21,631 research outputs found
Winds in Collision: high-energy particles in massive binary systems
High-resolution radio observations have revealed that non-thermal radio
emission in WR stars arises where the stellar wind of the WR star collides with
that of a binary companion. These colliding-wind binary (CWB) systems offer an
important laboratory for investigating the underlying physics of particle
acceleration. Hydrodynamic models of the binary stellar winds and the
wind-collision region (WCR) that account for the evolution of the electron
energy spectrum, largely due to inverse Compton cooling, are now available.
Radiometry and imaging obtained with the VLA, MERLIN, EVN and VLBA provide
essential constraints to these models. Models of the radio emission from WR146
and WR147 are shown, though these very wide systems do not have defined orbits
and hence lack a number of important model parameters. Multi-epoch VLBI imaging
of the archetype WR+O star binary WR140 through a part of its 7.9-year orbit
has been used to define the orbit inclination, distance and the luminosity of
the companion star to enable the best constraints for any radio emitting CWB
system. Models of the spatial distribution of relativistic electrons and ions,
and the magnetic energy density are used to model the radio emission, and also
to predict the high energy emission at X-ray and gamma-ray energies. It is
clear that high-energy facilities e.g. GLAST and VERITAS, will be important for
constraining particle acceleration parameters such as the spectral index of the
energy spectrum and the acceleration efficiency of both ions and electrons, and
in turn, identify unique models for the radio spectra. This will be especially
important in future attempts to model the spectra of WR140 throughout its
complete orbit. A WCR origin for the synchrotron emission in O-stars, the
progenitors of WR stars, is illustrated by observations of Cyg OB2 No. 9.Comment: Invited review at the 8th EVN Symposium, Torun September 26-29, 2006.
11 pages, 12 figure
Spillovers
Interstate and international spillovers from public agricultural research and development (R&D) investments account for a significant share of agricultural productivitygrowth. Hence, spillovers of agricultural R&D results across geopolitical boundaries have implications for measures of research impacts on productivity, and the implied rates of return to research, as well as for state, national and international agricultural research policy. In studies of aggregate state or national agricultural productivity, interstate or international R&D spillovers might account for half or more of the total measured productivitygrowth. Similarly, results from studies of particular crop technologies indicate that international technology spillovers, and multinational impacts of technologies from international centres, were important elements in the total picture of agricultural development in the 20th Century. Within countries, funding institutions have been developed to address spatial spillovers of agricultural technologies. The fact that corresponding institutions have not been developed for international spillovers has contributed to a global underinvestment in certain types of agricultural research.Research and Development/Tech Change/Emerging Technologies,
Forcing neurocontrollers to exploit sensory symmetry through hard-wired modularity in the game of Cellz
Several attempts have been made in the past to construct encoding schemes that allow modularity to emerge in evolving systems, but success is limited. We believe that in order to create successful and scalable encodings for emerging modularity, we first need to explore the benefits of different types of modularity by hard-wiring these into evolvable systems. In this paper we explore different ways of exploiting sensory symmetry inherent in the agent in the simple game Cellz by evolving symmetrically identical modules. It is concluded that significant increases in both speed of evolution and final fitness can be achieved relative to monolithic controllers. Furthermore, we show that a simple function approximation task that exhibits sensory symmetry can be used as a quick approximate measure of the utility of an encoding scheme for the more complex game-playing task
On the Monotone Upper Bound Problem
The Monotone Upper Bound Problem asks for the maximal number M(d,n) of
vertices on a strictly-increasing edge-path on a simple d-polytope with n
facets. More specifically, it asks whether the upper bound M(d,n)<=M_{ubt}(d,n)
provided by McMullen's (1970) Upper Bound Theorem is tight, where M_{ubt}(d,n)
is the number of vertices of a dual-to-cyclic d-polytope with n facets.
It was recently shown that the upper bound M(d,n)<=M_{ubt}(d,n) holds with
equality for small dimensions (d<=4: Pfeifle, 2003) and for small corank
(n<=d+2: G\"artner et al., 2001). Here we prove that it is not tight in
general: In dimension d=6 a polytope with n=9 facets can have M_{ubt}(6,9)=30
vertices, but not more than 26 <= M(6,9) <= 29 vertices can lie on a
strictly-increasing edge-path.
The proof involves classification results about neighborly polytopes, Kalai's
(1988) concept of abstract objective functions, the Holt-Klee conditions
(1998), explicit enumeration, Welzl's (2001) extended Gale diagrams, randomized
generation of instances, as well as non-realizability proofs via a version of
the Farkas lemma.Comment: 15 pages; 6 figure
Evolving controllers for simulated car racing
This paper describes the evolution of controllers for racing a simulated radio-controlled car around a track, modelled on a real physical track. Five different controller architectures were compared, based on neural networks, force fields and action sequences. The controllers use either egocentric (first person), Newtonian (third person) or no information about the state of the car (open-loop controller). The only controller that is able to evolve good racing behaviour is based on a neural network acting on egocentric inputs
Arms races and car races
Evolutionary car racing (ECR) is extended to the case of two cars racing on the same track. A sensor representation is devised, and various methods of evolving car controllers for competitive racing are explored. ECR can be combined with co-evolution in a wide variety of ways, and one aspect which is explored here is the relative-absolute fitness continuum. Systematical behavioural differences are found along this continuum; further, a tendency to specialization and the reactive nature of the controller architecture are found to limit evolutionary progress
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