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At least 199 records · Page 11Linked to original sources

PubMed2001

Theoretical description of teaching-learning processes: a multidisciplinary approach.

A multidisciplinary approach based on concepts from sociology, educational psychology, statistical physics, and computational science is developed for the theoretical description of teaching-learning processes that take place in the classroom. The emerging model is consistent with well-established empirical results, such as the higher achievements reached working in collaborative groups and the influence of the structure of the group on the achievements of the individuals. Furthermore, another social learning process that takes place in massive interactions among individuals via the Internet is also investigated.

Cognition↗

PubMed2001

Multibranch entrainment and slow evolution among branches in coupled oscillators.

In globally coupled oscillators, it is believed that strong higher harmonics of coupling functions are essential for multibranch entrainment (MBE), in which there exist many stable states, whose number scales as approximately O(expN) (where N is the system size). The existence of MBE implies the nonergodicity of the system. Then, because this apparent breaking of ergodicity is caused by microscopic energy barriers, this seems to be in conflict with a basic principle of statistical physics. Using macroscopic dynamical theories, we demonstrate that there is no such ergodicity breaking, and such a system slowly evolves among branch states, jumping over microscopic energy barriers due to the influence of thermal noise. This phenomenon can be regarded as an example of slow dynamics driven by a perturbation along a neutrally stable manifold consisting of an infinite number of branch states.

Journal Article↗

PubMed2002

Robust patterns in food web structure.

We analyze the properties of seven community food webs from a variety of environments, including freshwater, marine-freshwater interfaces, and terrestrial environments. We uncover quantitative unifying patterns that describe the properties of the diverse trophic webs considered and suggest that statistical physics concepts such as scaling and universality may be useful in the description of ecosystems. Specifically, we find that several quantities characterizing these diverse food webs obey functional forms that are universal across the different environments considered. The empirical results are in remarkable agreement with the analytical solution of a recently proposed model for food webs.

Animals↗

PubMed2003

Equilibrium model of bimodal distributions of epitaxial island growth.

We present a nanostructure diagram for use in designing heteroepitaxial systems of quantum dots. The nanostructure diagram is computed using a new equilibrium statistical physics model and predicts the island size and shape distributions for a range of combinations of growth temperature and amount of deposited material. The model is applied to Ge on Si(001), the archetype for bimodal island growth, and the results compare well with data from atomic force microscopy of Ge/Si islands grown by chemical vapor deposition.

Journal Article↗

PubMed2003

Phase transitions in sexual populations subject to stabilizing selection.

We show that a simple model of an evolving sexual population, which dates back to some of the earliest work in theoretical population genetics, exhibits an unexpected and previously unobserved phase transition between ordered and disordered states. This behavior is not present in populations evolving asexually without recombination and is thus important in any comparison of sexual and asexual populations. In order to calculate the details of the phase transition, we use techniques from statistical physics. We introduce the correlation of the population as the order parameter of the system and use maximum entropy inference to find the state of the population at any time.

Biological Evolution↗

PubMed2003

Experimental characterization of transition to chaos in the presence of noise.

Transition to chaos in the presence of noise is an important problem in nonlinear and statistical physics. Recently, a scaling law has been theoretically predicted which relates the Lyapunov exponent to the noise variation near the transition. Here we present experimental observation of noise-induced chaos in an electronic circuit and obtain the fundamental scaling law characterizing the transition. The experimentally obtained scaling exponent agrees very well with that predicted by theory.

Journal Article↗

PubMed2004

First-principles-based surface phase diagram of fully relaxed binary alloy surfaces.

The combination of density-functional theory (DFT) calculations of geometrically fully relaxed binary alloy surfaces with concepts from statistical physics is applied to construct a DFT-based phase diagram for a binary alloy surface. As a first example, we studied the appearance of Co antisite atoms at CoAl(100) surfaces. The structural parameters as multilayer relaxations, surface buckling, lateral order, and segregation profile of the predicted stable surface phases are in excellent agreement with experimental structure determinations applying low-energy electron diffraction.

Journal Article↗

PubMed2004

Error correction on a tree: an instanton approach.

