作者： jinshanw

Jinshan's CV

Jinshan’s Curriculum Vitae

Curriculum Vitae

Jinshan Wu

Department of Systems Science

Beijing Normal University

Tel: +86-10-58807876(O), +86-18610014018(M)

E-mail: Jinshanw@bnu.edu.ca

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  • Education

    • 2011, PH.D. in Condensed Matter Physics, Department of Physics & Astronomy, University of British Columbia (UBC)
    • 2003-2004, one year in a PH.D. program in Simon Fraser University (SFU), and then transferred to UBC
    • 2006, M.Sc. in Condensed Matter Physics, Department of Physics & Astronomy, UBC
    • 2002, M.Sc. in Statistical Physics, Physics Department, Beijing Normal University(BNU)
    • 1999, B.S. in Physics, Department of Physics, BNU

  • Employment

    • 2011-, Associate Professor, Department of Systems Science, BNU, Beijing, China
    • 2004-2011, Teaching Assistant, Department of Physics & Astronomy, UBC
    • 2003-2004, Teaching Assistant, Department of Physics, SFU
    • 2002-2003, Lecturer and Research Associate, Department of Systems Science, BNU

  • Professional experience

    • Associate Professor

      • 2012 Spring, Physics and Mathematics in Studies of Complexity II, graduate course, Department of Systems Science, BNU.
      • 2011 Fall, Physics and Mathematics in Studies of Complexity I, graduate course, Department of Systems Science, BNU.
      • 2011- , Non-equilibrium statistical physics and Quantum transport project, PI, funded partially by National Natural Science Foundation of China.
      • 2011- , Network-based learning strategies of Chinese characters, PI, not yet funded by any agencies.
      • 2012- , Study concept mapping technology and generate collections of concept maps, PI, funded partially by university research fund from BNU.

    • Lecturer

      • 2003, Math Model, undergraduate course, Department of Systems Science, BNU.
      • 2002, Econophysics, a course for graduate students, Department of Systems Science, BNU, 2002,9-2003,1. I designed and established this course from scratch. A review paper ([19] in the publication list) on Econophysics prepared for the class was post on arXiv. Since then many have used it as an introductory material for the subject.

    • Research Associate

      • 2002-2003, under Prof. Zengru Di’s supervision, lead a team working on empirical studies of and modelling weighted complex networks
      • 2002-2003, help Prof. Zengru Di to organize a proposal for National Fund of Natural Science in China, The statistical properties of firm sizes and its theoretical model, funded at 2003,9.

    • Research Assistant

      • 2004-2011, as a graduate student in Prof. Mona Berciu’s group, working on various projects related to quantum transport
      • 1999-2002, as a graduate student (master) in Prof. Zhanru Yang’s group, during the later years of and one year after my graduation (2001-2003), I lead a team working on physical models on complex networks

  • Skills in numerical computation

    • High-performance computational software: BLAS, Lapack, Petsc, Slepc, gsl, xmds
    • Programming language: C, Java, Linux shell script

  • Award

    • University Graduate Fellowship (UGF) from UBC, 2006-2009
    • Graduate Fellowship from SFU, spring 2004
    • Canron Limited – Sidney Hong Memorial Grad Scholarship, Spring 2004
    • Westak International Sales Inc. Grad Scholarship in Expert Systems, Spring 2004
    • Scholarship for Excellent Graduate Students from BNU, 2000
    • Award for excellent undergraduate students from BNU, 1998

  • Research Contribution

    • Quantum Transport

      In my Ph. D. work at UBC I aimed to establish a theoretical framework for finding the non-equilibrium stationary states of quantum systems starting mostly from first principles. Approaches exist for this problem such as the Landauer-Buttiker formula and the non-equilibrium Green’s function method. We decided to use the open-system scenario, which is not widely used because of the difficulty in solving the resulting open-system master equation. Using direct methods, one needs to solve an eigenvalue problem of size 4N where N is the size of the system measured in qubits. We first searched for efficient methods to solve this problem and then applications of this framework on physical models. The following lists several projects I have worked on.

