2,595 research outputs found
Novel Si(1-x)Ge(x)/Si heterojunction internal photoemission long wavelength infrared detectors
There is a major need for long-wavelength-infrared (LWIR) detector arrays in the range of 8 to 16 microns which operate with close-cycle cryocoolers above 65 K. In addition, it would be very attractive to have Si-based infrared (IR) detectors that can be easily integrated with Si readout circuitry and have good pixel-to-pixel uniformity, which is critical for focal plane array (FPA) applications. Here, researchers report a novel Si(1-x)Ge(x)/Si heterojunction internal photoemission (HIP) detector approach with a tailorable long wavelength infrared cutoff wavelength, based on internal photoemission over the Si(1-x)Ge(x)/Si heterojunction. The HIP detectors were grown by molecular beam epitaxy (MBE), which allows one to optimize the device structure with precise control of doping profiles, layer thickness and composition. The feasibility of a novel Si(1-x)Ge(x)/Si HIP detector has been demonstrated with tailorable cutoff wavelength in the LWIR region. Photoresponse at wavelengths 2 to 10 microns are obtained with quantum efficiency (QE) above approx. 1 percent in these non-optimized device structures. It should be possible to significantly improve the QE of the HIP detectors by optimizing the thickness, composition, and doping concentration of the Si(1-x)Ge(x) layers and by configuring the detector for maximum absorption such as the use of a cavity structure. With optimization of the QE and by matching the barrier energy to the desired wavelength cutoff to minimize the thermionic current, researchers predict near background limited performance in the LWIR region with operating temperatures above 65K. Finally, with mature Si processing, the relatively simple device structure offers potential for low-cost producible arrays with excellent uniformity
Flow of emotional messages in artificial social networks
Models of message flows in an artificial group of users communicating via the
Internet are introduced and investigated using numerical simulations. We
assumed that messages possess an emotional character with a positive valence
and that the willingness to send the next affective message to a given person
increases with the number of messages received from this person. As a result,
the weights of links between group members evolve over time. Memory effects are
introduced, taking into account that the preferential selection of message
receivers depends on the communication intensity during the recent period only.
We also model the phenomenon of secondary social sharing when the reception of
an emotional e-mail triggers the distribution of several emotional e-mails to
other people.Comment: 10 pages, 7 figures, submitted to International Journal of Modern
Physics
Effect of the accelerating growth of communications networks on their structure
Motivated by data on the evolution of the Internet and World Wide Web we
consider scenarios of self-organization of the nonlinearly growing networks
into free-scale structures. We find that the accelerating growth of the
networks establishes their structure. For the growing networks with
preferential linking and increasing density of links, two scenarios are
possible. In one of them, the value of the exponent of the
connectivity distribution is between 3/2 and 2. In the other, and
the distribution is necessarily non-stationary.Comment: 4 pages revtex, 3 figure
Search in Power-Law Networks
Many communication and social networks have power-law link distributions,
containing a few nodes which have a very high degree and many with low degree.
The high connectivity nodes play the important role of hubs in communication
and networking, a fact which can be exploited when designing efficient search
algorithms. We introduce a number of local search strategies which utilize high
degree nodes in power-law graphs and which have costs which scale sub-linearly
with the size of the graph. We also demonstrate the utility of these strategies
on the Gnutella peer-to-peer network.Comment: 17 pages, 14 figure
Economics-Based Optimization of Unstable Flows
As an example for the optimization of unstable flows, we present an
economics-based method for deciding the optimal rates at which vehicles are
allowed to enter a highway. It exploits the naturally occuring fluctuations of
traffic flow and is flexible enough to adapt in real time to the transient flow
characteristics of road traffic. Simulations based on realistic parameter
values show that this strategy is feasible for naturally occurring traffic, and
that even far from optimality, injection policies can improve traffic flow.
Moreover, the same method can be applied to the optimization of flows of gases
and granular media.Comment: Revised version of ``Optimizing Traffic Flow'' (cond-mat/9809397).
For related work see http://www.parc.xerox.com/dynamics/ and
http://www.theo2.physik.uni-stuttgart.de/helbing.htm
Quantum Portfolios
Quantum computation holds promise for the solution of many intractable
problems. However, since many quantum algorithms are stochastic in nature they
can only find the solution of hard problems probabilistically. Thus the
efficiency of the algorithms has to be characterized both by the expected time
to completion {\it and} the associated variance. In order to minimize both the
running time and its uncertainty, we show that portfolios of quantum algorithms
analogous to those of finance can outperform single algorithms when applied to
the NP-complete problems such as 3-SAT.Comment: revision includes additional data and corrects minor typo
Properties of weighted complex networks
We study two kinds of weighted networks, weighted small-world (WSW) and
weighted scale-free (WSF). The weight of a link between nodes and
in the network is defined as the product of endpoint node degrees; that is
. In contrast to adding weights to links during
networks being constructed, we only consider weights depending on the ``
popularity\rq\rq of the nodes represented by their connectivity. It was found
that the both weighted networks have broad distributions on characterization
the link weight, vertex strength, and average shortest path length.
Furthermore, as a survey of the model, the epidemic spreading process in both
weighted networks was studied based on the standard \emph{susceptible-infected}
(SI) model. The spreading velocity reaches a peak very quickly after the
infection outbreaks and an exponential decay was found in the long time
propagation.Comment: 14 pages, 5 figure
Nonlinear Dynamics in Distributed Systems
We build on a previous statistical model for distributed systems and
formulate it in a way that the deterministic and stochastic processes within
the system are clearly separable. We show how internal fluctuations can be
analysed in a systematic way using Van Kanpen's expansion method for Markov
processes. We present some results for both stationary and time-dependent
states. Our approach allows the effect of fluctuations to be explored,
particularly in finite systems where such processes assume increasing
importance.Comment: Two parts: 8 pages LaTeX file and 5 (uuencoded) figures in Postscript
forma
Log-Networks
We introduce a growing network model in which a new node attaches to a
randomly-selected node, as well as to all ancestors of the target node. This
mechanism produces a sparse, ultra-small network where the average node degree
grows logarithmically with network size while the network diameter equals 2. We
determine basic geometrical network properties, such as the size dependence of
the number of links and the in- and out-degree distributions. We also compare
our predictions with real networks where the node degree also grows slowly with
time -- the Internet and the citation network of all Physical Review papers.Comment: 7 pages, 6 figures, 2-column revtex4 format. Version 2: minor changes
in response to referee comments and to another proofreading; final version
for PR
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