We introduce a method that allows analytical or semianalytical estimating of the post-error correction bit error rate (BER) when a forward-error correction is utilized for transmitting information through a noisy channel. The generic method that applies to a variety of error-correction schemes in the regimes where the BER is low is illustrated using the example of a finite-size code approximated by a treelike structure. Exploring the statistical physics formulation of the problem we find that the BER decreases with the signal-to-noise ratio nonuniformly, i.e., crossing over through a sequence of phases. The higher the signal-to-noise ratio the lower the symmetry of the phase dominating BER.

Journal Article↗

PubMed2005

Colloidal interactions and self-assembly using DNA hybridization.

The specific binding of complementary DNA strands has been suggested as an ideal method for directing the controlled self-assembly of microscopic objects. We report the first direct measurements of such DNA-induced interactions between colloidal microspheres, as well as the first colloidal crystals assembled using them. The interactions measured with our optical tweezer method can be modeled in detail by well-known statistical physics and chemistry, boding well for their application to directed self-assembly. The microspheres' binding dynamics, however, have a surprising power-law scaling that can significantly slow annealing and crystallization.

Colloids↗

PubMed2005

Lossy data compression with random gates.

We introduce a new protocol for a lossy data compression algorithm which is based on constraint satisfaction gates. We show that the theoretical capacity of algorithms built from standard parity-check gates converges exponentially fast to the Shannon's bound when the number of variables seen by each gate increases. We then generalize this approach by introducing random gates. They have theoretical performances nearly as good as parity checks, but they offer the great advantage that the encoding can be done in linear time using the survey inspired decimation algorithm, a powerful algorithm for constraint satisfaction problems derived from statistical physics.

Journal Article↗

PubMed2006

Glassy behavior of light.

We study the nonlinear dynamics of a multimode random laser using the methods of statistical physics of disordered systems. A replica-symmetry breaking phase transition is predicted as a function of the pump intensity. We thus show that light propagating in a random nonlinear medium displays glassy behavior; i.e., the photon gas has a multitude of metastable states and a nonvanishing complexity, corresponding to mode-locking processes in random lasers. The present work reveals the existence of new physical phenomena, and demonstrates how nonlinear optics and random lasers can be a benchmark for the modern theory of complex systems and glasses.

Journal Article↗

PubMed2006

Self-consistent scaling theory for logarithmic-correction exponents.

Multiplicative logarithmic corrections frequently characterize critical behavior in statistical physics. Here, a recently proposed theory relating the exponents of such terms is extended to account for circumstances which often occur when the leading specific-heat critical exponent vanishes. Also, the theory is widened to encompass the correlation function. The new relations are then confronted with results from the literature, and some new predictions for logarithmic corrections in certain models are made.

Journal Article↗

PubMed2001

A Bose-Einstein condensate of metastable atoms.

We report the realization of a Bose-Einstein condensate of metastable atoms (helium in the lowest triplet state). The excitation energy of each atom with respect to the ground state is 20 electron volts, but inelastic processes that would destroy the sample are suppressed strongly enough in a spin-polarized sample to allow condensation. Our detection scheme takes advantage of the metastability to achieve detection of individual atoms as well as of the decay products of inelastic processes. This detection opens the way toward new studies in mesoscopic quantum statistical physics, as well as in atomic quantum optics.

Journal Article↗

PubMed2004

Improved spike-sorting by modeling firing statistics and burst-dependent spike amplitude attenuation: a Markov chain Monte Carlo approach.

Spike-sorting techniques attempt to classify a series of noisy electrical waveforms according to the identity of the neurons that generated them. Existing techniques perform this classification ignoring several properties of actual neurons that can ultimately improve classification performance. In this study, we propose a more realistic spike train generation model. It incorporates both a description of "nontrivial" (i.e., non-Poisson) neuronal discharge statistics and a description of spike waveform dynamics (e.g., the events amplitude decays for short interspike intervals). We show that this spike train generation model is analogous to a one-dimensional Potts spin-glass model. We can therefore tailor to our particular case the computational methods that have been developed in fields where Potts models are extensively used, including statistical physics and image restoration. These methods are based on the construction of a Markov chain in the space of model parameters and spike train configurations, where a configuration is defined by specifying a neuron of origin for each spike. This Markov chain is built such that its unique stationary density is the posterior density of model parameters and configurations given the observed data. A Monte Carlo simulation of the Markov chain is then used to estimate the posterior density. We illustrate the way to build the transition matrix of the Markov chain with a simple, but realistic, model for data generation. We use simulated data to illustrate the performance of the method and to show that this approach can easily cope with neurons firing doublets of spikes and/or generating spikes with highly dynamic waveforms. The method cannot automatically find the "correct" number of neurons in the data. User input is required for this important problem and we illustrate how this can be done. We finally discuss further developments of the method.

