1,148 research outputs found
The upper-atmosphere extension of the ICON general circulation model (version: Ua-icon-1.0)
How the upper-atmosphere branch of the circulation contributes to and interacts with the circulation of the middle and lower atmosphere is a research area with many open questions. Inertia-gravity waves, for instance, have moved in the focus of research as they are suspected to be key features in driving and shaping the circulation. Numerical atmospheric models are an important pillar for this research. We use the ICOsahedral Non-hydrostatic (ICON) general circulation model, which is a joint development of the Max Planck Institute for Meteorology (MPI-M) and the German Weather Service (DWD), and provides, e.g., local mass conservation, a flexible grid nesting option, and a non-hydrostatic dynamical core formulated on an icosahedral-triangular grid. We extended ICON to the upper atmosphere and present here the two main components of this new configuration named UA-ICON: an extension of the dynamical core from shallow- to deep-atmosphere dynamics and the implementation of an upper-atmosphere physics package. A series of idealized test cases and climatological simulations is performed in order to evaluate the upper-atmosphere extension of ICON. © Author(s) 2019
Evidence for Quadratic Tidal Tensor Bias from the Halo Bispectrum
The relation between the clustering properties of luminous matter in the form
of galaxies and the underlying dark matter distribution is of fundamental
importance for the interpretation of ongoing and upcoming galaxy surveys. The
so called local bias model, where galaxy density is a function of local matter
density, is frequently discussed as a means to infer the matter power spectrum
or correlation function from the measured galaxy correlation. However,
gravitational evolution generates a term quadratic in the tidal tensor and thus
non-local in the density field, even if this term is absent in the initial
conditions (Lagrangian space). Because the term is quadratic, it contributes as
a loop correction to the power spectrum, so the standard linear bias picture
still applies on large scales, however, it contributes at leading order to the
bispectrum for which it is significant on all scales. Such a term could also be
present in Lagrangian space if halo formation were influenced by the tidal
field. We measure the corresponding coupling strengths from the
matter-matter-halo bispectrum in numerical simulations and find a non-vanishing
coefficient for the tidal tensor term. We find no scale dependence of the bias
parameters up to k=0.1 h/Mpc and that the tidal effect is increasing with halo
mass. While the Lagrangian bias picture is a better description of our results
than the Eulerian bias picture, our results suggest that there might be a tidal
tensor bias already in the initial conditions. We also find that the
coefficients of the quadratic density term deviate quite strongly from the
theoretical predictions based on the spherical collapse model and a universal
mass function. Both quadratic density and tidal tensor bias terms must be
included in the modeling of galaxy clustering of current and future surveys if
one wants to achieve the high precision cosmology promise of these datasets.Comment: 14 pages, 4 figures, 1 tabl
Context-aware and automatic configuration of mobile devices in cloud-enabled ubiquitous computing
This is the author's accepted manuscript. The final publication is available at Springer via http://dx.doi.org/10.1007/s00779-013-0698-3. Copyright @ Springer-Verlag London 2013.Context-sensitive (or aware) applications have, in recent years, moved from the realm of possibilities to that of ubiquity. One exciting research area that is still very much in the realm of possibilities is that of cloud computing, and in this paper, we present our work, which explores the overlap of these two research areas. Accordingly, this paper explores the notion of cross-source integration of cloud-based, context-aware information in ubiquitous computing through a developed prototypical solution. Moreover, the described solution incorporates remote and automatic configuration of Android smartphones and advances the research area of context-aware information by harvesting information from several sources to build a rich foundation on which algorithms for context-aware computation can be based. Evaluation results show the viability of integrating and tailoring contextual information to provide users with timely, relevant and adapted application behaviour and content
Systemic risk approach to mitigate delay cascading in railway networks
In public railway systems, minor disruptions can trigger cascading events
that lead to delays in the entire system. Typically, delays originate and
propagate because the equipment is blocking ways, operational units are
unavailable, or at the wrong place at the needed time. The specific
understanding of the origins and processes involved in delay-spreading is still
a challenge, even though large-scale simulations of national railway systems
are becoming available on a highly detailed scale. Without this understanding,
