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M. J. Werner

Publications and source records attributed to M. J. Werner.

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Retrospective Evaluation of the Five-Year and Ten-Year CSEP-Italy Earthquake Forecasts

On 1 August 2009, the global Collaboratory for the Study of Earthquake Predictability (CSEP) launched a prospective and comparative earthquake predictability experiment in Italy. The goal of the CSEP-Italy experiment is to test earthquake occurrence hypotheses that have been formalized as probabilistic earthquake forecasts over temporal scales that range from days to years. In the first round of forecast submissions, members of the CSEP-Italy Working Group presented eighteen five-year and ten-year earthquake forecasts to the European CSEP Testing Center at ETH Zurich. We considered the twelve time-independent earthquake forecasts among this set and evaluated them with respect to past seismicity data from two Italian earthquake catalogs. In this article, we present the results of tests that measure the consistency of the forecasts with the past observations. Besides being an evaluation of the submitted time-independent forecasts, this exercise provided insight into a number of important issues in predictability experiments with regard to the specification of the forecasts, the performance of the tests, and the trade-off between the robustness of results and experiment duration. We conclude with suggestions for the future design of earthquake predictability experiments.

physics.geo-ph

Adaptively Smoothed Seismicity Earthquake Forecasts for Italy

We present a model for estimating the probabilities of future earthquakes of magnitudes m > 4.95 in Italy. The model, a slightly modified version of the one proposed for California by Helmstetter et al. (2007) and Werner et al. (2010), approximates seismicity by a spatially heterogeneous, temporally homogeneous Poisson point process. The temporal, spatial and magnitude dimensions are entirely decoupled. Magnitudes are independently and identically distributed according to a tapered Gutenberg-Richter magnitude distribution. We estimated the spatial distribution of future seismicity by smoothing the locations of past earthquakes listed in two Italian catalogs: a short instrumental catalog and a longer instrumental and historical catalog. The bandwidth of the adaptive spatial kernel is estimated by optimizing the predictive power of the kernel estimate of the spatial earthquake density in retrospective forecasts. When available and trustworthy, we used small earthquakes m>2.95 to illuminate active fault structures and likely future epicenters. By calibrating the model on two catalogs of different duration to create two forecasts, we intend to quantify the loss (or gain) of predictability incurred when only a short but recent data record is available. Both forecasts, scaled to five and ten years, were submitted to the Italian prospective forecasting experiment of the global Collaboratory for the Study of Earthquake Predictability (CSEP). An earlier forecast from the model was submitted by Helmstetter et al. (2007) to the Regional Earthquake Likelihood Model (RELM) experiment in California, and, with over half of the five-year experiment over, the forecast performs better than its competitors.

physics.geo-ph

High Resolution Long- and Short-Term Earthquake Forecasts for California

We present two models for estimating the probabilities of future earthquakes in California, to be tested in the Collaboratory for the Study of Earthquake Predictability (CSEP). The first, time-independent model, modified from Helmstetter et al. (2007), provides five-year forecasts for magnitudes m > 4.95. We show that large quakes occur on average near the locations of small m > 2 events, so that a high-resolution estimate of the spatial distribution of future large quakes is obtained from the locations of the numerous small events. We employ an adaptive spatial kernel of optimized bandwidth and assume a universal, tapered Gutenberg-Richter distribution. In retrospective tests, we show that no Poisson forecast could capture the observed variability. We therefore also test forecasts using a negative binomial distribution for the number of events. We modify existing likelihood-based tests to better evaluate the spatial forecast. Our time-dependent model, an Epidemic Type Aftershock Sequence (ETAS) model modified from Helmstetter et al. (2006), provides next-day forecasts for m > 3.95. The forecasted rate is the sum of a background rate, proportional to our time-independent model, and of the triggered events due to all prior earthquakes. Each earthquake triggers events with a rate that increases exponentially with its magnitude and decays in time according to Omori's law. An isotropic kernel models the spatial density of aftershocks for small (< 5.5) events. For larger quakes, we smooth early aftershocks to forecast later events. We estimate parameters by optimizing retrospective forecasts. Our short-term model realizes a gain of about 6.0 over the time-independent model.

physics.geo-ph

Earthquake Forecasting Based on Data Assimilation: Sequential Monte Carlo Methods for Renewal Processes