Action Potentials↗

PubMed2000

PhysioBank, PhysioToolkit, and PhysioNet: components of a new research resource for complex physiologic signals.

The newly inaugurated Research Resource for Complex Physiologic Signals, which was created under the auspices of the National Center for Research Resources of the National Institutes of Health, is intended to stimulate current research and new investigations in the study of cardiovascular and other complex biomedical signals. The resource has 3 interdependent components. PhysioBank is a large and growing archive of well-characterized digital recordings of physiological signals and related data for use by the biomedical research community. It currently includes databases of multiparameter cardiopulmonary, neural, and other biomedical signals from healthy subjects and from patients with a variety of conditions with major public health implications, including life-threatening arrhythmias, congestive heart failure, sleep apnea, neurological disorders, and aging. PhysioToolkit is a library of open-source software for physiological signal processing and analysis, the detection of physiologically significant events using both classic techniques and novel methods based on statistical physics and nonlinear dynamics, the interactive display and characterization of signals, the creation of new databases, the simulation of physiological and other signals, the quantitative evaluation and comparison of analysis methods, and the analysis of nonstationary processes. PhysioNet is an on-line forum for the dissemination and exchange of recorded biomedical signals and open-source software for analyzing them. It provides facilities for the cooperative analysis of data and the evaluation of proposed new algorithms. In addition to providing free electronic access to PhysioBank data and PhysioToolkit software via the World Wide Web (http://www.physionet. org), PhysioNet offers services and training via on-line tutorials to assist users with varying levels of expertise.

Databases as Topic↗

PubMed2000

Gaussian processes for classification: mean-field algorithms.

We derive a mean-field algorithm for binary classification with gaussian processes that is based on the TAP approach originally proposed in statistical physics of disordered systems. The theory also yields an approximate leave-one-out estimator for the generalization error, which is computed with no extra computational cost. We show that from the TAP approach, it is possible to derive both a simpler "naive" mean-field theory and support vector machines (SVMs) as limiting cases. For both mean-field algorithms and support vector machines, simulation results for three small benchmark data sets are presented. They show that one may get state-of-the-art performance by using the leave-one-out estimator for model selection and the built-in leave-one-out estimators are extremely precise when compared to the exact leave-one-out estimate. The second result is taken as strong support for the internal consistency of the mean-field approach.

Algorithms↗

PubMed2005

Fluctuation-dissipation theorem and models of learning.

Advances in statistical learning theory have resulted in a multitude of different designs of learning machines. But which ones are implemented by brains and other biological information processors? We analyze how various abstract Bayesian learners perform on different data and argue that it is difficult to determine which learning-theoretic computation is performed by a particular organism using just its performance in learning a stationary target (learning curve). Based on the fluctuation-dissipation relation in statistical physics, we then discuss a different experimental setup that might be able to solve the problem.

Animals↗

PubMed1999

Backward projections in the cerebral cortex: implications for memory storage.

Cortical areas are characterized by forward and backward connections between adjacent cortical areas in a processing stream. Within each area there are recurrent collateral connections between the pyramidal cells. We analyze the properties of this architecture for memory storage and processing. Hebb-like synaptic modifiability in the connections and attractor states are incorporated. We show the following: (1) The number of memories that can be stored in the connected modules is of the same order of magnitude as the number that can be stored in any one module using the recurrent collateral connections, and is proportional to the number of effective connections per neuron. (2) Cooperation between modules leads to a small increase in memory capacity. (3) Cooperation can also help retrieval in a module that is cued with a noisy or incomplete pattern. (4) If the connection strength between modules is strong, then global memory states that reflect the pairs of patterns on which the modules were trained together are found. (5) If the intermodule connection strengths are weaker, then separate, local memory states can exist in each module. (6) The boundaries between the global and local retrieval states, and the nonretrieval state, are delimited. All of these properties are analyzed quantitatively with the techniques of statistical physics.

Cerebral Cortex↗