arXiv subjects

Alvaro Corral

Publications and source records attributed to Alvaro Corral.

At least 37 records · Page 2Linked to original sources

arXiv2014

Finite-size scaling of survival probability in branching processes

Branching processes pervade many models in statistical physics. We investigate the survival probability of a Galton-Watson branching process after a finite number of generations. We reveal the finite-size scaling law of the survival probability for a given branching process ruled by a probability distribution of the number of offspring per element whose standard deviation is finite, obtaining the exact scaling function as well as the critical exponents. Our findings prove the universal behavior of branching processes concerning the survival probability.

cond-mat.stat-mech↗

arXiv2014

Data-Driven Prediction of Thresholded Time Series of Rainfall and SOC models

We study the occurrence of events, subject to threshold, in a representative SOC sandpile model and in high-resolution rainfall data. The predictability in both systems is analyzed by means of a decision variable sensitive to event clustering, and the quality of the predictions is evaluated by the receiver operating characteristics (ROC) method. In the case of the SOC sandpile model, the scaling of quiet-time distributions with increasing threshold leads to increased predictability of extreme events. A scaling theory allows us to understand all the details of the prediction procedure and to extrapolate the shape of the ROC curves for the most extreme events. For rainfall data, the quiet-time distributions do not scale for high thresholds, which means that the corresponding ROC curves cannot be straightforwardly related to those for lower thresholds.

physics.ao-ph↗

arXiv2014

Scaling in the Timing of Extreme Events

Extreme events can come either from point processes, when the size or energy of the events is above a certain threshold, or from time series, when the intensity of a signal surpasses a threshold value. We are particularly concerned by the time between these extreme events, called respectively waiting time and quiet time. If the thresholds are high enough it is possible to justify the existence of scaling laws for the probability distribution of the times as a function of the threshold value, although the scaling functions are different in each case. For point processes, in addition to the trivial Poisson process, one can obtain double-power-law distributions with no finite mean value. This is justified in the context of renormalization-group transformations, where such distributions arise as limiting distributions after iterations of the transformation. Clear connections with the generalized central limit theorem are established from here. The non-existence of finite moments leads to a semi-parametric scaling law in terms of the sample mean waiting time, in which the (usually unkown) scale parameter is eliminated but not the exponents. In the case of time series, scaling can arise by considering random-walk-like signals with absorbing boundaries, resulting in distributions with a power-law "bulk" and a faster decay for long times. For large thresholds the moments of the quiet-time distribution show a power-law dependence with the scale parameter, and isolation of the latter and of the exponents leads to a non-parametric scaling law in terms only of the moments of the distribution. Conclusions about the projections of changes in the occurrence of natural hazards lead to the necessity of distinguishing the behavior of the mean of the distribution with the behavior of the extreme events.

cond-mat.stat-mech↗

arXiv2013

Fitting and goodness-of-fit test of non-truncated and truncated power-law distributions

Power-law distributions contain precious information about a large variety of processes in geoscience and elsewhere. Although there are sound theoretical grounds for these distributions, the empirical evidence in favor of power laws has been traditionally weak. Recently, Clauset et al. have proposed a systematic method to find over which range (if any) a certain distribution behaves as a power law. However, their method has been found to fail, in the sense that true (simulated) power-law tails are not recognized as such in some instances, and then the power-law hypothesis is rejected. Moreover, the method does not work well when extended to power-law distributions with an upper truncation. We explain in detail a similar but alternative procedure, valid for truncated as well as for non-truncated power-law distributions, based in maximum likelihood estimation, the Kolmogorov-Smirnov goodness-of-fit test, and Monte Carlo simulations. An overview of the main concepts as well as a recipe for their practical implementation is provided. The performance of our method is put to test on several empirical data which were previously analyzed with less systematic approaches. The databases presented here include the half-lives of the radionuclides, the seismic moment of earthquakes in the whole world and in Southern California, a proxy for the energy dissipated by tropical cyclones elsewhere, the area burned by forest fires in Italy, and the waiting times calculated over different spatial subdivisions of Southern California. We find the functioning of the method very satisfactory.