efficient management of delay propagation, a growing concern in some Western
countries, will remain impossible. Here, we present a systemic risk-based
approach to manage daily delay cascading on national scales. We compute the
{\em systemic impact} of every train as the maximum of all delays it could
possibly cause due to its interactions with other trains, infrastructure, and
operational units. To compute it, we design an effective impact network where
nodes are train services and links represent interactions that could cause
delays. Our results are not only consistent with highly detailed and
computationally intensive agent-based railway simulations but also allow us to
pinpoint and identify the causes of delay cascades in detail. The systemic
approach reveals structural weaknesses in railway systems whenever shared
resources are involved. We use the systemic impact to optimally allocate
additional shared resources to the system to reduce delays with minimal costs
and effort. The method offers a practical and intuitive solution for delay
management by optimizing the effective impact network through the introduction
of new cheap local train services.Comment: 27 pages, 14 figure
An algorithm for the direct reconstruction of the dark matter correlation function from weak lensing and galaxy clustering
The clustering of matter on cosmological scales is an essential probe for
studying the physical origin and composition of our Universe. To date, most of
the direct studies have focused on shear-shear weak lensing correlations, but
it is also possible to extract the dark matter clustering by combining
galaxy-clustering and galaxy-galaxy-lensing measurements. In this study we
develop a method that can constrain the dark matter correlation function from
galaxy clustering and galaxy-galaxy-lensing measurements, by focusing on the
correlation coefficient between the galaxy and matter overdensity fields. To
generate a mock galaxy catalogue for testing purposes, we use the Halo
Occupation Distribution approach applied to a large ensemble of N-body
simulations to model pre-existing SDSS Luminous Red Galaxy sample observations.
Using this mock catalogue, we show that a direct comparison between the excess
surface mass density measured by lensing and its corresponding galaxy
clustering quantity is not optimal. We develop a new statistic that suppresses
the small-scale contributions to these observations and show that this new
statistic leads to a cross-correlation coefficient that is within a few percent
of unity down to 5 Mpc/h. Furthermore, the residual incoherence between the
galaxy and matter fields can be explained using a theoretical model for
scale-dependent bias, giving us a final estimator that is unbiased to within
1%. We also perform a comprehensive study of other physical effects that can
affect the analysis, such as redshift space distortions and differences in
radial windows between galaxy clustering and weak lensing observations. We
apply the method to a range of cosmological models and show the viability of
our new statistic to distinguish between cosmological models.Comment: 23 pages, 14 figures, accepted by PRD; minor changes to V1, 1 new
figure, more detailed discussion of the covariance of the new ADSD statisti
Density reconstruction from biased tracers and its application to primordial non-Gaussianity
Large-scale Fourier modes of the cosmic density field are of great value for
learning about cosmology because of their well-understood relationship to
fluctuations in the early universe. However, cosmic variance generally limits
the statistical precision that can be achieved when constraining model
parameters using these modes as measured in galaxy surveys, and moreover, these
modes are sometimes inaccessible due to observational systematics or
foregrounds. For some applications, both limitations can be circumvented by
reconstructing large-scale modes using the correlations they induce between
smaller-scale modes of an observed tracer (such as galaxy positions). In this
paper, we further develop a formalism for this reconstruction, using a
quadratic estimator similar to the one used for lensing of the cosmic microwave
background. We incorporate nonlinearities from gravity, nonlinear biasing, and
local-type primordial non-Gaussianity, and verify that the estimator gives the
expected results when applied to N-body simulations. We then carry out
forecasts for several upcoming surveys, demonstrating that, when reconstructed
modes are included alongside directly-observed tracer density modes,
constraints on local primordial non-Gaussianity are generically tightened by
tens of percents compared to standard single-tracer analyses. In certain cases,
these improvements arise from cosmic variance cancellation, with reconstructed
modes taking the place of modes of a separate tracer, thus enabling an
effective "multitracer" approach with single-tracer observations.Comment: 30 pages plus 14 pages appendices, 19 figure
Beyond the plane-parallel and Newtonian approach: Wide-angle redshift distortions and convergence in general relativity
