor, 数学科, 教授
INGARDEN R.S Institute of Physics, Nicholas Copernicus University, Professor, 理論物理学科, 教授
ACCARDI L Department of Mathematics, University of Rome II,Professor, 数学科, 教授
SUYARI H Faculity of Science and Technology, Science University of Tokyo, Assistant
AKASHI S Faculity of Science, Niigata University, Associate Professor
G.LU Y Department of Mathematics, University of Bari, Associate Professor
|
|---|
| Research Abstract |
Information Dynamics was introduced by the head investigator of the joint research program in 1991 as a concept to treat uniformly various fields of mathematical sciences. Information Dynamics contains two concepts, one is complexity and another is dynamics. The dynamics means the state change with respect to time evolution. There are two kind of complexities in Information Dynamics. One is the complexity for syatem itsself and another is the transmitted complexity for innitial system to final sustem through a channel. By using the dynamics and two copmplexities, we studied the following topics : (1) Limits of quantum mutual entropy were discussed through quantum stochstic process. (2) Quantum capacity was formulated for purely quantum channels and its for a mode of potical communication process was computed. (3) Applications of Fractal Dimension of States : Fractal Dimension of States could be applied to analysis of crators on the moon and shapes of rivers in Japan. (4) By using the e
… More
ntropic complexities, quantum dynamical entropy and quantum dynamical mutual entropy were formulated and they were calculated for a model of optical modulations. (5) The quantum dynamical entropy through quantum Makov chain was defined and was computed for several models. (6) Information Genetics : Entropy evolution rate could be applied to analysis of genes and its strucure of coding was investigated. (7) Qunatum Communication Theory (Optical Communication Theory) : Some information efficiencies such as mutual entropy, capacity, error probability and SNR can be rogorously formulated and applied to each communication processes such as attenuation channel, noisy quantum channel and amplifier process. (8) Quantum Computation : Quantum mutual entropy was computed for the optical Fredin-Toffoli-Milburn gate for quantum computer. Moreover, the quantum channel and mutual entropy was derived in quantum teleportation processes. (9) Applications of Complexties to Chaos Theory : The complexty was formulated by means of entropy and mutual entropy and it was applied to the analysis of Logostic mapping. (10) Discussion of quantum field theory : In quantum physic for local systems, BRS symmetry was analyzed and was discussed the characterization theorem of their phenomena for quantum field theory. Less
|
