arXiv subjects

Chaoming Song

Publications and source records attributed to Chaoming Song.

At least 55 records · Page 3Linked to original sources

arXiv2012

Global Epigenetic State Network Governs Cellular Pluripotent Reprogramming and Transdifferentiation

How do mammalian cells that share the same genome exist in notably distinct phenotypes, exhibiting differences in morphology, gene expression patterns, and epigenetic chromatin statuses? Furthermore how do cells of different phenotypes differentiate reproducibly from a single fertilized egg? These fundamental questions are closely related to a deeply rooted paradigm in developmental biology that cell differentiation is irreversible. Yet, recently a growing body of research suggests the possibility of cell reprogramming, which offers the potential for us to convert one type of cell into another. Despite the significance of quantitative understandings of cell reprogramming, theoretical efforts often suffer from the complexity of large circuits maintaining cell phenotypes coupled at many different epigenetic and gene regulation levels. To capture the global architecture of cell phenotypes, we propose an "epigenetic state network" approach that translates the classical concept of an epigenetic landscape into a simple-yet-predictive mathematical model. As a testing case, we apply the approach to the reprogramming of fibroblasts (FB) to cardiomyocytes (CM). The epigenetic state network for this case predicts three major pathways of reprogramming. One pathway goes by way of induced pluripotent stem cells (iPSC) and continues on to the normal pathway of cardiomyocyte differentiation. The other two pathways involve transdifferentiation (TD) either indirectly through cardiac progenitor (CP) cells or directly from fibroblast to cardiomyocyte. Numerous experimental observations support the predicted states and pathways.

q-bio.MN↗

arXiv2011

Edwards thermodynamics of the jamming transition for frictionless packings: ergodicity test and role of angoricity and compactivity

This paper illustrates how the tools of equilibrium statistical mechanics can help to explain a far-from-equilibrium problem: the jamming transition in frictionless granular materials. Edwards ideas consist of proposing a statistical ensemble of volume and stress fluctuations through the thermodynamic notion of entropy, compactivity, X, and angoricity, A (two temperature-like variables). We find that Edwards thermodynamics is able to describe the jamming transition (J-point). Using the ensemble formalism we elucidate the following: (i)We test the combined volume-stress ensemble by comparing the statistical properties of jammed configurations obtained by dynamics with those averaged over the ensemble of minima in the potential energy landscape as a test of ergodicity. Agreement between both methods supports the idea of "thermalization" at a given angoricity and compactivity. (ii) A microcanonical ensemble analysis supports the idea of maximum entropy principle for grains. (iii) The intensive variables describe the approach to jamming through a series of scaling relations as A {\to} 0+ and X {\to} 0-. Due to the force-volume coupling, the jamming transition can be probed thermodynamically by a "jamming temperature" TJ comprised of contributions from A and X. (iv) The thermodynamic framework reveals the order of the jamming phase transition by showing the absence of critical fluctuations at jamming in observables like pressure and volume. (v) Finally, we elaborate on a comparison with relevant studies showing a breakdown of equiprobability of microstates.

cond-mat.soft↗

arXiv2010

Application of Edwards' statistical mechanics to high dimensional jammed sphere packings

The isostatic jamming limit of frictionless spherical particles from Edwards' statistical mechanics [Song \emph{et al.}, Nature (London) {\bf 453}, 629 (2008)] is generalized to arbitrary dimension $d$ using a liquid-state description. The asymptotic high-dimensional behavior of the self-consistent relation is obtained by saddle-point evaluation and checked numerically. The resulting random close packing density scaling $ϕ\sim d\,2^{-d}$ is consistent with that of other approaches, such as replica theory and density functional theory. The validity of various structural approximations is assessed by comparing with three- to six-dimensional isostatic packings obtained from simulations. These numerical results support a growing accuracy of the theoretical approach with dimension. The approach could thus serve as a starting point to obtain a geometrical understanding of the higher-order correlations present in jammed packings.