We extend previous analyses of wide-angle correlations in the galaxy power
spectrum in redshift space to include all general relativistic effects. These
general relativistic corrections to the standard approach become important on
large scales and at high redshifts, and they lead to new terms in the
wide-angle correlations. We show that in principle the new terms can produce
corrections of nearly 10 % on Gpc scales over the usual Newtonian
approximation. General relativistic corrections will be important for future
large-volume surveys such as SKA and Euclid, although the problem of cosmic
variance will present a challenge in observing this.Comment: 14 pages, 5 figures; Typo in equation 5 corrected; results unaffecte
Savor the Cryosphere
This article provides concise documentation of the ongoing retreat of glaciers, along with the implications that the ice loss presents, as well as suggestions for geoscience educators to better convey this story to both students and citizens. We present the retreat of glaciers—the loss of ice—as emblematic of the recent, rapid contraction of the cryosphere. Satellites are useful for assessing the loss of ice across regions with the passage of time. Ground-based glaciology, particularly through the study of ice cores, can record the history of environmental conditions present during the existence of a glacier. Repeat photography vividly displays the rapid retreat of glaciers that is characteristic across the planet. This loss of ice has implications to rising sea level, greater susceptibility to dryness in places where people rely upon rivers delivering melt water resources, and to the destruction of natural environmental archives that were held within the ice. Warming of the atmosphere due to rising concentrations of greenhouse gases released by the combustion of fossil fuels is causing this retreat. We highlight multimedia productions that are useful for teaching this story effectively. As geoscience educators, we attempt to present the best scholarship as accurately and eloquently as we can, to address the core challenge of conveying the magnitude of anthropogenic impacts, while also encouraging optimistic determination on the part of students, coupled to an increasingly informed citizenry. We assert that understanding human perturbation of nature, then choosing to engage in thoughtful science-based decision-making, is a wise choice. This topic comprised “Savor the Cryosphere,” a Pardee Keynote Symposium at the 2015 Annual Meeting in Baltimore, Maryland, USA, for which the GSA recorded supporting interviews and a webinar
Primordial non-Gaussianity in the Bispectrum of the Halo Density Field
The bispectrum vanishes for linear Gaussian fields and is thus a sensitive
probe of non-linearities and non-Gaussianities in the cosmic density field.
Hence, a detection of the bispectrum in the halo density field would enable
tight constraints on non-Gaussian processes in the early Universe and allow
inference of the dynamics driving inflation. We present a tree level derivation
of the halo bispectrum arising from non-linear clustering, non-linear biasing
and primordial non-Gaussianity. A diagrammatic description is developed to
provide an intuitive understanding of the contributing terms and their
dependence on scale, shape and the non-Gaussianity parameter fNL. We compute
the terms based on a multivariate bias expansion and the peak-background split
method and show that non-Gaussian modifications to the bias parameters lead to
amplifications of the tree level bispectrum that were ignored in previous
studies. Our results are in a good agreement with published simulation
measurements of the halo bispectrum. Finally, we estimate the expected signal
to noise on fNL and show that the constraint obtainable from the bispectrum
analysis significantly exceeds the one obtainable from the power spectrum
analysis.Comment: 34 pages, 15 figures, (v3): matches JCAP published versio
Anomalous Dimensions and Non-Gaussianity
We analyze the signatures of inflationary models that are coupled to strongly
interacting field theories, a basic class of multifield models also motivated
by their role in providing dynamically small scales. Near the squeezed limit of
the bispectrum, we find a simple scaling behavior determined by operator
dimensions, which are constrained by the appropriate unitarity bounds.
Specifically, we analyze two simple and calculable classes of examples:
conformal field theories (CFTs), and large-N CFTs deformed by relevant
time-dependent double-trace operators. Together these two classes of examples
exhibit a wide range of scalings and shapes of the bispectrum, including nearly
equilateral, orthogonal and local non-Gaussianity in different regimes. Along
the way, we compare and contrast the shape and amplitude with previous results
on weakly coupled fields coupled to inflation. This signature provides a
precision test for strongly coupled sectors coupled to inflation via irrelevant
operators suppressed by a high mass scale up to 1000 times the inflationary
Hubble scale.Comment: 40 pages, 10 figure
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