physics.geo-ph↗

arXiv2012

Scale Invariant Events and Dry Spells for Medium Resolution Local Rain Data

We analyze distributions of rain-event sizes, rain-event durations, and dry-spell durations for data obtained from a network of 20 rain gauges scattered in a region of the NW Mediterranean coast. While power-law distributions model the dry-spell durations with a common exponent 1.50 +- 0.05, density analysis is inconclusive for event sizes and event durations, due to finite size effects. However, we present alternative evidence of the existence of scale invariance in these distributions by means of different data collapses of the distributions. These results are in agreement with the expectations from the Self-Organized Criticality paradigm, and demonstrate that scaling properties of rain events and dry spells can also be observed for medium resolution rain data.

physics.ao-ph↗

arXiv2012

Statistical similarity between the compression of a porous material and earthquakes

It has been long stated that there are profound analogies between fracture experiments and earthquakes; however, few works attempt a complete characterization of the parallelisms between these so separate phenomena. We study the Acoustic Emission events produced during the compression of Vycor (SiO2). The Gutenberg-Richter law, the modified Omori's law, and the law of aftershock productivity are found to hold for a minimum of 5 decades, are independent of the compression rate, and keep stationary for all the duration of the experiments. The waiting-time distribution fulfills a unified scaling law with a power-law exponent close to 2.45 for long times, which is explained in terms of the temporal variations of the activity rate.

physics.geo-ph↗

arXiv2012

Criticality and self-organization in branching processes: application to natural hazards

The statistics of natural catastrophes contains very counter-intuitive results. Using earthquakes as a working example, we show that the energy radiated by such events follows a power-law or Pareto distribution. This means, in theory, that the expected value of the energy does not exist (is infinite), and in practice, that the mean of a finite set of data in not representative of the full population. Also, the distribution presents scale invariance, which implies that it is not possible to define a characteristic scale for the energy. A simple model to account for this peculiar statistics is a branching process: the activation or slip of a fault segment can trigger other segments to slip, with a certain probability, and so on. Although not recognized initially by seismologists, this is a particular case of the stochastic process studied by Galton and Watson one hundred years in advance, in order to model the extinction of (prominent) families. Using the formalism of probability generating functions we will be able to derive, in an accessible way, the main properties of these models. Remarkably, a power-law distribution of energies is only recovered in a very special case, when the branching process is at the onset of attenuation and intensification, i.e., at criticality. In order to account for this fact, we introduce the self-organized critical models, in which, by means of some feedback mechanism, the critical state becomes an attractor in the evolution of such systems. Analogies with statistical physics are drawn. The bulk of the material presented here is self-contained, as only elementary probability and mathematics are needed to start to read.

cond-mat.stat-mech↗

arXiv2012

Variability of North Atlantic hurricanes: seasonal versus individual-event features

Tropical cyclones are affected by a large number of climatic factors, which translates into complex patterns of occurrence. The variability of annual metrics of tropical-cyclone activity has been intensively studied, in particular since the sudden activation of the N Atl in the mid 1990's. We provide first a swift overview on previous work by diverse authors about these annual metrics for the NAtl basin, where the natural variability of the phenomenon, the existence of trends, the drawbacks of the records, and the influence of global warming have been the subject of interesting debates. Next, we present an alternative approach that does not focus on seasonal features but on the characteristics of single events [Corral et al Nature Phys 6, 693, 2010]. It is argued that the individual-storm power dissipation index (PDI) constitutes a natural way to describe each event, and further, that the PDI statistics yields a robust law for the occurrence of tropical cyclones in terms of a power law. In this context, methods of fitting these distributions are discussed. As an important extension to this work we introduce a distribution function that models the whole range of the PDI density (excluding incompleteness effects at the smallest values), the gamma distribution, consisting in a power-law with an exponential decay at the tail. The characteristic scale of this decay, represented by the cutoff parameter, provides very valuable information on the finiteness size of the basin, via the largest values of the PDIs that the basin can sustain. We use the gamma fit to evaluate the influence of sea surface temperature (SST) on the occurrence of extreme PDI values, for which we find an increase around 50 % in the values of these basin-wide events for a 0.49 degC SST average difference. ...