In meteorology, engineering and computer sciences, data assimilation is routinely employed as the optimal way to combine noisy observations with prior model information for obtaining better estimates of a state, and thus better forecasts, than can be achieved by ignoring data uncertainties. Earthquake forecasting, too, suffers from measurement errors and partial model information and may thus gain significantly from data assimilation. We present perhaps the first fully implementable data assimilation method for earthquake forecasts generated by a point-process model of seismicity. We test the method on a synthetic and pedagogical example of a renewal process observed in noise, which is relevant to the seismic gap hypothesis, models of characteristic earthquakes and to recurrence statistics of large quakes inferred from paleoseismic data records. To address the non-Gaussian statistics of earthquakes, we use sequential Monte Carlo methods, a set of flexible simulation-based methods for recursively estimating arbitrary posterior distributions. We perform extensive numerical simulations to demonstrate the feasibility and benefits of forecasting earthquakes based on data assimilation. In particular, we show that the forecasts based on the Optimal Sampling Importance Resampling (OSIR) particle filter are significantly better than those of a benchmark forecast that ignores uncertainties in the observed event times. We use the marginal data likelihood, a measure of the explanatory power of a model in the presence of data errors, to estimate parameters and compare models.

physics.geo-ph

Statistical Physics Approaches to Seismicity

This entry in the Encyclopedia of Complexity and Systems Science, Springer present a summary of some of the concepts and calculational tools that have been developed in attempts to apply statistical physics approaches to seismology. We summarize the leading theoretical physical models of the space-time organization of earthquakes. We present a general discussion and several examples of the new metrics proposed by statistical physicists, underlining their strengths and weaknesses. The entry concludes by briefly outlining future directions. The presentation is organized as follows. I Glossary II Definition and Importance of the Subject III Introduction IV Concepts and Calculational Tools IV.1 Renormalization, Scaling and the Role of Small Earthquakes in Models of Triggered Seismicity IV.2 Universality IV.3 Intermittent Periodicity and Chaos IV.4 Turbulence IV.5 Self-Organized Criticality V Competing mechanisms and models V.1 Roots of complexity in seismicity: dynamics or heterogeneity? V.2 Critical earthquakes V.3 Spinodal decomposition V.4 Dynamics, stress interaction and thermal fluctuation effects VI Empirical studies of seismicity inspired by statistical physics VI.1 Early successes and latter subsequent challenges VI.2 Entropy method for the distribution of time intervals between mainshocks VI.3 Scaling of the PDF of Waiting Times VI.4 Scaling of the PDF of Distances Between Subsequent Earthquakes VI.5 The Network Approach VII Future Directions

physics.geo-ph

Magnitude Uncertainties Impact Seismic Rate Estimates, Forecasts and Predictability Experiments

The Collaboratory for the Study of Earthquake Predictability (CSEP) aims to prospectively test time-dependent earthquake probability forecasts on their consistency with observations. To compete, time-dependent seismicity models are calibrated on earthquake catalog data. But catalogs contain much observational uncertainty. We study the impact of magnitude uncertainties on rate estimates in clustering models, on their forecasts and on their evaluation by CSEP's consistency tests. First, we quantify magnitude uncertainties. We find that magnitude uncertainty is more heavy-tailed than a Gaussian, such as a double-sided exponential distribution, with scale parameter nu_c=0.1 - 0.3. Second, we study the impact of such noise on the forecasts of a simple clustering model which captures the main ingredients of popular short term models. We prove that the deviations of noisy forecasts from an exact forecast are power law distributed in the tail with exponent alpha=1/(a*nu_c), where a is the exponent of the productivity law of aftershocks. We further prove that the typical scale of the fluctuations remains sensitively dependent on the specific catalog. Third, we study how noisy forecasts are evaluated in CSEP consistency tests. Noisy forecasts are rejected more frequently than expected for a given confidence limit. The Poisson assumption of the consistency tests is inadequate for short-term forecast evaluations. To capture the idiosyncrasies of each model together with any propagating uncertainties, the forecasts need to specify the entire likelihood distribution of seismic rates.

physics.geo-ph

Comment on "Analysis of the Spatial Distribution between Successive Earthquakes" by Davidsen and Paczuski

