1,385 research outputs found
Optimal Opinion Control: The Campaign Problem
Opinion dynamics is nowadays a very common field of research. In this article
we formulate and then study a novel, namely strategic perspective on such
dynamics: There are the usual normal agents that update their opinions, for
instance according the well-known bounded confidence mechanism. But,
additionally, there is at least one strategic agent. That agent uses opinions
as freely selectable strategies to get control on the dynamics: The strategic
agent of our benchmark problem tries, during a campaign of a certain length, to
influence the ongoing dynamics among normal agents with strategically placed
opinions (one per period) in such a way, that, by the end of the campaign, as
much as possible normals end up with opinions in a certain interval of the
opinion space. Structurally, such a problem is an optimal control problem. That
type of problem is ubiquitous. Resorting to advanced and partly non-standard
methods for computing optimal controls, we solve some instances of the campaign
problem. But even for a very small number of normal agents, just one strategic
agent, and a ten-period campaign length, the problem turns out to be extremely
difficult. Explicitly we discuss moral and political concerns that immediately
arise, if someone starts to analyze the possibilities of an optimal opinion
control.Comment: 47 pages, 12 figures, and 11 table
ColDICE: a parallel Vlasov-Poisson solver using moving adaptive simplicial tessellation
Resolving numerically Vlasov-Poisson equations for initially cold systems can
be reduced to following the evolution of a three-dimensional sheet evolving in
six-dimensional phase-space. We describe a public parallel numerical algorithm
consisting in representing the phase-space sheet with a conforming,
self-adaptive simplicial tessellation of which the vertices follow the
Lagrangian equations of motion. The algorithm is implemented both in six- and
four-dimensional phase-space. Refinement of the tessellation mesh is performed
using the bisection method and a local representation of the phase-space sheet
at second order relying on additional tracers created when needed at runtime.
In order to preserve in the best way the Hamiltonian nature of the system,
refinement is anisotropic and constrained by measurements of local Poincar\'e
invariants. Resolution of Poisson equation is performed using the fast Fourier
method on a regular rectangular grid, similarly to particle in cells codes. To
compute the density projected onto this grid, the intersection of the
tessellation and the grid is calculated using the method of Franklin and
Kankanhalli (1993) generalised to linear order. As preliminary tests of the
code, we study in four dimensional phase-space the evolution of an initially
small patch in a chaotic potential and the cosmological collapse of a
fluctuation composed of two sinusoidal waves. We also perform a "warm" dark
matter simulation in six-dimensional phase-space that we use to check the
parallel scaling of the code.Comment: Code and illustration movies available at:
http://www.vlasix.org/index.php?n=Main.ColDICE - Article submitted to Journal
of Computational Physic
Quantifying and combining uncertainty for improving the behavior of Digital Twin Systems
Uncertainty is an inherent property of any complex system, especially those
that integrate physical parts or operate in real environments. In this paper,
we focus on the Digital Twins of adaptive systems, which are particularly
complex to design, verify, and optimize. One of the problems of having two
systems (the physical one and its digital replica) is that their behavior may
not always be consistent. In addition, both twins are normally subject to
different types of uncertainties, which complicates their comparison. In this
paper we propose the explicit representation and treatment of the uncertainty
of both twins, and show how this enables a more accurate comparison of their
behaviors. Furthermore, this allows us to reduce the overall system uncertainty
and improve its behavior by properly averaging the individual uncertainties of
the two twins. An exemplary incubator system is used to illustrate and validate
our proposal
Maximum approximate entropy and r threshold: A new approach for regularity changes detection
Approximate entropy (ApEn) has been widely used as an estimator of regularity
in many scientific fields. It has proved to be a useful tool because of its
ability to distinguish different system's dynamics when there is only available
short-length noisy data. Incorrect parameter selection (embedding dimension
, threshold and data length ) and the presence of noise in the signal
can undermine the ApEn discrimination capacity. In this work we show that
() can also be used as a feature to
discern between dynamics. Moreover, the combined use of and
allows a better discrimination capacity to be accomplished, even in
the presence of noise. We conducted our studies using real physiological time
series and simulated signals corresponding to both low- and high-dimensional
systems. When is incapable of discerning between different
dynamics because of the noise presence, our results suggest that
provides additional information that can be useful for classification purposes.
Based on cross-validation tests, we conclude that, for short length noisy
signals, the joint use of and can significantly decrease
the misclassification rate of a linear classifier in comparison with their
isolated use
Hydrological cycle in the Danube basin in present-day and XXII century simulations by IPCCAR4 global climate models
We present an intercomparison and verification analysis of 20 GCMs (Global
Circulation Models) included in the 4th IPCC assessment report regarding their
representation of the hydrological cycle on the Danube river basin for 1961–2000
and for the 2161–2200 SRESA1B scenario runs. The basin-scale properties of the
hydrological cycle are computed by spatially integrating the precipitation, evaporation,
and runoff fields using the Voronoi-Thiessen tessellation formalism. The span of the
model- simulated mean annual water balances is of the same order of magnitude of
the observed Danube discharge of the Delta; the true value is within the range
simulated by the models. Some land components seem to have deficiencies since there
are cases of violation of water conservation when annual means are considered. The
overall performance and the degree of agreement of the GCMs are comparable to those
of the RCMs (Regional Climate Models) analyzed in a previous work, in spite of the
much higher resolution and common nesting of the RCMs. The reanalyses are shown
to feature several inconsistencies and cannot be used as a verification benchmark for
the hydrological cycle in the Danubian region. In the scenario runs, for basically all
models the water balance decreases, whereas its interannual variability increases.
Changes in the strength of the hydrological cycle are not consistent among models:
it is confirmed that capturing the impact of climate change on the hydrological cycle
is not an easy task over land areas. Moreover, in several cases we find that qualitatively
different behaviors emerge among the models: the ensemble mean does not represent
any sort of average model, and often it falls between the models’ clusters
Energetics of climate models: net energy balance and meridional enthalpy transport
We analyze the publicly released outputs of the simulations performed by climate models (CMs) in preindustrial (PI) and Special Report on Emissions Scenarios A1B (SRESA1B) conditions. In the PI simulations, most CMs feature biases of the order of 1 W m −2 for the net global and the net atmospheric, oceanic, and land energy balances. This does not result from transient effects but depends on the imperfect closure of the energy cycle in the fluid components and on inconsistencies over land. Thus, the planetary emission temperature is underestimated, which may explain the CMs' cold bias. In the PI scenario, CMs agree on the meridional atmospheric enthalpy transport's peak location (around 40°N/S), while discrepancies of ∼20% exist on the intensity. Disagreements on the oceanic transport peaks' location and intensity amount to ∼10° and ∼50%, respectively. In the SRESA1B runs, the atmospheric transport's peak shifts poleward, and its intensity increases up to ∼10% in both hemispheres. In most CMs, the Northern Hemispheric oceanic transport decreases, and the peaks shift equatorward in both hemispheres. The Bjerknes compensation mechanism is active both on climatological and interannual time scales. The total meridional transport peaks around 35° in both hemispheres and scenarios, whereas disagreements on the intensity reach ∼20%. With increased CO 2 concentration, the total transport increases up to ∼10%, thus contributing to polar amplification of global warming. Advances are needed for achieving a self-consistent representation of climate as a nonequilibrium thermodynamical system. This is crucial for improving the CMs' skill in representing past and future climate changes
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