Gaussian Belief with dynamic data and in dynamic network

In this paper we analyse Belief Propagation over a Gaussian model in a dynamic environment. Recently, this has been proposed as a method to average local measurement values by a distributed protocol ("Consensus Propagation", Moallemi & Van Roy, 2006), where the average is available for read-out at every single node. In the case that the underlying network is constant but the values to be averaged fluctuate ("dynamic data"), convergence and accuracy are determined by the spectral properties of an associated Ruelle-Perron-Frobenius operator. For Gaussian models on Erdos-Renyi graphs, numerical computation points to a spectral gap remaining in the large-size limit, implying exceptionally good scalability. In a model where the underlying network also fluctuates ("dynamic network"), averaging is more effective than in the dynamic data case. Altogether, this implies very good performance of these methods in very large systems, and opens a new field of statistical physics of large (and dynamic) information systems.Comment: 5 pages, 7 figure

Large Area Crop Inventory Experiment (LACIE). Intensive test site assessment report

There are no author-identified significant results in this report

Evidence for Thermally Activated Spontaneous Fluxoid Formation in Superconducting Thin-Film Rings

We have observed spontaneous fluxoid generation in thin-film rings of the amorphous superconductor Mo$_3$Si, cooled through the normal-superconducting transition, as a function of quench rate and externally applied magnetic field, using a variable sample temperature scanning SQUID microscope. Our results can be explained using a model of freezout of thermally activated fluxoids, mediated by the transport of bulk vortices across the ring walls. This mechanism is complementary to a mechanism proposed by Kibble and Zurek, which only relies on causality to produce a freezout of order parameter fluctuations.Comment: 4 pages, 3 figure

Hierarchical Models for Independence Structures of Networks

We introduce a new family of network models, called hierarchical network models, that allow us to represent in an explicit manner the stochastic dependence among the dyads (random ties) of the network. In particular, each member of this family can be associated with a graphical model defining conditional independence clauses among the dyads of the network, called the dependency graph. Every network model with dyadic independence assumption can be generalized to construct members of this new family. Using this new framework, we generalize the Erd\"os-R\'enyi and beta-models to create hierarchical Erd\"os-R\'enyi and beta-models. We describe various methods for parameter estimation as well as simulation studies for models with sparse dependency graphs.Comment: 19 pages, 7 figure

Replicated Bethe Free Energy: A Variational Principle behind Survey Propagation

A scheme to provide various mean-field-type approximation algorithms is presented by employing the Bethe free energy formalism to a family of replicated systems in conjunction with analytical continuation with respect to the number of replicas. In the scheme, survey propagation (SP), which is an efficient algorithm developed recently for analyzing the microscopic properties of glassy states for a fixed sample of disordered systems, can be reproduced by assuming the simplest replica symmetry on stationary points of the replicated Bethe free energy. Belief propagation and generalized SP can also be offered in the identical framework under assumptions of the highest and broken replica symmetries, respectively.Comment: appeared in Journal of the Physical Society of Japan 74, 2133-2136 (2005

The sensitivity of land emissivity estimates from AMSR-E at C and X bands to surface properties

Microwave observations at low frequencies exhibit more sensitivity to surface and subsurface properties with little interference from the atmosphere. The objective of this study is to develop a global land emissivity product using passive microwave observations from the Advanced Microwave Scanning Radiometer – Earth Observing System (AMSR-E) and to investigate its sensitivity to land surface properties. The developed product complements existing land emissivity products from SSM/I and AMSU by adding land emissivity estimates at two lower frequencies, 6.9 and 10.65 GHz (C- and X-band, respectively). Observations at these low frequencies penetrate deeper into the soil layer. Ancillary data used in the analysis, such as surface skin temperature and cloud mask, are obtained from International Satellite Cloud Climatology Project (ISCCP). Atmospheric properties are obtained from the TIROS Operational Vertical Sounder (TOVS) observations to determine the small upwelling and downwelling atmospheric emissions as well as the atmospheric transmission. A sensitivity test confirms the small effect of the atmosphere but shows that skin temperature accuracy can significantly affect emissivity estimates. Retrieved emissivities at C- and X-bands and their polarization differences exhibit similar patterns of variation with changes in land cover type, soil moisture, and vegetation density as seen at SSM/I-like frequencies (Ka and Ku bands). The emissivity maps from AMSR-E at these higher frequencies agree reasonably well with the existing SSM/I-based product. The inherent discrepancy introduced by the difference between SSM/I and AMSR-E frequencies, incidence angles, and calibration has been assessed. Significantly greater standard deviation of estimated emissivities compared to SSM/I land emissivity product was found over desert regions. Large differences between emissivity estimates from ascending and descending overpasses were found at lower frequencies due to the inconsistency between thermal IR skin temperatures and passive microwave brightness temperatures which can originate from below the surface. The mismatch between day and night AMSR-E emissivities is greater than ascending and descending differences of SSM/I emissivity. This is because of unique orbit time of AMSR-E (01:30 a.m./p.m. LT) while other microwave sensors have orbit time of 06:00 to 09:00 (a.m./p.m.). This highlights the importance of considering the penetration depth of the microwave signal and diurnal variability of the temperature in emissivity retrieval. The effect of these factors is greater for AMSR-E observations than SSM/I observations, as AMSR-E observations exhibit a greater difference between day and night measures. This issue must be addressed in future studies to improve the accuracy of the emissivity estimates especially at AMSR-E lower frequencies

Statistical Mechanical Development of a Sparse Bayesian Classifier

The demand for extracting rules from high dimensional real world data is increasing in various fields. However, the possible redundancy of such data sometimes makes it difficult to obtain a good generalization ability for novel samples. To resolve this problem, we provide a scheme that reduces the effective dimensions of data by pruning redundant components for bicategorical classification based on the Bayesian framework. First, the potential of the proposed method is confirmed in ideal situations using the replica method. Unfortunately, performing the scheme exactly is computationally difficult. So, we next develop a tractable approximation algorithm, which turns out to offer nearly optimal performance in ideal cases when the system size is large. Finally, the efficacy of the developed classifier is experimentally examined for a real world problem of colon cancer classification, which shows that the developed method can be practically useful.Comment: 13 pages, 6 figure

The Phase Diagram of 1-in-3 Satisfiability Problem

We study the typical case properties of the 1-in-3 satisfiability problem, the boolean satisfaction problem where a clause is satisfied by exactly one literal, in an enlarged random ensemble parametrized by average connectivity and probability of negation of a variable in a clause. Random 1-in-3 Satisfiability and Exact 3-Cover are special cases of this ensemble. We interpolate between these cases from a region where satisfiability can be typically decided for all connectivities in polynomial time to a region where deciding satisfiability is hard, in some interval of connectivities. We derive several rigorous results in the first region, and develop the one-step--replica-symmetry-breaking cavity analysis in the second one. We discuss the prediction for the transition between the almost surely satisfiable and the almost surely unsatisfiable phase, and other structural properties of the phase diagram, in light of cavity method results.Comment: 30 pages, 12 figure

Variations of the McEliece Cryptosystem

Two variations of the McEliece cryptosystem are presented. The first one is based on a relaxation of the column permutation in the classical McEliece scrambling process. This is done in such a way that the Hamming weight of the error, added in the encryption process, can be controlled so that efficient decryption remains possible. The second variation is based on the use of spatially coupled moderate-density parity-check codes as secret codes. These codes are known for their excellent error-correction performance and allow for a relatively low key size in the cryptosystem. For both variants the security with respect to known attacks is discussed