223 research outputs found
Motion of four-dimensional rigid body around a fixed point: an elementary approach. I
The goal of this note is to give the explicit solution of Euler-Frahm
equations for the Manakov four-dimensional case by elementary means. For this,
we use some results from the original papers by Schottky [Sch 1891], Koetter
[Koe 1892], Weber [We 1878], and Caspary [Ca 1893]. We hope that such approach
will be useful for the solution of the problem of -dimensional top.Comment: LaTeX, 9 page
On integration of the Kowalevski gyrostat and the Clebsch problems
For the Kowalevski gyrostat change of variables similar to that of the
Kowalevski top is done. We establish one to one correspondence between the
Kowalevski gyrostat and the Clebsch system and demonstrate that Kowalevski
variables for the gyrostat practically coincide with elliptic coordinates on
sphere for the Clebsch case. Equivalence of considered integrable systems
allows to construct two Lax matrices for the gyrostat using known rational and
elliptic Lax matrices for the Clebsch model. Associated with these matrices
solutions of the Clebsch system and, therefore, of the Kowalevski gyrostat
problem are discussed. The Kotter solution of the Clebsch system in modern
notation is presented in detail.Comment: LaTeX, 24 page
Discovering universal statistical laws of complex networks
Different network models have been suggested for the topology underlying
complex interactions in natural systems. These models are aimed at replicating
specific statistical features encountered in real-world networks. However, it
is rarely considered to which degree the results obtained for one particular
network class can be extrapolated to real-world networks. We address this issue
by comparing different classical and more recently developed network models
with respect to their generalisation power, which we identify with large
structural variability and absence of constraints imposed by the construction
scheme. After having identified the most variable networks, we address the
issue of which constraints are common to all network classes and are thus
suitable candidates for being generic statistical laws of complex networks. In
fact, we find that generic, not model-related dependencies between different
network characteristics do exist. This allows, for instance, to infer global
features from local ones using regression models trained on networks with high
generalisation power. Our results confirm and extend previous findings
regarding the synchronisation properties of neural networks. Our method seems
especially relevant for large networks, which are difficult to map completely,
like the neural networks in the brain. The structure of such large networks
cannot be fully sampled with the present technology. Our approach provides a
method to estimate global properties of under-sampled networks with good
approximation. Finally, we demonstrate on three different data sets (C.
elegans' neuronal network, R. prowazekii's metabolic network, and a network of
synonyms extracted from Roget's Thesaurus) that real-world networks have
statistical relations compatible with those obtained using regression models
Status of the GEO600 gravitational wave detector
The GEO600 laser interferometric gravitational wave detector is approaching the end of its commissioning phase which started in 1995.During a test run in January 2002 the detector was operated for 15 days in a power-recycled michelson configuration. The detector and environmental data which were acquired during this test run were used to test the data analysis code. This paper describes the subsystems of GEO600, the status of the detector by August 2002 and the plans towards the first science run
An Algebraic Approach for Decoding Spread Codes
In this paper we study spread codes: a family of constant-dimension codes for
random linear network coding. In other words, the codewords are full-rank
matrices of size (k x n) with entries in a finite field F_q. Spread codes are a
family of optimal codes with maximal minimum distance. We give a
minimum-distance decoding algorithm which requires O((n-k)k^3) operations over
an extension field F_{q^k}. Our algorithm is more efficient than the previous
ones in the literature, when the dimension k of the codewords is small with
respect to n. The decoding algorithm takes advantage of the algebraic structure
of the code, and it uses original results on minors of a matrix and on the
factorization of polynomials over finite fields
Identification and Classification of Hubs in Brain Networks
Brain regions in the mammalian cerebral cortex are linked by a complex network of fiber bundles. These inter-regional networks have previously been analyzed in terms of their node degree, structural motif, path length and clustering coefficient distributions. In this paper we focus on the identification and classification of hub regions, which are thought to play pivotal roles in the coordination of information flow. We identify hubs and characterize their network contributions by examining motif fingerprints and centrality indices for all regions within the cerebral cortices of both the cat and the macaque. Motif fingerprints capture the statistics of local connection patterns, while measures of centrality identify regions that lie on many of the shortest paths between parts of the network. Within both cat and macaque networks, we find that a combination of degree, motif participation, betweenness centrality and closeness centrality allows for reliable identification of hub regions, many of which have previously been functionally classified as polysensory or multimodal. We then classify hubs as either provincial (intra-cluster) hubs or connector (inter-cluster) hubs, and proceed to show that lesioning hubs of each type from the network produces opposite effects on the small-world index. Our study presents an approach to the identification and classification of putative hub regions in brain networks on the basis of multiple network attributes and charts potential links between the structural embedding of such regions and their functional roles
Integrable systems on the sphere associated with genus three algebraic curves
New variables of separation for few integrable systems on the two-dimensional
sphere with higher order integrals of motion are considered in detail. We
explicitly describe canonical transformations of initial physical variables to
the variables of separation and vice versa, calculate the corresponding
quadratures and discuss some possible integrable deformations of initial
systems.Comment: 19 pages, LaTeX with AMS font
Setting upper limits on the strength of periodic gravitational waves from PSR J1939+2134 using the first science data from the GEO 600 and LIGO detectors
Data collected by the GEO 600 and LIGO interferometric gravitational wave detectors during their first observational science run were searched for continuous gravitational waves from the pulsar J1939+2134 at twice its rotation frequency. Two independent analysis methods were used and are demonstrated in this paper: a frequency domain method and a time domain method. Both achieve consistent null results, placing new upper limits on the strength of the pulsar's gravitational wave emission. A model emission mechanism is used to interpret the limits as a constraint on the pulsar's equatorial ellipticity
Analysis of LIGO data for gravitational waves from binary neutron stars
We report on a search for gravitational waves from coalescing compact binary
systems in the Milky Way and the Magellanic Clouds. The analysis uses data
taken by two of the three LIGO interferometers during the first LIGO science
run and illustrates a method of setting upper limits on inspiral event rates
using interferometer data. The analysis pipeline is described with particular
attention to data selection and coincidence between the two interferometers. We
establish an observational upper limit of 1.7 \times 10^{2}M_\odot$.Comment: 17 pages, 9 figure
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