By analyzing a southern California earthquake catalog, Davidsen and Paczuski [Phys. Rev. Lett. 94, 048501 (2005)] claim to have found evidence contradicting the theory of aftershock zone scaling in favor of scale-free statistics. We present four elements showing that Davidsen and Paczuski's results may be insensitive to the existence of physical length scales associated with aftershock zones or mainshock rupture lengths, so that their claim is unsubstantiated. (i) Their exponent smaller than 1 for a pdf implies that the power law statistics they report is at best an intermediate asymptotic; (ii) their power law is not robust to the removal of 6 months of data around Landers earthquake within a period of 17 years; (iii) the same analysis for Japan and northern California shows no evidence of robust power laws; (iv) a statistical model of earthquake triggering that explicitely obeys aftershock zone scaling can reproduce the observed histogram of Davidsen and Paczuski, demonstrating that their statistic may not be sensitive to the presence of characteristic scales associated with earthquake triggering.

physics.geo-ph

Apparent Clustering and Apparent Background Earthquakes Biased by Undetected Seismicity

In models of triggered seismicity and in their inversion with empirical data, the detection threshold m_d is commonly equated to the magnitude m_0 of the smallest triggering earthquake. This unjustified assumption neglects the possibility of shocks below the detection threshold triggering observable events. We introduce a formalism that distinguishes between the detection threshold m_d and the minimum triggering earthquake m_0 < m_d. By considering the branching structure of one complete cascade of triggered events, we derive the apparent branching ratio n_a (which is the apparent fraction of aftershocks in a given catalog) and the apparent background source S_a that are observed when only the structure above the detection threshold m_d is known due to the presence of smaller undetected events that are capable of triggering larger events. If earthquake triggering is controlled in large part by the smallest magnitudes as several recent analyses have shown, this implies that previous estimates of the clustering parameters may significantly underestimate the true values: for instance, an observed fraction of 55% of aftershocks is renormalized into a true value of 75% of triggered events.

physics.geo-ph

Constraints on the Size of the Smallest Triggering Earthquake from the ETAS Model, Baath's Law, and Observed Aftershock Sequences

The physics of earthquake triggering together with simple assumptions of self-similarity impose the existence of a minimum magnitude m0 below which earthquakes do not trigger other earthquakes. Noting that the magnitude md of completeness of seismic catalogs has no reason to be the same as the magnitude m0 of the smallest triggering earthquake, we use quantitative fits and maximum likelihood inversions of observed aftershock sequences as well as Baath's law, compare with ETAS model predictions and thereby constrain the value of m0. We show that the branching ratio $n$ (average number of triggered earthquake per earthquake also equal to the fraction of aftershocks in seismic catalogs) is the key parameter controlling the minimum triggering magnitude m0. Conversely, physical upper bounds for m0 derived from state- and velocity-weakening friction indicate that at least 60 to 70 percent of all earthquakes are aftershocks.

physics.geo-ph

Photon-photon interactions in cavity electromagnetically induced transparency

Dissipation-free photon-photon interaction at the single photon level is studied in the context of cavity electromagnetically induced transparency (EIT). For a single multilevel atom exhibiting EIT in the strong cavity-coupling regime, the anharmonicity of the atom-cavity system has an upper bound determined by single atom-photon coupling strength. Photon blockade is inferred to occur for both single and multi-atom cases from the behaviour of transition rates between dressed states of the system. Numerical calculations of the second order coherence function indicate that photon antibunching in both single and two-atom cases are strong and comparable.

quant-ph

Phase transitions and the internal noise structure of nonlinear Schrödi nger equation solitons

We predict phase-transitions in the quantum noise characteristics of systems described by the quantum nonlinear Schrödinger equation, showing them to be related to the solitonic field transition at half the fundamental soliton amplitude. These phase-transitions are robust with respect to Raman noise and scattering losses. We also describe the rich internal quantum noise structure of the solitonic fields in the vicinity of the phase-transition. For optical coherent quantum solitons, this leads to the prediction that eliminating the peak side-band noise due to the electronic nonlinearity of silica fiber by spectral filtering leads to the optimal photon-number noise reduction of a fundamental soliton.

quant-ph

Quantum soliton generation using an interferometer

For the first time a method for realizing macroscopic quantum optical solitons is presented. Simultaneous photon-number and momentum squeezing is predicted using soliton propagation in an interferometer. Extraction of soliton pulses closer to true quantum solitons than their coherent counterparts from mode-locked lasers is possible. Moreover, it is a general method of reducing photon-number fluctuations below the shot-noise level for non-soliton pulses as well. It is anticipated that similar reductions in particle fluctuations could occur for other forms of interfering bosonic fields whenever self-interaction nonlinearities exist, for example, interacting ultracold atoms.

quant-ph