18,243 research outputs found
Probabilistic modeling and statistical inference for random fields and space-time processes
Author from publisher's list. Cover title.Final report for ONR Grant N00014-91-J-100
Nested ocean models: Work in progress
The ongoing work of combining three existing software programs into a nested grid oceanography model is detailed. The HYPER domain decomposition program, the SPEM ocean modeling program, and a quasi-geostrophic model written in England are being combined into a general ocean modeling facility. This facility will be used to test the viability and the capability of two-way nested grids in the North Atlantic
Fluid flow estimation with multiscale ensemble filters based on motion measurements under location uncertainty
International audienceThis paper proposes a novel multi-scale fluid flow data assimilation approach, which integrates and complements the advantages of a Bayesian sequential assimilation technique, the Weighted Ensemble Kalman filter (WEnKF). The data assimilation proposed in this work incorporates measurement brought by an efficient multiscale stochastic formulation of the well-known Lucas-Kanade (LK) estimator. This estimator has the great advantage to provide uncertainties associated to the motion measurements at different scales. The proposed assimilation scheme benefits from this multiscale uncertainty information and enables to enforce a physically plausible dynamical consistency of the estimated motion fields along the image sequence. Experimental evaluations are presented on synthetic and real fluid flow sequences
Synchronicity From Synchronized Chaos
The synchronization of loosely coupled chaotic oscillators, a phenomenon
investigated intensively for the last two decades, may realize the
philosophical notion of synchronicity. Effectively unpredictable chaotic
systems, coupled through only a few variables, commonly exhibit a predictable
relationship that can be highly intermittent. We argue that the phenomenon
closely resembles the notion of meaningful synchronicity put forward by Jung
and Pauli if one identifies "meaningfulness" with internal synchronization,
since the latter seems necessary for synchronizability with an external system.
Jungian synchronization of mind and matter is realized if mind is analogized to
a computer model, synchronizing with a sporadically observed system as in
meteorological data assimilation. Internal synchronization provides a recipe
for combining different models of the same objective process, a configuration
that may also describe the functioning of conscious brains. In contrast to
Pauli's view, recent developments suggest a materialist picture of
semi-autonomous mind, existing alongside the observed world, with both
exhibiting a synchronistic order. Basic physical synchronicity is manifest in
the non-local quantum connections implied by Bell's theorem. The quantum world
resides on a generalized synchronization "manifold", a view that provides a
bridge between nonlocal realist interpretations and local realist
interpretations that constrain observer choice .Comment: 1) clarification regarding the connection with philosophical
synchronicity in Section 2 and in the concluding section 2) reference to
Maldacena-Susskind "ER=EPR" relation in discussion of role of wormholes in
entanglement and nonlocality 3) length reduction and stylistic changes
throughou
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A survey on inverse problems for applied sciences
The aim of this paper is to introduce inversion-based engineering applications and to investigate some of the important ones from mathematical point of view. To do this we employ acoustic, electromagnetic, and elastic waves for presenting different types of inverse problems. More specifically, we first study location, shape, and boundary parameter reconstruction algorithms for the inaccessible targets in acoustics. The inverse problems for the time-dependent differential equations of isotropic and anisotropic elasticity are reviewed in the following section of the paper. These problems were the objects of the study by many authors in the last several decades. The physical interpretations for almost all of these problems are given, and the geophysical applications for some of them are described. In our last section, an introduction with many links into the literature is given for modern algorithms which combine techniques from classical inverse problems with stochastic tools into ensemble methods both for data assimilation as well as for forecasting
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