Learning Loosely Connected Markov Random Fields

We consider the structure learning problem for graphical models that we call loosely connected Markov random fields, in which the number of short paths between any pair of nodes is small, and present a new conditional independence test based algorithm for learning the underlying graph structure. The novel maximization step in our algorithm ensures that the true edges are detected correctly even when there are short cycles in the graph. The number of samples required by our algorithm is C*log p, where p is the size of the graph and the constant C depends on the parameters of the model. We show that several previously studied models are examples of loosely connected Markov random fields, and our algorithm achieves the same or lower computational complexity than the previously designed algorithms for individual cases. We also get new results for more general graphical models, in particular, our algorithm learns general Ising models on the Erdos-Renyi random graph G(p, c/p) correctly with running time O(np^5).Comment: 45 pages, minor revisio

On the Kolmogorov Constants for the Second-Order Structure Function and the Energy Spectrum

We examine the behavior of the Kolmogorov constants C_2, C_k, and C_{k1}, which are, respectively, the prefactors of the second order longitudinal structure function, the three dimensional and one-dimensional longitudinal energy spectrum in the inertial range. We show that their ratios, C_2/C_{k1} and C_k/C_{k1}, exhibit clear dependence on the micro-scale Reynolds number R_{\lambda}, implying that they cannot all be independent of R_{\lambda}. In particular, it is found that (C_{k1}/C_2-0.25) = 1.95R_{\lambda}^{-0.68}. The study further reveals that the widely-used relation C_2 = 4.02 C_{k1} holds only asymptotically when R_{\lambda} <= 10^5. It is also found that C_2 has much stronger R_{\lambda}-dependence than either C_k, or C_{k1} if the latter indeed has a systematic dependence on R_{\lambda}. We further show that the variable dependence on R_{\lambda} of these three numbers can be attributed to the difference of the inertial range in real- and wavenumber-space, with inertial range in real-space known to be much shorter than that in wavenumber space.Comment: 10 pages, 4 figures. Journal of Fluid Mechanics format (JFM.cls

Time-Frequency Analysis Reveals Pairwise Interactions in Insect Swarms

The macroscopic emergent behavior of social animal groups is a classic example of dynamical self-organization, and is thought to arise from the local interactions between individuals. Determining these interactions from empirical data sets of real animal groups, however, is challenging. Using multicamera imaging and tracking, we studied the motion of individual flying midges in laboratory mating swarms. By performing a time-frequency analysis of the midge trajectories, we show that the midge behavior can be segmented into two distinct modes: one that is independent and composed of low-frequency maneuvers, and one that consists of higher-frequency nearly harmonic oscillations conducted in synchrony with another midge. We characterize these pairwise interactions, and make a hypothesis as to their biological function

Measurements of the Solid-body Rotation of Anisotropic Particles in 3D Turbulence

We introduce a new method to measure Lagrangian vorticity and the rotational dynamics of anisotropic particles in a turbulent fluid flow. We use 3D printing technology to fabricate crosses (two perpendicular rods) and jacks (three mutually perpendicular rods). Time-resolved measurements of their orientation and solid-body rotation rate are obtained from stereoscopic video images of their motion in a turbulent flow between oscillating grids with $R_\lambda$=$91$. The advected particles have a largest dimension of 6 times the Kolmogorov length, making them a good approximation to anisotropic tracer particles. Crosses rotate like disks and jacks rotate like spheres, so these measurements, combined with previous measurements of tracer rods, allow experimental study of ellipsoids across the full range of aspect ratios. The measured mean square tumbling rate, $\langle \dot{p}_i \dot{p}_i \rangle$, confirms previous direct numerical simulations that indicate that disks tumble much more rapidly than rods. Measurements of the alignment of crosses with the direction of the solid-body rotation rate vector provide the first direct observation of the alignment of anisotropic particles by the velocity gradients of the flow.Comment: 15 pages, 7 figure

Long-Range Acoustic Interactions in Insect Swarms: An Adaptive Gravity Model

The collective motion of groups of animals emerges from the net effect of the interactions between individual members of the group. In many cases, such as birds, fish, or ungulates, these interactions are mediated by sensory stimuli that predominantly arise from nearby neighbors. But not all stimuli in animal groups are short range. Here, we consider mating swarms of midges, which are thought to interact primarily via long-range acoustic stimuli. We exploit the similarity in form between the decay of acoustic and gravitational sources to build a model for swarm behavior. By accounting for the adaptive nature of the midges\u27 acoustic sensing, we show that our \u27adaptive gravity\u27 model makes mean-field predictions that agree well with experimental observations of laboratory swarms. Our results highlight the role of sensory mechanisms and interaction range in collective animal behavior. Additionally, the adaptive interactions that we present here open a new class of equations of motion, which may appear in other biological contexts

Effects of polymer additives in the bulk of turbulent thermal convection

We present experimental evidence that a minute amount of polymer additives can significantly enhance heat transport in the bulk region of turbulent thermal convection. The effects of polymer additives are found to be the \textit{suppression} of turbulent background fluctuations that give rise to incoherent heat fluxes that make no net contribution to heat transport, and at the same time to \textit{increase} the coherency of temperature and velocity fields. The suppression of small-scale turbulent fluctuations leads to more coherent thermal plumes that result in the heat transport enhancement. The fact that polymer additives can increase the coherency of thermal plumes is supported by the measurements of a number of local quantities, such as the extracted plume amplitude and width, the velocity autocorrelation functions and the velocity-temperature cross-correlation coefficient. The results from local measurements also suggest the existence of a threshold value for the polymer concentration, only above which can significant modification of the plume coherent properties and enhancement of the local heat flux be observed. Estimation of the plume emission rate suggests that the second effect of polymer additives is to stabilize the thermal boundary layers.Comment: 8 figures, 11 page

Intrinsic Fluctuations and Driven Response of Insect Swarms

Animals of all sizes form groups, as acting together can convey advantages over acting alone; thus, collective animal behavior has been identified as a promising template for designing engineered systems. However, models and observations have focused predominantly on characterizing the overall group morphology, and often focus on highly ordered groups such as bird flocks. We instead study a disorganized aggregation (an insect mating swarm), and compare its natural fluctuations with the group-level response to an external stimulus. We quantify the swarm’s frequency-dependent linear response and its spectrum of intrinsic fluctuations, and show that the ratio of these two quantities has a simple scaling with frequency. Our results provide a new way of comparing models of collective behavior with experimental data