      • Using a BBGKY-like method for solving the open-system master equation [2] the task of solving an eigenvalue problem of size 4N becomes a problem of solving a linear system of size N2 by converting the open-system master equation into linear equations of Green’s functions. The equations of different Green’s functions (single-particle ones, tow-particle ones and so on) are coupled. The cluster expansion, originally used for the equilibrium BBGKY method, is used to truncate the coupled equation. The accuracy of this method is around 2%.
      • The second order form of the BBGKY-like method requires solving a linear system of size N4 but improves accuracy even further. Such a form also gives the two-particle correlated Green’s functions beyond the Hartree-Fock approximation. Manuscript in preparation.
      • A coherent-state representation approach was also explored to solve the above problem of size 4N by simulating a stochastic differential equation with 2N complex variables by converting the open-system master equation into a generalized Fokker-Planck equation. Analytical expression of the non-equilibrium stationary states are derived for some systems. The accuracy of this method is around 6%. Manuscript in preparation.
      • We also found in study of the Kubo formula for open systems [1] that in order to study transport one has to take into account the coupling from the central system to the baths explicitly. In using the usual Kubo formula in transport studies, one assume the central system is a closed system.
      • Using direct methods we studied thermal transport of spin chains[17] and analyzed systems up to N=10. Connections between integrability and anomalous transport, which is widely believed by physicists and has been demonstrated by studies based on the usual Kubo formula, is challenged by our results.

    • Weighted networks

      This series of works started in late 2002 when I was employed as a research associate for Prof. Zengru Di at BNU after I got my M.Sc. Degree in statistical physics from BNU. Many thanks to Prof. Zengru Di, Prof. Yougui Wang and Prof. Zhangang, Han for offering me a position usually requiring a PH.D. Degree. The focus of my research on weighted networks has been the basic statistical features of static weighted networks, their evolution and also some more advanced structure in those networks.

      • Empirical study of weighted networks[11,12]: We collected almost all papers published on Econophysics up to date (back then), compiled a weighted network and studies its basic statistical properties.
      • Evolutionary model for weighted networks [3,7,9]: Inspired by social networks and the above weighted networks of econophysicists, a new model of weighted networks was proposed. It is based on local rules, which means that nodes in the network only need to know limited information about their neighbors and at most their next neighbors. That is in this model a data centers providing global information is not required. We went one step further and conjectured that the well-known mechanism of global preferential attachment (that the richest gets richer while the poorest gets poorer) can be an emergent phenomenon rooted from local rules. We tested and confirmed this conjecture on our own model and several others.

    • Quantum Game Theory[20]

      In physicists’ terminologies, classical games can be regarded as games based on classical objects. The state of the object changes according to players’ choice of strategies. These strategies are described by operators acting on the object to modify its state. The final state of the object determines the payoff for every player. The coin flipping games is a perfect example of this picture. The coin is a classical two-state system, which is denoted by physicists as a mixture state of “heads” and “tails”. Flipping and non-flipping correspond respectively to the Pauli matrixand identity matrix. A natural question then arises of what happens if the classical coin is replaced by a quantum spin.
      I found that the answer is very non-trivial: a probability distribution over the strategy space, which is the description of a general strategy in classical game theory, is no longer capable of describing games with quantum objects. A density matrix over a basis of the strategy space has to be used. The same transition happens from Classical Mechanics to Quantum Mechanics. A probability distribution is replaced by a density matrix, which allows superpositions while the former allows only probability summations.

    • Quantum Foundation[18]

      Partially inspired by the above work on quantum game theory, I was motivated to study the difference between a probability distribution and a density matrix. Can the former be converted to the later equivalently or vice versa? Luckily I found that the same question has been asked and investigated by physicists on the question of validity of hidden variable theory. In a hidden variable theory, there is no superposition principle, but classical probability summations are allowed. In a sense, the hidden variable theory is searching for a map from a density matrix to a classical probability distribution.

      On one hand there is a theorem stating that all convex theories, which includes quantum mechanics, can be embedded into a classical probability theory with constraints (see for example, A. S. Holevo, Probabilistic and Statistical Aspects of Quantum Theory). On the other hand, Bell’s inequality rules out all local hidden variable theories. The constrained classical theory has to be non-local. Of course many believe that physical theory should be local, but some are still willing to sacrifice locality. I investigated the question of what beyond locality one has to give up in order to have such a classical theory for quantum systems. I found there are many other unacceptable features of the classical theory by explicitly constructing such a theory for systems of one spin half and two spin halfs. Those unwanted features make the theory even harder to understand than the usual quantum mechanics.

  • List of publications

    • 想招两个一年级本科生指导一下

    从物理系和系统科学系找两个新生，最好一边一个，加入我的研究小组。计划用两年时间学习核心课程，两年时间做一些研究工作。在完成普通学生的课程基础上，我会对数学、物理学、计算机、英语课程提出额外的要求，并提供指导。你会花很多其他人玩乐的时间来学习和开展研究工作。这一点你要有心理准备。

    要求：

    1. 对学术研究有浓厚的兴趣
    2. 有毅力，不畏难
    3. 数学、物理学、英语不是很差

    目标：

    1. 完成数学、物理学、计算机科学本科以及硕士研究生阶段的核心课程的学习
    2. 基本的科研训练：学术品味、寻找问题、完成计算、报告学术成果、论文写作
    3. 多学科的兴趣

