26,468 research outputs found
Radiation from Bodies with Extreme Acceleration II: Kinematics
When applied to a dipole source subjected to acceleration which is violent
and long lasting (``extreme acceleration''), Maxwell's equations predict
radiative power which augments Larmor's classical radiation formula by a
nontrivial amount. The physical assumptions behind this result are made
possible by the kinematics of a system of geometrical clocks whose tickings are
controlled by cavities which are expanding inertially. For the purpose of
measuring the radiation from such a source we take advantage of the physical
validity of a spacetime coordinate framework (``inertially expanding frame'')
based on such clocks. They are compatible and commensurable with the
accelerated clocks of the accelerated source. By contrast, a common Lorentz
frame with its mutually static clocks won't do: it lacks that commensurability.
Inertially expanding clocks give a physicist a window into the frame of a
source with extreme acceleration. He thus can locate that source and measure
radiation from it without being subjected to such acceleration himself. The
conclusion is that inertially expanding reference frames reveal qualitatively
distinct aspects of nature which would not be accessible if static inertial
frames were the only admissible frames.Comment: This 21-page 13-figure RevTeX4 article is a follow-up to Part I:
"Radiation from violently accelerated bodies", gr-qc/011004
Dominance-Based Multiobjective Simulated Annealing
Copyright © 2008 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.Simulated annealing is a provably convergent optimizer for single-objective problems. Previously proposed multiobjective extensions have mostly taken the form of a single-objective simulated annealer optimizing a composite function of the objectives. We propose a multiobjective simulated annealer utilizing the relative dominance of a solution as the system energy for optimization, eliminating problems associated with composite objective functions. We also propose a method for choosing perturbation scalings promoting search both towards and across the Pareto front. We illustrate the simulated annealer's performance on a suite of standard test problems and provide comparisons with another multiobjective simulated annealer and the NSGA-II genetic algorithm. The new simulated annealer is shown to promote rapid convergence to the true Pareto front with a good coverage of solutions across it comparing favorably with the other algorithms. An application of the simulated annealer to an industrial problem, the optimization of a code-division-multiple access (CDMA) mobile telecommunications network's air interface, is presented and the simulated annealer is shown to generate nondominated solutions with an even and dense coverage that outperforms single objective genetic algorithm optimizers
Coplanar Repeats by Energy Minimization
This paper proposes an automated method to detect, group and rectify
arbitrarily-arranged coplanar repeated elements via energy minimization. The
proposed energy functional combines several features that model how planes with
coplanar repeats are projected into images and captures global interactions
between different coplanar repeat groups and scene planes. An inference
framework based on a recent variant of -expansion is described and fast
convergence is demonstrated. We compare the proposed method to two widely-used
geometric multi-model fitting methods using a new dataset of annotated images
containing multiple scene planes with coplanar repeats in varied arrangements.
The evaluation shows a significant improvement in the accuracy of
rectifications computed from coplanar repeats detected with the proposed method
versus those detected with the baseline methods.Comment: 14 pages with supplemental materials attache
Season- and depth-dependent variability of a demersal fish assemblage in a large fjord estuary (Puget Sound, Washington)
Fjord estuaries are common along the northeast Pacific coastline, but little information is available on fish assemblage structure and its spatiotemporal variability. Here, we examined changes in diversity metrics, species biomasses, and biomass spectra (the distribution of biomass
across body size classes) over three seasons (fall, winter, summer) and at multiple depths (20 to 160 m) in Puget Sound, Washington, a deep and highly urbanized fjord estuary on the U.S. west coast. Our results indicate that
this fish assemblage is dominated by cartilaginous species (spotted ratfish [Hydrolagus colliei] and spiny dogfish
[Squalus acanthias]) and therefore differs fundamentally from fish assemblages found in shallower estuaries in the northeast Pacific. Diversity was greatest in shallow waters
(80 m) that are more common in Puget Sound and that are dominated
by spotted ratf ish and seasonally (fall and summer) by spiny dogfish. Strong depth-dependent variation in the demersal fish assemblage may be a general feature of deep fjord estuaries and indicates pronounced spatial variability in the food web. Future comparisons with less impacted fjords may offer insight into whether cartilaginous
species naturally dominate these systems or only do so under
conditions related to human-caused ecosystem degradation. Information on species distributions is critical for marine spatial planning and for modeling energy flows in coastal food webs. The data presented here will aid these endeavors and highlight areas for future research in this important
yet understudied system
Characterizing the network topology of the energy landscapes of atomic clusters
By dividing potential energy landscapes into basins of attractions
surrounding minima and linking those basins that are connected by transition
state valleys, a network description of energy landscapes naturally arises.
These networks are characterized in detail for a series of small Lennard-Jones
clusters and show behaviour characteristic of small-world and scale-free
networks. However, unlike many such networks, this topology cannot reflect the
rules governing the dynamics of network growth, because they are static spatial
networks. Instead, the heterogeneity in the networks stems from differences in
the potential energy of the minima, and hence the hyperareas of their
associated basins of attraction. The low-energy minima with large basins of
attraction act as hubs in the network.Comparisons to randomized networks with
the same degree distribution reveals structuring in the networks that reflects
their spatial embedding.Comment: 14 pages, 11 figure
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