physics.ao-ph↗

arXiv2012

A practical recipe to fit discrete power-law distributions

Power laws pervade statistical physics and complex systems, but, traditionally, researchers in these fields have paid little attention to properly fit these distributions. Who has not seen (or even shown) a log-log plot of a completely curved line pretending to be a power law? Recently, Clauset et al. have proposed a method to decide if a set of values of a variable has a distribution whose tail is a power law. The key of their procedure is the identification of the minimum value of the variable for which the fit holds, which is selected as the value for which the Kolmogorov-Smirnov distance between the empirical distribution and its maximum-likelihood fit is minimum. However, it has been shown that this method can reject the power-law hypothesis even in the case of power-law simulated data. Here we propose a simpler selection criterion, which is illustrated with the more involving case of discrete power-law distributions.

stat.AP↗

arXiv2011

Non-characteristic Half-lives in Radioactive Decay

Half-lives of radionuclides span more than 50 orders of magnitude. We characterize the probability distribution of this broad-range data set at the same time that explore a method for fitting power-laws and testing goodness-of-fit. It is found that the procedure proposed recently by Clauset et al. [SIAM Rev. 51, 661 (2009)] does not perform well as it rejects the power-law hypothesis even for power-law synthetic data. In contrast, we establish the existence of a power-law exponent with a value around 1.1 for the half-life density, which can be explained by the sharp relationship between decay rate and released energy, for different disintegration types. For the case of alpha emission, this relationship constitutes an original mechanism of power-law generation.

physics.data-an↗

arXiv2009

Scaling of Tropical-Cyclone Dissipation

The influence of climate variability and global warming on the occurrence of tropical cyclones (TC) is a controversial issue. Existing historical databases on the subject are not fully reliable, but a more fundamental hindrance is the lack of basic understanding regarding the intrinsic nature of tropical cyclone genesis and evolution. It is known that tropical cyclones involve more than a passive response to changing external forcing, but it is not clear which dynamic behaviour best describes them. Here we present a new approach based on the application of the power dissipation index (PDI), which constitutes an estimation of released energy, to individual tropical cyclones. A robust law emerges for the statistics of PDI, valid in four different ocean basins and over long time periods. In addition to suggesting a novel description of the physics of tropical cyclones in terms of critical phenomena, the law allows to quantify their response to changing climatic conditions, with an increase in the largest PDI values with sea surface temperature or the presence of El Nino phenomenon, depending on the basin under consideration. In this way, we demonstrate that the recent upswing in North Atlantic hurricane activity does not involve TCs quantitatively different from those in other sustained high-activity periods prior to 1970.

physics.ao-ph↗

arXiv2009

Statistical Tests for Scaling in the Inter-Event Times of Earthquakes in California

We explore in depth the validity of a recently proposed scaling law for earthquake interevent time distributions in the case of the Southern California, using the waveform cross-correlation catalog of Shearer et al. Two statistical tests are used: on the one hand, the standard two-sample Kolmogorov-Smirnov test is in agreement with the scaling of the distributions. On the other hand, the one-sample Kolmogorov-Smirnov statistic complemented with Monte Carlo simulation of the inter-event times, as done by Clauset et al., supports the validity of the gamma distribution as a simple model of the scaling function appearing on the scaling law, for rescaled inter-event times above 0.01, except for the largest data set (magnitude greater than 2). A discussion of these results is provided.

