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Register a new userThe critical earthquake concept applied to mine rockbursts with time-to-failure analysis
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We report new tests of the critical earthquake concepts performed on rockbursts in deep South African mines. We extend the concept of an optimal time and space correlation region and test it on the eight main shocks of our catalog provided by ISSI. In a first test, we use the simplest signature of criticality in terms of a power law time-to-failure formula. Notwithstanding the fact that the search for the optimal correlation size is performed with this simple power law, we find evidence both for accelerated seismicity and for the presence of logperiodic behavior with a prefered scaling factor close to 2. We then propose a new algorithm based on a space and time smoothing procedure, which is also intended to account for the finite range and time mechanical interactions between events. This new algorithm provides a much more robust and efficient construction of the optimal correlation region, which allows us the use of the logperiodic formula directly in the search process. In this preliminary work, we have only tested the new algorithm on the largest event on the catalog. The result is of remarkable good quality with a dramatic improvement in accuracy and robustness. This confirms the potential importance of logperiodic signals. Our study opens the road for an efficient implemention of a systematic testing procedure of real-time predictions.
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We test the concept that seismicity prior to a large earthquake can be understood in terms of the statistical physics of a critical phase transition. In this model, the cumulative seismic strain release increases as a power-law time-to-failure before the final event. Furthermore, the region of correlated seismicity predicted by this model is much greater than would be predicted from simple elasto-dynamic interactions. We present a systematic procedure to test for the accelerating seismicity predicted by the critical point model and to identify the region approaching criticality, based on a comparison between the observed cumulative energy (Benioff strain) release and the power-law behavior predicted by theory. This method is used to find the critical region before all earthquakes along the San Andreas system since 1950 with M 6.5. The statistical significance of our results is assessed by performing the same procedure on a large number of randomly generated synthetic catalogs. The null hypothesis, that the observed acceleration in all these earthquakes could result from spurious patterns generated by our procedure in purely random catalogs, is rejected with 99.5% confidence. An empirical relation between the logarithm of the critical region radius (R) and the magnitude of the final event (M) is found, such that log R mu 0.5 M, suggesting that the largest probable event in a given region scales with the size of the regional fault network.
We propose a new test of the critical earthquake model based on the hypothesis that precursory earthquakes are ``actors that create fluctuations in the stress field which exhibit an increasing correlation length as the critical large event becomes imminent. Our approach constitutes an attempt to build a more physically-based cumulative function in the spirit of but improving on the cumulative Benioff strain used in previous works documenting the phenomenon of accelerated seismicity. Using a space and time dependent visco-elastic Green function in a two-layer model of the Earth lithosphere, we compute the spatio-temporal stress fluctuations induced by every earthquake precursor and estimate, through an appropriate wavelet transform, the contribution of each event to the correlation properties of the stress field around the location of the main shock at different scales. Our physically-based definition of the cumulative stress function adding up the contribution of stress loads by all earthquakes preceding a main shock seems to be unable to reproduce an acceleration of the cumulative stress nor an increase of the stress correlation length similar to those observed previously for the cumulative Benioff strain. Either earthquakes are ``witnesses of large scale tectonic organization and/or the triggering Green function requires much more than just visco-elastic stress transfers.
In this paper we introduce a new algorithm to study some NP-complete problems. This algorithm is a Markov Chain Monte Carlo (MCMC) inspired by the cavity method developed in the study of spin glass. We will focus on the maximum clique problem and we will compare this new algorithm with several standard algorithms on some DIMACS benchmark graphs and on random graphs. The performances of the new algorithm are quite surprising. Our effort in this paper is to be clear as well to those readers who are not in the field.
The Casimir effect in quantum electrodynamics (QED) is perhaps the best-known example of fluctuation-induced long-ranged force acting on objects (conducting plates) immersed in a fluctuating medium (quantum electromagnetic field in vacuum). A similar effect emerges in statistical physics, where the force acting, e.g., on colloidal particles immersed in a binary liquid mixture is affected by the classical thermal fluctuations occurring in the surrounding medium. The resulting Casimir-like force acquires universal features upon approaching a critical point of the medium and becomes long-ranged at criticality. In turn, this universality allows one to investigate theoretically the temperature dependence of the force via representative models and to stringently test the corresponding predictions in experiments. In contrast to QED, the Casimir force resulting from critical fluctuations can be easily tuned with respect to strength and sign by surface treatments and temperature control. We present some recent advances in the theoretical study of the universal properties of the critical Casimir force arising in thin films. The corresponding predictions compare very well with the experimental results obtained for wetting layers of various fluids. We discuss how the Casimir force between a colloidal particle and a planar wall immersed in a binary liquid mixture has been measured with femto-Newton accuracy, comparing these experimental results with the corresponding theoretical predictions.
The need to unravel modulations hidden in noisy time series of experimental data is a well known problem, traditionally attacked through a variety of methods, among which a popular tool is the so called Lomb-Scargle periodogram. Recently, for a class of problems in the solar neutrino field, it has been proposed an alternative maximum likelihood based approach, intended to overcome some intrinsic limitations affecting the Lomb-Scargle implementation. This work is focused to highlight the features of the likelihood methodology, introducing in particular an analytical approach to assess the quantitative significance of the potential modulation signals. As an example, the proposed method is applied to the time series of the measured values of the 8B neutrino flux released by the Super-Kamiokande collaboration, and the results compared with those of previous analysis performed on the same data sets. It is also examined in detail the comparison between the Lomb-Scargle and the likelihood methods, giving in the appendix the complete demonstration of their close relationship.
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