cond-mat.stat-mech↗

arXiv2010

Jamming I: A volume function for jammed matter

We introduce a "Hamiltonian"-like function, called the volume function, indispensable to describe the ensemble of jammed matter such as granular materials and emulsions from a geometrical point of view. The volume function represents the available volume of each particle in the jammed systems. At the microscopic level, we show that the volume function is the Voronoi volume associated to each particle and in turn we provide an analytical formula for the Voronoi volume in terms of the contact network, valid for any dimension. We then develop a statistical theory for the probability distribution of the volumes in 3d to calculate an average volume function coarse-grained at a mesoscopic level. The salient result is the discovery of a mesoscopic volume function inversely proportional to the coordination number. Our analysis is the first step toward the calculation of macroscopic observables and equations of state using the statistical mechanics of jammed matter, when supplemented by the condition of mechanical equilibrium of jamming that properly defines jammed matter at the ensemble level.

cond-mat.soft↗

arXiv2010

Jamming in two-dimensional packings

We investigate the existence of random close and random loose packing limits in two-dimensional packings of monodisperse hard disks. A statistical mechanics approach-- based on several approximations to predict the probability distribution of volumes-- suggests the existence of the limiting densities of the jammed packings according to their coordination number and compactivity. This result has implications for the understanding of disordered states in the disk packing problem as well as the existence of a putative glass transition in two dimensional systems.

cond-mat.soft↗

arXiv2010

Jamming II: Edwards' statistical mechanics of random packings of hard spheres

The problem of finding the most efficient way to pack spheres has an illustrious history, dating back to the crystalline arrays conjectured by Kepler and the random geometries explored by Bernal in the 60's. This problem finds applications spanning from the mathematician's pencil, the processing of granular materials, the jamming and glass transitions, all the way to fruit packing in every grocery. There are presently numerous experiments showing that the loosest way to pack spheres gives a density of ~55% (RLP) while filling all the loose voids results in a maximum density of ~63-64% (RCP). While those values seem robustly true, to this date there is no physical explanation or theoretical prediction for them. Here we show that random packings of monodisperse hard spheres in 3d can pack between the densities 4/(4 + 2 \sqrt 3) or 53.6% and 6/(6 + 2 \sqrt 3) or 63.4%, defining RLP and RCP, respectively. The reason for these limits arises from a statistical picture of jammed states in which the RCP can be interpreted as the ground state of the ensemble of jammed matter with zero compactivity, while the RLP arises in the infinite compactivity limit. We combine an extended statistical mechanics approach 'a la Edwards' (where the role traditionally played by the energy and temperature in thermal systems is substituted by the volume and compactivity) with a constraint on mechanical stability imposed by the isostatic condition. Ultimately, our results lead to a phase diagram that provides a unifying view of the disordered hard sphere packing problem.

cond-mat.soft↗

arXiv2010

Distribution of volumes and coordination number in jammed matter: mesoscopic ensemble

We investigate the distribution of the volume and coordination number associated to each particle in a jammed packing of monodisperse hard sphere using the mesoscopic ensemble developed in Nature 453, 606 (2008). Theory predicts an exponential distribution of the orientational volumes for random close packings and random loose packings. A comparison with computer generated packings reveals deviations from the theoretical prediction in the volume distribution, which can be better modeled by a compressed exponential function. On the other hand, the average of the volumes is well reproduced by the theory leading to good predictions of the limiting densities of RCP and RLP. We discuss a more exact theory to capture the volume distribution in its entire range. The available data suggests a plausible order/disorder transition defining random close packings. Finally, we consider an extended ensemble to calculate the coordination number distribution which is shown to be of an exponential and inverse exponential form for coordinations larger and smaller than the average, respectively, in reasonable agreement with the simulated data.

cond-mat.soft↗

arXiv2010

Modeling the scaling properties of human mobility

While the fat tailed jump size and the waiting time distributions characterizing individual human trajectories strongly suggest the relevance of the continuous time random walk (CTRW) models of human mobility, no one seriously believes that human traces are truly random. Given the importance of human mobility, from epidemic modeling to traffic prediction and urban planning, we need quantitative models that can account for the statistical characteristics of individual human trajectories. Here we use empirical data on human mobility, captured by mobile phone traces, to show that the predictions of the CTRW models are in systematic conflict with the empirical results. We introduce two principles that govern human trajectories, allowing us to build a statistically self-consistent microscopic model for individual human mobility. The model not only accounts for the empirically observed scaling laws but also allows us to analytically predict most of the pertinent scaling exponents.

