● 会议名称（中文）： 统计物理与计算机科学研讨会（STATPHYS-24北京卫星会议）

● 会议名称（英文）： Statistical Physics and Computer Science(Beijing Satellite Meeting of STATPHYS-24)

● 所属学科： 物理学　 计算机科学技术　 
 
● 会议类型： 国内会议 

● 会议论文集是否检索： 不详 

● 开始日期： 2010-7-8

● 结束日期： 2010-7-11

● 所在国家： 中华人民共和国 

● 所在城市： 北京市   东城区 

● 主办单位： Institute of Theoretical Physics, Chinese Academy of Sciences

● 会务组联系方式

E-mail： manage@kitpc.ac.cn
通讯地址： 北京市海淀区中关村东路55号
邮政编码： 100190

● 会议网站： http://kitpc.itp.ac.cn/scw.jsp?id=CS20100708

● 会议背景介绍：    

Recent research efforts demonstrate that very interesting collective behaviors and phase transition phenomena exist in various distributed information systems, such as large constraint satisfaction formulas, low-density-parity-check codes, networks of neurons, peer-to-peer computer networks, and combinatorial optimization problems. The application of statistical physics methods to these system has lead to great progress in understanding the typical computation complexity of random constraint satisfaction/optimization problems, the solution space evolution and phase transitions of random combinatorial satisfaction problems, the performances of low-density-parity-check codes, ...... The interaction of statistical physics and computer/information science has also resulted in the invention of new efficient message-passing algorithms. The developed methods and ideas will also be very valuable for studying the equilibrium and out-of-equilibrium properties of disordered and frustrated systems. 

● 征文范围及要求：    

These pioneer research practices of computer scientists, mathematicians, and physicists have created a new interdisciplinary field that is growing fast. Being a satellite meeting for STATPHYS-24, the 2010 Beijing workshop will be a platform for communicating latest research results, for presenting challenging problems, and for open-minded discusses of new research directions. The topics of this workshop will include (but not limited to) the following:
Phase transitions in combinatorial satisfaction/optimization problems
Reconstruction of neural and gene-regulation networks from correlation measurements
Message-passing algorithms
Glassy dynamics of search processes