668 research outputs found
On the CP-odd Nucleon Potential
The CP-odd nucleon potential for different models of CP violation in the one
meson exchange approximation is studied. It is shown that the main contribution
is due to the -meson exchange which leads to a simple one parameter CP-odd
nucleon potential.Comment: 12 pages, RevTex, UM-P-92/114, OZ-92/3
Parametric resonance enhancement in neutron interferometry and application for the search for non-Newtonian gravity
The parametric resonance enhancement of the phase of neutrons due to non-Newtonian anomalous gravitationis considered. The existence of such resonances is confirmed by numerical calculations. A possible experimentalscheme for observing this effect is discussed based on an existing neutron interferometer design
Beyond Moore's technologies: operation principles of a superconductor alternative
The predictions of Moore's law are considered by experts to be valid until
2020 giving rise to "post-Moore's" technologies afterwards. Energy efficiency
is one of the major challenges in high-performance computing that should be
answered. Superconductor digital technology is a promising post-Moore's
alternative for the development of supercomputers. In this paper, we consider
operation principles of an energy-efficient superconductor logic and memory
circuits with a short retrospective review of their evolution. We analyze their
shortcomings in respect to computer circuits design. Possible ways of further
research are outlined.Comment: OPEN ACCES
Multiresolution community detection for megascale networks by information-based replica correlations
We use a Potts model community detection algorithm to accurately and
quantitatively evaluate the hierarchical or multiresolution structure of a
graph. Our multiresolution algorithm calculates correlations among multiple
copies ("replicas") of the same graph over a range of resolutions. Significant
multiresolution structures are identified by strongly correlated replicas. The
average normalized mutual information, the variation of information, and other
measures in principle give a quantitative estimate of the "best" resolutions
and indicate the relative strength of the structures in the graph. Because the
method is based on information comparisons, it can in principle be used with
any community detection model that can examine multiple resolutions. Our
approach may be extended to other optimization problems. As a local measure,
our Potts model avoids the "resolution limit" that affects other popular
models. With this model, our community detection algorithm has an accuracy that
ranks among the best of currently available methods. Using it, we can examine
graphs over 40 million nodes and more than one billion edges. We further report
that the multiresolution variant of our algorithm can solve systems of at least
200000 nodes and 10 million edges on a single processor with exceptionally high
accuracy. For typical cases, we find a super-linear scaling, O(L^{1.3}) for
community detection and O(L^{1.3} log N) for the multiresolution algorithm
where L is the number of edges and N is the number of nodes in the system.Comment: 19 pages, 14 figures, published version with minor change
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