cond-mat.dis-nn↗

arXiv2010

Small world-Fractal Transition in Complex Networks: Renormalization Group Approach

We show that renormalization group (RG) theory applied to complex networks are useful to classify network topologies into universality classes in the space of configurations. The RG flow readily identifies a small-world/fractal transition by finding (i) a trivial stable fixed point of a complete graph, (ii) a non-trivial point of a pure fractal topology that is stable or unstable according to the amount of long-range links in the network, and (iii) another stable point of a fractal with short-cuts that exists exactly at the small-world/fractal transition. As a collateral, the RG technique explains the coexistence of the seemingly contradicting fractal and small-world phases and allows to extract information on the distribution of short-cuts in real-world networks, a problem of importance for information flow in the system.

cond-mat.dis-nn↗

arXiv2009

Jamming III: Characterizing Randomness via the Entropy of Jammed Matter

The nature of randomness in disordered packings of frictional and frictionless spheres is investigated using theory and simulations of identical spherical grains. The entropy of the packings is defined through the force and volume ensemble of jammed matter and shown difficult to calculate analytically. A mesoscopic ensemble of isostatic states is then utilized in an effort to predict the entropy through the defnition of a volume function dependent on the coordination number. Equations of state are obtained relating entropy, volume fraction and compactivity characterizing the different states of jammed matter, and elucidating the phase diagram for jammed granular matter. Analytical calculations are compared to numerical simulations using volume fluctuation analysis and graph theoretical methods, with reasonable agreement. The entropy of the jammed system reveals that the random loose packings are more disordered than random close packings, allowing for an unambiguous interpretation of both limits. Ensemble calculations show that the entropy vanishes at random close packing (RCP), while numerical simulations show that a finite entropy remains in the microscopic states at RCP. The notion of a negative compactivity, that explores states with volume fractions below those achievable by existing simulation protocols, is also explored, expanding the equations of state. We discuss possible extensions to the present mesoscopic approach describing packings from RLP to RCP to the ordered branch of the equation of state in an effort to understand the entropy of jammed matter in the full range of densities from RLP to FCC.

cond-mat.soft↗

arXiv2009

Entropy of jammed matter

We investigate the nature of randomness in disordered packings of frictional spheres. We calculate the entropy of 3D packings through the force and volume ensemble of jammed matter, a mesoscopic ensemble and numerical simulations using volume fluctuation analysis and graph theoretical methods. Equations of state are obtained relating entropy, volume fraction and compactivity characterizing the different states of jammed matter. At the mesoscopic level the entropy vanishes at random close packing. The entropy of the jammed system reveals that the random loose packings are more disordered than random close packings, allowing for an unambiguous interpretation of both limits.

cond-mat.soft↗

arXiv2009

Energy-landscape network approach to the glass transition

We study the energy-landscape network of Lennard-Jones clusters as a model of a glass forming system. We find the stable basins and the first order saddles connecting them, and identify them with the network nodes and links, respectively. We analyze the network properties and model the system's evolution. Using the model, we explore the system's response to varying cooling rates, and reproduce many of the glass transition properties. We also find that the static network structure gives rise to a critical temperature where a percolation transition breaks down the space of configurations into disconnected components. Finally, we discuss the possibility of studying the system mathematically with a trap-model generalized to networks.

cond-mat.soft↗

arXiv2008

From force distribution to average coordination number in frictional granular matter

We study the joint probability distribution of normal and tangential frictional forces in jammed granular media, $P_μ(f_t, f_n)$, for various friction coefficient $μ$, especially when $μ= \infty$. A universal scaling law is found to collapse the data for $μ=0$ to $\infty$ demonstrating a link between force distribution $P_μ(f_t, f_n)$ and average coordination number, $z^μ_c$. The results determine $z_c^μ$ for a finite friction coefficient, extending the constraints counting argument of isostatic granular packing to finite frictional packings.

