1,947 research outputs found
Efficient chaining of seeds in ordered trees
We consider here the problem of chaining seeds in ordered trees. Seeds are
mappings between two trees Q and T and a chain is a subset of non overlapping
seeds that is consistent with respect to postfix order and ancestrality. This
problem is a natural extension of a similar problem for sequences, and has
applications in computational biology, such as mining a database of RNA
secondary structures. For the chaining problem with a set of m constant size
seeds, we describe an algorithm with complexity O(m2 log(m)) in time and O(m2)
in space
Theory of proximity effect in superconductor/ferromagnet heterostructures
We present a microscopic theory of proximity effect in the
ferromagnet/superconductor/ferromagnet (F/S/F) nanostructures where S is s-wave
low-T_c superconductor and F's are layers of 3d transition ferromagnetic metal.
Our approach is based on the solution of Gor'kov equations for the normal and
anomalous Green's functions together with a self-consistent evaluation of the
superconducting order parameter. We take into account the elastic
spin-conserving scattering of the electrons assuming s-wave scattering in the S
layer and s-d scattering in the F layers. In accordance with the previous
quasiclassical theories, we found that due to exchange field in the ferromagnet
the anomalous Green's function F(z) exhibits the damping oscillations in the
F-layer as a function of distance z from the S/F interface. In the given model
a half of period of oscillations is determined by the length \xi_m^0 = \pi
v_F/E_ex, where v_F is the Fermi velocity and E_ex is the exchange field, while
damping is governed by the length l_0 = (1/l_{\uparrow} +
1/l_{\downarrow})^{-1} with l_{\uparrow} and l_{\downarrow} being
spin-dependent mean free paths in the ferromagnet. The superconducting
transition temperature T_c(d_F) of the F/S/F trilayer shows the damping
oscillations as a function of the F-layer thickness d_F with period \xi_F =
\pi/\sqrt{m E_ex}, where m is the effective electron mass. We show that strong
spin-conserving scattering either in the superconductor or in the ferromagnet
significantly suppresses these oscillations. The calculated T_c(d_F)
dependences are compared with existing experimental data for Fe/Nb/Fe trilayers
and Nb/Co multilayers.Comment: 13 pages, REVTeX4, 8 PS-figures; improved version, submitted to PR
Hard axis magnetization behavior and the surface spin flop transition in antiferromagnetic Fe Cr 100 superlattices
Uniform random generation of large acyclic digraphs
Directed acyclic graphs are the basic representation of the structure
underlying Bayesian networks, which represent multivariate probability
distributions. In many practical applications, such as the reverse engineering
of gene regulatory networks, not only the estimation of model parameters but
the reconstruction of the structure itself is of great interest. As well as for
the assessment of different structure learning algorithms in simulation
studies, a uniform sample from the space of directed acyclic graphs is required
to evaluate the prevalence of certain structural features. Here we analyse how
to sample acyclic digraphs uniformly at random through recursive enumeration,
an approach previously thought too computationally involved. Based on
complexity considerations, we discuss in particular how the enumeration
directly provides an exact method, which avoids the convergence issues of the
alternative Markov chain methods and is actually computationally much faster.
The limiting behaviour of the distribution of acyclic digraphs then allows us
to sample arbitrarily large graphs. Building on the ideas of recursive
enumeration based sampling we also introduce a novel hybrid Markov chain with
much faster convergence than current alternatives while still being easy to
adapt to various restrictions. Finally we discuss how to include such
restrictions in the combinatorial enumeration and the new hybrid Markov chain
method for efficient uniform sampling of the corresponding graphs.Comment: 15 pages, 2 figures. To appear in Statistics and Computin
Absence of First-order Transition and Tri-critical Point in the Dynamic Phase Diagram of a Spatially Extended Bistable System in an Oscillating Field
It has been well established that spatially extended, bistable systems that
are driven by an oscillating field exhibit a nonequilibrium dynamic phase
transition (DPT). The DPT occurs when the field frequency is on the order of
the inverse of an intrinsic lifetime associated with the transitions between
the two stable states in a static field of the same magnitude as the amplitude
of the oscillating field. The DPT is continuous and belongs to the same
universality class as the equilibrium phase transition of the Ising model in
zero field [G. Korniss et al., Phys. Rev. E 63, 016120 (2001); H. Fujisaka et
al., Phys. Rev. E 63, 036109 (2001)]. However, it has previously been claimed
that the DPT becomes discontinuous at temperatures below a tricritical point
[M. Acharyya, Phys. Rev. E 59, 218 (1999)]. This claim was based on
observations in dynamic Monte Carlo simulations of a multipeaked probability
density for the dynamic order parameter and negative values of the fourth-order
cumulant ratio. Both phenomena can be characteristic of discontinuous phase
transitions. Here we use classical nucleation theory for the decay of
metastable phases, together with data from large-scale dynamic Monte Carlo
simulations of a two-dimensional kinetic Ising ferromagnet, to show that these
observations in this case are merely finite-size effects. For sufficiently
small systems and low temperatures, the continuous DPT is replaced, not by a
discontinuous phase transition, but by a crossover to stochastic resonance. In
the infinite-system limit the stochastic-resonance regime vanishes, and the
continuous DPT should persist for all nonzero temperatures
Robust Henderson III estimators of variance components in the nested error model
Common methods for estimating variance components in Linear Mixed Models include Maximum Likelihood (ML) and Restricted Maximum Likelihood (REML). These methods are based on the strong assumption of multivariate normal distribution and it is well know that they are very sensitive to outlying observations with respect to any of the random components. Several robust altematives of these methods have been proposed (e.g. Fellner 1986, Richardson and Welsh 1995). In this work we present several robust alternatives based on the Henderson method III which do not rely on the normality assumption and provide explicit solutions for the variance components estimators. These estimators can later be used to derive robust estimators of regression coefficients. Finally, we describe an application of this procedure to small area estimation, in which the main target is the estimation of the means of areas or domains when the within-area sample sizes are small
Local density of states in superconductor-strong ferromagnet structures
We study the dependence of the local density of states (LDOS) on coordinates
for a superconductor-ferromagnet (S/F) bilayer and a S/F/S structure assuming
that the exchange energy h in the ferromagnet is sufficiently large: where is the elastic relaxation time. This limit cannot be
described by the Usadel equation and we solve the more general Eilenberger
equation. We demonstrate that, in the main approximation in the parameter , the proximity effect does not lead to a modification of the LDOS
in the S/F system and a non-trivial dependence on coordinates shows up in next
orders in In the S/F/S sandwich the correction to the LDOS is
nonzero in the main approximation and depends on the phase difference between
the superconductors. We also calculate the superconducting critical temperature
for the bilayered system and show that it does not depend on the
exchange energy of the ferromagnet in the limit of large h and a thick F layer.Comment: 9 pages, 5 figure
A Complete Set of In-plane Spin-transfer Coefficients for Small Angle pp Elastic Scattering at 200 MeV
This research was sponsored by the National Science Foundation Grant NSF PHY-931478
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