23,176 research outputs found
Condensation phase transitions of symmetric conserved-mass aggregation model on complex networks
We investigate condensation phase transitions of symmetric conserved-mass
aggregation (SCA) model on random networks (RNs) and scale-free networks (SFNs)
with degree distribution . In SCA model, masses diffuse
with unite rate, and unit mass chips off from mass with rate . The
dynamics conserves total mass density . In the steady state, on RNs and
SFNs with for , we numerically show that SCA
model undergoes the same type condensation transitions as those on regular
lattices. However the critical line depends on network
structures. On SFNs with , the fluid phase of exponential mass
distribution completely disappears and no phase transitions occurs. Instead,
the condensation with exponentially decaying background mass distribution
always takes place for any non-zero density. For the existence of the condensed
phase for at the zero density limit, we investigate one
lamb-lion problem on RNs and SFNs. We numerically show that a lamb survives
indefinitely with finite survival probability on RNs and SFNs with ,
and dies out exponentially on SFNs with . The finite life time
of a lamb on SFNs with ensures the existence of the
condensation at the zero density limit on SFNs with at which
direct numerical simulations are practically impossible. At ,
we numerically confirm that complete condensation takes place for any on RNs. Together with the recent study on SFNs, the complete condensation
always occurs on both RNs and SFNs in zero range process with constant hopping
rate.Comment: 6 pages, 6 figure
Macrostructural analysis : unravelling polyphase glacitectonic histories
Many Pleistocene glacial profiles look extremely simple, comprising till, or glacitectonite, overlying
older sediments or bedrock (Figure 4.1). In more complex sequences the till may itself be overlain by
younger sediments laid down as the ice retreated or during a completely separate, later phase of
advance. Macroscopically, subglacial traction tills (Evans et al., 2007) are typically massive,
unstructured deposits suggesting that it should be relatively straightforward to unravel the
glacitectonic deformation history recorded by the sequence. Many reconstructions do indeed look
very simple, slabs of sediment have been tilted and stacked and then overridden by the glacier to
cap the structure with till. Added to this is the use of vertical exaggeration which makes the whole
structure look like alpine tectonics (for an example see fig. 5 in van Gijssel, 1987). Dropping the
exaggeration led to the recognition that actually we were looking at much more horizontal
structures, i.e. overriding nappes and not imbricated slabs (van der Wateren, 1987).
Traditionally (van der Meer, 1987) glaciotectonics was thought to relate to large structures
like big push moraines and not to smaller structures like drag structures underneath tills (Figure 4.2),
let alone to the tills themselves. With the notion that deforming bed tills are tectonically and not
sedimentologically structured and could be regarded as tectomicts (Menzies et al., 2006), comes the
realisation that glacitectonics happens across a wide range of scales, from the microscopic to tens of
kilometres. Only by realising the full range of glaciotectonic scales can we hope to understand the
processes
An Algorithm to Simplify Tensor Expressions
The problem of simplifying tensor expressions is addressed in two parts. The
first part presents an algorithm designed to put tensor expressions into a
canonical form, taking into account the symmetries with respect to index
permutations and the renaming of dummy indices. The tensor indices are split
into classes and a natural place for them is defined. The canonical form is the
closest configuration to the natural configuration. In the second part, the
Groebner basis method is used to simplify tensor expressions which obey the
linear identities that come from cyclic symmetries (or more general tensor
identities, including non-linear identities). The algorithm is suitable for
implementation in general purpose computer algebra systems. Some timings of an
experimental implementation over the Riemann package are shown.Comment: 15 pages, Latex2e, submitted to Computer Physics Communications:
Thematic Issue on "Computer Algebra in Physics Research
Quantum Langevin theory of excess noise
In an earlier work [P. J. Bardroff and S. Stenholm], we have derived a fully
quantum mechanical description of excess noise in strongly damped lasers. This
theory is used here to derive the corresponding quantum Langevin equations.
Taking the semi-classical limit of these we are able to regain the starting
point of Siegman's treatment of excess noise [Phys. Rev. A 39, 1253 (1989)].
Our results essentially constitute a quantum derivation of his theory and allow
some generalizations.Comment: 9 pages, 0 figures, revte
Format zorgpad Voeding bij kanker
Het zorgpad ‘Voeding bij kanker’ beschrijft het (logistiek) pad dat de oncologische patiënt doorloopt binnen de voedingszorg vanaf het moment dat screening op behoefte aan voedingszorg plaatsvindt en verwijzing naar de diëtist tot en met follow-up of palliatieve fase. Hierbij zijn het format en de indeling aangehouden van de IKNL-formats van (niet-)tumorspecifieke zorgpade
Superfluid-insulator transition of the Josephson junction array model with commensurate frustration
We have studied the rationally frustrated Josephson-junction array model in
the square lattice through Monte Carlo simulations of D XY-model. For
frustration , the model at zero temperature shows a continuous
superfluid-insulator transition. From the measurement of the correlation
function and the superfluid stiffness, we obtain the dynamical critical
exponent and the correlation length critical exponent . While the dynamical critical exponent is the same as that for cases
, 1/2, and 1/3, the correlation length critical exponent is surprisingly
quite different. When , we have the nature of a first-order transition.Comment: RevTex 4, to appear in PR
The Parallel Persistent Memory Model
We consider a parallel computational model that consists of processors,
each with a fast local ephemeral memory of limited size, and sharing a large
persistent memory. The model allows for each processor to fault with bounded
probability, and possibly restart. On faulting all processor state and local
ephemeral memory are lost, but the persistent memory remains. This model is
motivated by upcoming non-volatile memories that are as fast as existing random
access memory, are accessible at the granularity of cache lines, and have the
capability of surviving power outages. It is further motivated by the
observation that in large parallel systems, failure of processors and their
caches is not unusual.
Within the model we develop a framework for developing locality efficient
parallel algorithms that are resilient to failures. There are several
challenges, including the need to recover from failures, the desire to do this
in an asynchronous setting (i.e., not blocking other processors when one
fails), and the need for synchronization primitives that are robust to
failures. We describe approaches to solve these challenges based on breaking
computations into what we call capsules, which have certain properties, and
developing a work-stealing scheduler that functions properly within the context
of failures. The scheduler guarantees a time bound of in expectation, where and are the work and
depth of the computation (in the absence of failures), is the average
number of processors available during the computation, and is the
probability that a capsule fails. Within the model and using the proposed
methods, we develop efficient algorithms for parallel sorting and other
primitives.Comment: This paper is the full version of a paper at SPAA 2018 with the same
nam
A group processes approach to antiscience beliefs and endorsement of “alternative facts”
The global spread of antiscience beliefs, misinformation, fake news, and conspiracy theories is posing a threat to the well-being of individuals and societies worldwide. Accordingly, research on why people increasingly doubt science and endorse “alternative facts” is flourishing. Much of this work has focused on identifying cognitive biases and individual differences. Importantly, however, the reasons that lead people to question mainstream scientific findings and share misinformation are also inherently tied to social processes that emerge out of divisive commitments to group identities and worldviews. In this special issue, we focus on the important and thus far neglected role of group processes in motivating science skepticism. The articles that feature in this special issue cover three core areas: the group-based roots of antiscience attitudes; the intergroup dynamics between science and conspiratorial thinking; and finally, insights about science denial related to the COVID-19 pandemic. Across all articles, we highlight the role of worldviews, identities, norms, religion, and other inter- and intragroup processes that shape antiscientific attitudes. We hope that this collection will inspire future research endeavors that take a group processes approach to the social psychological study of science skepticism. </jats:p
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