cond-mat.soft↗

arXiv2008

Fractal and Transfractal Scale-Free Networks

Self-similarity is a property of fractal structures, a concept introduced by Mandelbrot and one of the fundamental mathematical results of the 20th century. The importance of fractal geometry stems from the fact that these structures were recognized in numerous examples in Nature, from the coexistence of liquid/gas at the critical point of evaporation of water, to snowflakes, to the tortuous coastline of the Norwegian fjords, to the behavior of many complex systems such as economic data, or the complex patterns of human agglomeration. Here we review the recent advances in self-similarity of complex networks and its relation to transport, diffusion, percolations and other topological properties such us degree distribution, modularity, and degree-degree correlations.

physics.soc-ph↗

arXiv2008

Scaling of degree correlations and the influence on diffusion in scale-free networks

Connectivity correlations play an important role in the structure of scale-free networks. While several empirical studies exist, there is no general theoretical analysis that can explain the largely varying behavior of real networks. Here, we use scaling theory to quantify the degree of correlations in the particular case of networks with a power-law degree distribution. These networks are classified in terms of their correlation properties, revealing additional information on their structure. For instance, the studied social networks and the Internet at the router level are clustered around the line of random networks, implying a strongly connected core of hubs. On the contrary, some biological networks and the WWW exhibit strong anti-correlations. The present approach can be used to study robustness or diffusion, where we find that anti-correlations tend to accelerate the diffusion process.

physics.soc-ph↗

arXiv2008

Particle dynamics and effective temperature of jammed granular matter in a slowly sheared 3D Couette cell

We report experimental measurements of particle dynamics on slowly sheared granular matter in a three-dimensional (3D) Couette cell. A closely-packed ensemble of transparent spherical beads is confined by an external pressure and filled with fluid to match both the density and refractive index of the beads. This allows us to track tracer particles embedded in the system and obtain three-dimensional trajectories as a function of time. We study the PDF of the vertical and radial displacements, finding Gaussian and exponential distributions, respectively. For slow shear rates, the mean-square fluctuations in all three directions are found to be dependent only on the angular displacement of the Couette cell. Both the diffusivity and mobility of tracer particles are proportional to the shear rate, giving rise to a constant effective temperature, characteristic of the jammed system.

cond-mat.soft↗

arXiv2007

Scaling theory of transport in complex networks

Transport is an important function in many network systems and understanding its behavior on biological, social, and technological networks is crucial for a wide range of applications. However, it is a property that is not well-understood in these systems and this is probably due to the lack of a general theoretical framework. Here, based on the finding that renormalization can be applied to bio-networks, we develop a scaling theory of transport in self-similar networks. We demonstrate the networks invariance under length scale renormalization and we show that the problem of transport can be characterized in terms of a set of critical exponents. The scaling theory allows us to determine the influence of the modular structure on transport. We also generalize our theory by presenting and verifying scaling arguments for the dependence of transport on microscopic features, such as the degree of the nodes and the distance between them. Using transport concepts such as diffusion and resistance we exploit this invariance and we are able to explain, based on the topology of the network, recent experimental results on the broad flow distribution in metabolic networks.

cond-mat.dis-nn↗

arXiv2007

How to calculate the fractal dimension of a complex network: the box covering algorithm

Covering a network with the minimum possible number of boxes can reveal interesting features for the network structure, especially in terms of self-similar or fractal characteristics. Considerable attention has been recently devoted to this problem, with the finding that many real networks are self-similar fractals. Here we present, compare and study in detail a number of algorithms that we have used in previous papers towards this goal. We show that this problem can be mapped to the well-known graph coloring problem and then we simply can apply well-established algorithms. This seems to be the most efficient method, but we also present two other algorithms based on burning which provide a number of other benefits. We argue that the presented algorithms provide a solution close to optimal and that another algorithm that can significantly improve this result in an efficient way does not exist. We offer to anyone that finds such a method to cover his/her expenses for a 1-week trip to our lab in New York (details in http://jamlab.org).

cond-mat.dis-nn↗