    待遇：

    1. 考察期间过后，给一定津贴
    2. 完成研究工作的话，按照本组硕士研究生的标准给予奖励

    我的所得：

    1. 更多的学生来完成我的工作。不过这个不重要，其他研究生也可以完成
    2. 试一试在我自己身上管用的学习方法和内容有没有一定的推广价值
    3. 寻找和培养超越我自己的学生，这一点最重要

    关于培养方向的部分细节内容可以参考：工具、课程与学习资料
    关于吴金闪的更多细节可见吴金闪的简历
    关于吴金闪团队的工作的更详细的介绍可见研究计划与进展

    工具、课程与学习资料

    这些是我整理的为一般性的研究工作做准备的一些资料和工具。大部分都可以从网上下载（docin, doc88, iask文库之类的地方，当然还有Google）。

    • General discussion of Scientific Investigation and Scientific Thinking: The Art of Scientific Investigation by W.I.B. Beveridge, Learning, Creating and Using Knowledge by J.D. Novak.
    • LaTeX (typesetting): The Not So Short Introduction to LATEX2ε, a sample file or a journal specific template, google latex symbols when needed.
    • gnuplot (figures): gnuplot in action, gnuplot manual, gnuplot not so frequently asked questions.
    • jaxodraw (Feynman diagram): jaxodraw official website.
    • Linux shell (A series of Linux commands in a file to save time): Linux Shell Scripting Tutorial v1.05r3 A Beginner’s handbook (http://www.freeos.com/guides/lsst/index.html) .
    • C:
      1. Find a good textbook and a good tutorial on C programming: Programming in C By Stephen G. Kochan, C by Examples by Greg M. Perry, C in 21 days by Aitken and Jones, The C Programming Language by K&R, http://en.wikibooks.org/wiki/C_Programming, http://www.cprogramming.com/tutorial/c-tutorial.html .
      2. First find a compiler (gcc), compile from the command line.
      3. Learn how to compile and run a basic program (makefile), such as printing “Hello World” to the screen and exit.
      4. Learn about variable types, such as the difference between char, int, float, double, etc.
      5. Learn about the concept of variables, arrays and functions.
      6. Learn pointers, dynamic memory allocation.
      7. Learn conditional statements and loops, such as the “if”, “switch” and “for” statements. Also learn the continue and break statements.
      8. Learn some basic standard library functions, but not too much.
      9. Start with small programs, however meanwhile constantly think about one much bigger problem on your mind, say the task you want to accomplish in the beginning when you notice that you need C and start to work on that problem (via for example, first decomposing the big problem into many small ones) as soon as possible.
      10. Learn key steps about debugging (gdb).
      11. Learn a little bit about programming style: Notes on Coding Style for C Programming, Writing Bug-Free C Code.
      12. Learn data structures and a little bit on algorithms, linked list, graph, tree.
      13. Learn a little bit of code profiling (code optimization): gprof, http://www.ibm.com/developerworks/library/l-gnuprof.html .
    • Python: 转闫小勇（@yanxy）整理的资料：Python精要参考（第二版）——iask上有，100多页，保证几天学会Python基本编程：）Networkx入门笔记——我博客上有: here
      Numpy 1.5 Beginner’s guide——iask上有，200多页，看前三章一般就够了，推荐！
      用python做科学计算——在线版：http://hyry.dip.jp:8000/pydoc/index.html，可以看看里边的numpy和matplotlib部分，其他不看也罢。
      个人建议：学编程，关键是动手写。看书看不会，越写越熟练！
    • R: http://www.ling.upenn.edu/~joseff/rstudy/index.html，Introductory Statistics with R by Peter Dalgaard，The Art of R Programming: A Tour of Statistical Software Design by Norman Matloff， The R Book by Michael J. Crawley。
    • sage: http://www.sagemath.org/doc/tutorial/index.html，SAGE For Newbies by Ted Kosan，Sage Beginner’s Guide by Craig Finch。
    • Network Analysis and related packages: An Introduction to Networks by Newman, Our own review paper and several papers from others (see documents from the complexity group on this website), NetworkX, Pajek, UCINET, SNAP: Stanford Network Analysis Platform, igraph, Network Workbench.
    • Monte Carlo and Monte Carlo in statistical physics:
    • Linear Algebra System (BLAS, Lapack, Petsc, Slepc): official websites, examples and manual
    • General algorithms (numerical diffrentiation, integration, the Runge-Kutta method, root finding etc): gsl and gsl manual, Introduction to Algorithms, by Thomas H. Cormen, Charles E. Leiserson, Ronald L. Rivest and Clifford Stein, The Algorithm Design Manual by Steven S. Skiena。
    • Parallel programming (MPI, just some general priciples): “Parallel Programming in C with MPI and OpenMP” by Quinn, Petsc, Slepc manual and examples
    • Physics, Math and Economics:
      1. Classical Mechanics: Feynman’s Lecture on Classical Mechanics，力学概论by方励之，Mechanics by Landau；Calculus required.
      2. Quantum Mechanics: Feynman’s Lecture on Quantum Mechanics, Principles of quantum mechanics by R. Shankar, Modern Quantum Mechanics by J.J. Sakurai，高等量子力学by喀兴林，Quantum Mechanics by L. Ballentine；Classical Mechanics, Linear Algebra, Probability Theory required。
      3. Statistical Physics: 量子统计物理学by杨展如，Statistical Mechanics by D.A. Mcquarrie, Statistical Physics by Leo P. Kadanoff, A Modern Course in Statistical Physics by L. E. Reichl, Equilibrium Statistical Physics by Michael Plischke and Birger Bergersen, Introduction to Modern Statistical Mechanics by David Chandler；Classical Mechanics, Quantum Mechanics, Probability Theory, Stochastic Process required.
      4. Quantum Field Theory: Quantum Field Theory: From Operators to Path Integrals by Kerson Huang，Many-Particle Physics by Gerald D. Mahan，An Introduction to Quantum Field Theory by Peskin & Schroeder； Classical Mechanics, Quantum Mechanics, Statistical Mechanics required, Group Theory, Functional Analysis can be helpful。
      5. Non-linear Dynamics: Invitation to dynamical systems by Edward R. Scheinerman, Chaos: Making a New Science by James Clark(译作《混沌学传奇》或者《混沌：开创新科学》) 。
      6. Linear Algebra: 线性代数by居余马，线性代数与矩阵论by许以超，Algebra by M. Artin
      7. Calculus: Calculus Early Transcendentals by James Stewart，简明微积分 by 龚升，Principles of Mathematical Analysis by Rudin
      8. Probability Theory: 概率论导引 by A·H·柯尔莫戈洛夫，概率论引论by汪仁官，概率论by何书元，A course in Probability Theory by Kai Lai Chung
      9. Statistics: Statistics by D. Freedman, 有中文版
      10. Fokker-Planck equation, Master equation etc. in Stochastic Process: Fokker-Planck Equation by H. Risken
      11. Game Theory: Games of Strategy by Dixit etal, 演化博弈论 by 威布尔
      12. Microeconomics:
      13. Mathematical Modelling (the idea of searching and presenting phenomena by their natural math structures): A first course in mathematical modeling by Frank R. Giordano
      14. Group Theory (to have a better understanding of math, also helpful in understanding Quantum Mechanics, Quantum Field Theory): 熊全淹的《近世代数》， Representations of Compact Lie Groups by T. Bröcker and T.tom Dieck
      15. Functional Analysis (essential for understanding properly Quantum Mechanics and Quantum Field Theory):
      16. Differential Geometry (to have a better understanding of math, also important in learning General Relativity): 微分几何与广义相对论入门by梁灿斌，尤其是各种附录要仔细看，非常有价值

