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Random-energy model in random fields [PDF]
Physical Review E, 2006 The random-energy model is studied in the presence of random fields. The problem is solved exactly both in the microcanonical ensemble, without recourse to the replica method, and in the canonical ensemble using the replica formalism. The phase diagrams for bimodal and Gaussian random fields are investigated in detail. In contrast to the Gaussian case,
Filho, Luiz O. de Oliveira +2 more
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Partially Observed Markov Random Fields Are Variable Neighborhood Random Fields [PDF]
Journal of Statistical Physics, 2012 The present paper has two goals. First to present a natural example of a new class of random fields which are the variable neighborhood random fields. The example we consider is a partially observed nearest neighbor binary Markov random field. The second goal is to establish sufficient conditions ensuring that the variable neighborhoods are almost ...
Cassandro, M. +2 more
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Regularly varying random fields [PDF]
Stochastic Processes and their Applications, 2020 We study the extremes of multivariate regularly varying random fields. The crucial tools in our study are the tail field and the spectral field, notions that extend the tail and spectral processes of Basrak and Segers (2009). The spatial context requires multiple notions of extremal index, and the tail and spectral fields are applied to clarify these ...
Wu, Lifan, Samorodnitsky, Gennady
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Random Fields in Physics, Biology and Data Science
Frontiers in Physics, 2021 A random field is the representation of the joint probability distribution for a set of random variables. Markov fields, in particular, have a long standing tradition as the theoretical foundation of many applications in statistical physics and ...
Enrique Hernández-Lemus +1 more
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Random fields and random sampling [PDF]
Kybernetika, 2020 The authors study the limit in distribution of the maximum of a stationary bivariate real random field, sampled at double random times under some dependence conditions. It is shown that the limit distribution is a max-semistable distribution when the random samples have a geometric growth pattern. When the random field is sampled at double random times,
Dias, Sandra, Temido, Maria da Graça
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Frontiers in Earth Science, 2022 The 2019 Le Teil earthquake is an illustrative example of a moderate (MW 4.9) yet damaging event, occurring at shallow depth (≈1 km) in a region with little to no geophysical data available.
Fanny Lehmann +4 more
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Applied Sciences, 2023 Natural disasters, when and where they occur, often cause serious social and economic consequences, which require an urgent solution to the problem. In particular, Greece, which is characterized by a complex geological structure and intense tectonic ...
Nikolaos Alamanis, Panagiotis Dakoulas
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Computers & Chemical Engineering, 2022 We present a new modeling paradigm for optimization that we call random field optimization. Random fields are a powerful modeling abstraction that aims to capture the behavior of random variables that live on infinite-dimensional spaces (e.g., space and time) such as stochastic processes (e.g., time series, Gaussian processes, and Markov processes ...
Pulsipher, Joshua L. +2 more
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Spatial Warped Gaussian Processes: Estimation and Efficient Field Reconstruction
Entropy, 2021 A class of models for non-Gaussian spatial random fields is explored for spatial field reconstruction in environmental and sensor network monitoring.
Gareth W. Peters +3 more
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ULTRAMETRIC RANDOM FIELD [PDF]
Infinite Dimensional Analysis, Quantum Probability and Related Topics, 2006 Gaussian random field on general ultrametric space is introduced as a solution of pseudodifferential stochastic equation. Covariation of the introduced random field is computed with the help of wavelet analysis on ultrametric spaces. Notion of ultrametric Markovianity, which describes independence of contributions to random field from different ...
Khrennikov, A. Yu., Kozyrev, S. V.
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