Yi Cheng Zhang

Extracting Hidden Information from Knowledge Networks

We develop a method allowing us to reconstruct individual tastes of customers from a sparsely connected network of their opinions on products, services, or each other. Two distinct phase transitions occur as the density of edges in this network is increased: Above the first, macroscopic prediction of tastes becomes possible; while above the second, all unknown opinions can be uniquely reconstructed. We illustrate our ideas using a simple Gaussian model, which we study using both field-theoretical methods and numerical simulations. We point out a potential relevance of our approach to the field of bioinformatics.

Statistical mechanics of competitive resource allocation using agent-based models

Demand outstrips available resources in most situations, which gives rise to competition, interaction and learning. In this article, we review a broad spectrum of multi-agent models of competition (El Farol Bar problem, Minority Game, Kolkata Paise Restaurant problem, Stable marriage problem, Parking space problem and others) and the methods used to understand them analytically. We emphasize the power of concepts and tools from statistical mechanics to understand and explain fully collective phenomena such as phase transitions and long memory, and the mapping between agent heterogeneity and physical disorder. As these methods can be applied to any large-scale model of competitive resource allocation made up of heterogeneous adaptive agent with non-linear interaction, they provide a prospective unifying paradigm for many scientific disciplines. (This abstract was borrowed from another version of this item.)

Dynamical Optimization Theory of a Diversified Portfolio

We propose and study a simple model of dynamical redistribution of capital in a diversified portfolio. We consider a hypothetical situation of a portfolio composed of N uncorrelated stocks. Each stock price follows a multiplicative random walk with identical drift and dispersion. The rules of our model naturally give rise to power law tails in the distribution of capital fractions invested in different stocks. The exponent of this scale free distribution is calculated in both discrete and continuous time formalism. It is demonstrated that the dynamical redistribution strategy results in a larger typical growth rate of the capital than a static “buy-and-hold” strategy. In the large N limit the typical growth rate is shown to asymptotically approach that of the expectation value of the stock price. The finite dimensional variant of the model is shown to describe the partition function of directed polymers in random media.

Modeling forest fire by a paper-burning experiment, a realization of the interface growth mechanism

Abstract We present an experiment on the propagation front of a flameless fire on a thin piece of paper. We find that fire fronts on a piece of paper follow quite well self-affine scaling statistics, with the roughening exponent χ around 0.70, well above the value 1 2 in the theoretical interface growth model using Gaussian noise. This discrepancy may be due to an anomalously singular behavior of the noise distribution, consistent with some recent studies.

Exploring an opinion network for taste prediction: An empirical study

We develop a simple statistical method to find affinity relations in a large opinion network which is represented by a very sparse matrix. These relations allow us to predict missing matrix elements. We test our method on the Eachmovie data of thousands of movies and viewers. We found that significant prediction precision can be achieved and it is rather stable. There is an intrinsic limit to further improve the prediction precision by collecting more data, implying perfect prediction can never obtain via statistical means.

1/F NOISE IN BAK-TANG-WIESENFELD MODELS ON NARROW STRIPES

We report our findings of an 1/f power spectrum for the total amount of sand in directed and undirected Bak-Tang-Wiesenfeld models confined on narrow stripes and driven locally. The underlying mechanism for the 1/f noise in these systems is an exponentially long configuration memory giving rise to a very broad distribution of time scales. Both models are solved analytically with the help of an operator algebra to explicitly show the appearance of the long configuration memory.

Probability Distribution of Drawdowns in Risky Investments

We study the risk criterion for investments based on the drawdown from the maximal value of the capital in the past. Depending on investors risk attitude, thus his risk exposure, we find that the distribution of these drawdowns follows a general power law. In particular, if the risk exposure is Kelly-optimal, the exponent of this power law has the borderline value of 2, i.e. the average drawdown is just about to diverge.

Self-organized critical directed percolation

We introduce and study a dynamic transport model exhibiting Self-Organized Criticality. The novel concepts of our model are the probabilistic propagation of activity and unbiased random repartition of energy among the active site and its nearest neighbors. For space dimensionality d ≥ 2 we argue that the model is related to (d + 1)-dimensional directed percolation, with time interpreted as the preferred direction.

Comment on “Role of intermittency in urban development: A model of large-scale city formation”

A Comment on the Letter by Damian H. Zanette and Susanna C. Manrubia, Phys. Rev. Lett. 79, 523, (1997). The authors of the Letter offer a Reply.