physics.geo-ph↗

arXiv2009

Universal Complex Structures in Written Language

Quantitative linguistics has provided us with a number of empirical laws that characterise the evolution of languages and competition amongst them. In terms of language usage, one of the most influential results is Zipf's law of word frequencies. Zipf's law appears to be universal, and may not even be unique to human language. However, there is ongoing controversy over whether Zipf's law is a good indicator of complexity. Here we present an alternative approach that puts Zipf's law in the context of critical phenomena (the cornerstone of complexity in physics) and establishes the presence of a large scale "attraction" between successive repetitions of words. Moreover, this phenomenon is scale-invariant and universal -- the pattern is independent of word frequency and is observed in texts by different authors and written in different languages. There is evidence, however, that the shape of the scaling relation changes for words that play a key role in the text, implying the existence of different "universality classes" in the repetition of words. These behaviours exhibit striking parallels with complex catastrophic phenomena.

physics.soc-ph↗

arXiv2008

Point-occurrence self-similarity in crackling-noise systems and in other complex systems

It has been recently found that a number of systems displaying crackling noise also show a remarkable behavior regarding the temporal occurrence of successive events versus their size: a scaling law for the probability distributions of waiting times as a function of a minimum size is fulfilled, signaling the existence on those systems of self-similarity in time-size. This property is also present in some non-crackling systems. Here, the uncommon character of the scaling law is illustrated with simple marked renewal processes, built by definition with no correlations. Whereas processes with a finite mean waiting time do not fulfill a scaling law in general and tend towards a Poisson process in the limit of very high sizes, processes without a finite mean tend to another class of distributions, characterized by double power-law waiting-time densities. This is somehow reminiscent of the generalized central limit theorem. A model with short-range correlations is not able to escape from the attraction of those limit distributions. A discussion on open problems in the modeling of these properties is provided.

cond-mat.stat-mech↗

arXiv2007

Scaling and correlations in the dynamics of forest-fire occurrence

Forest-fire waiting times, defined as the time between successive events above a certain size in a given region, are calculated for Italy. The probability densities of the waiting times are found to verify a scaling law, despite that fact that the distribution of fire sizes is not a power law. The meaning of such behavior in terms of the possible self-similarity of the process in a nonstationary system is discussed. We find that the scaling law arises as a consequence of the stationarity of fire sizes and the existence of a non-trivial ``instantaneous'' scaling law, sustained by the correlations of the process.

physics.geo-ph↗

arXiv2006

Statistical Features of Earthquake Temporal Occurrence

A review of the statistical properties of earthquakes is provided, centered mainly in the work of the author (apologies for that). We explain the scaling law for the recurrence-time distributions, its universal character for stationary seismicity and for Omori sequences, the counterintuitive phenomenon of decreasing hazard with time and the increasing of the expected residual recurrence time, the relation of the scaling law with a renormalization-group transformation, and the correlations between recurrence times and magnitudes. Finally, the connections with Bak et al.'s unified scaling law are analyzed.

cond-mat.other↗

arXiv2006

Universal Earthquake-Occurrence Jumps, Correlations with Time, and Anomalous Diffusion

Spatiotemporal properties of seismicity are investigated for a worldwide (WW) catalog and for Southern California in the stationary case (SC), showing a nearly universal scaling behavior. Distributions of distances between consecutive earthquakes (jumps) are magnitude independent and show two power-law regimes, separated by jump values about 200 km (WW) and 15 km (SC). Distributions of waiting times conditioned to the value of jumps show that both variables are correlated in general, but turn out to be independent when only short or long jumps are considered. Finally, diffusion profiles reflect the shape of the jump distribution.

cond-mat.stat-mech↗

arXiv2005

Comment on "Earthquakes Descaled"

We show that Bak et al.'s unified scaling law cannot be trivially explained by a single Omori aftershock sequence. On the contrary, the spatial heterogeneity of seismicity plays a fundamental role in the unified scaling law, which implies that the law provides a way to quantify seismic patterns in space.

cond-mat.other↗