    Xelatex图的caption中汉字显示的问题

    不是所有的字体都能够用在caption中的。解决方法：在正文和插图中用不同的字体。例如：

    \usepackage{xeCJK}
    \usepackage{fontspec}
    \setCJKfamilyfont{main}{AR PL UMing CN}
    \newfontfamily\ChineseInCaption{WenQuanYi Micro Hei}

    \begin{document}

    \CJKfamily{main}
    正文
    \begin{figure…..}
    \includegraphics{fig1.eps}
    \caption{插图 \ChineseInCaption 汉字拆分及网络构建示意图。}
    \end{figure…..}

    向每一位研究生推荐The Art of Scientific Investigation

    昨天收到大辉推荐的一本书：The Art of Scientific Investigation（被翻译成科学之路或者科学的艺术），看了两章，强力推荐。可以从docin下载到:http://www.docin.com/p-602753.html; http://www.docin.com/p-288814187.html; http://www.docin.com/p-79237417.html。

    另外，发现了一个学术道德问题，1983年出版的翻译版《科学之路》实际上抄袭了1978年出版的《科学的艺术》。除了改了政治色彩浓厚的几句话，几个标点符号（而且我认为大部分标点符号还改错了），基本上就是原文照抄。独立翻译能够做到90%以上相同，是不可思议的事情。让我们记住1978版的译者——陈捷。

    另一方面，我非常推荐原版，写的非常容易看懂，谢谢W.I.B.Beveridge。