19,814 research outputs found
Neutral heavy lepton production at next high energy linear colliders
The discovery potential for detecting new heavy Majorana and Dirac neutrinos
at some recently proposed high energy colliders is discussed. These
new particles are suggested by grand unified theories and superstring-inspired
models. For these models the production of a single heavy neutrino is shown to
be more relevant than pair production when comparing cross sections and
neutrino mass ranges.
The process is calculated
including on-shell and off-shell heavy neutrino effects.
We present a detailed study of cross sections and distributions that shows a
clear separation between the signal and standard model contributions, even
after including hadronization effects.Comment: 4 pages including 15 figures, 1 table. RevTex. Accepted in Physical
Review
Generalized Euler-Lagrange equations for variational problems with scale derivatives
We obtain several Euler-Lagrange equations for variational functionals
defined on a set of H\"older curves. The cases when the Lagrangian contains
multiple scale derivatives, depends on a parameter, or contains higher-order
scale derivatives are considered.Comment: Submitted on 03-Aug-2009; accepted for publication 16-March-2010; in
"Letters in Mathematical Physics"
Diluted antiferromagnet in a ferromagnetic enviroment
The question of robustness of a network under random ``attacks'' is treated
in the framework of critical phenomena. The persistence of spontaneous
magnetization of a ferromagnetic system to the random inclusion of
antiferromagnetic interactions is investigated. After examing the static
properties of the quenched version (in respect to the random antiferromagnetic
interactions) of the model, the persistence of the magnetization is analysed
also in the annealed approximation, and the difference in the results are
discussed
Physical properties of the Schur complement of local covariance matrices
General properties of global covariance matrices representing bipartite
Gaussian states can be decomposed into properties of local covariance matrices
and their Schur complements. We demonstrate that given a bipartite Gaussian
state described by a covariance matrix \textbf{V}, the
Schur complement of a local covariance submatrix of it can be
interpreted as a new covariance matrix representing a Gaussian operator of
party 1 conditioned to local parity measurements on party 2. The connection
with a partial parity measurement over a bipartite quantum state and the
determination of the reduced Wigner function is given and an operational
process of parity measurement is developed. Generalization of this procedure to
a -partite Gaussian state is given and it is demonstrated that the
system state conditioned to a partial parity projection is given by a
covariance matrix such as its block elements are Schur complements
of special local matrices.Comment: 10 pages. Replaced with final published versio
Spin-glass behaviour on random lattices
The ground-state phase diagram of an Ising spin-glass model on a random graph
with an arbitrary fraction of ferromagnetic interactions is analysed in the
presence of an external field. Using the replica method, and performing an
analysis of stability of the replica-symmetric solution, it is shown that
, correponding to an unbiased spin glass, is a singular point in the
phase diagram, separating a region with a spin-glass phase () from a
region with spin-glass, ferromagnetic, mixed, and paramagnetic phases
()
Recording from two neurons: second order stimulus reconstruction from spike trains and population coding
We study the reconstruction of visual stimuli from spike trains, recording
simultaneously from the two H1 neurons located in the lobula plate of the fly
Chrysomya megacephala. The fly views two types of stimuli, corresponding to
rotational and translational displacements. If the reconstructed stimulus is to
be represented by a Volterra series and correlations between spikes are to be
taken into account, first order expansions are insufficient and we have to go
to second order, at least. In this case higher order correlation functions have
to be manipulated, whose size may become prohibitively large. We therefore
develop a Gaussian-like representation for fourth order correlation functions,
which works exceedingly well in the case of the fly. The reconstructions using
this Gaussian-like representation are very similar to the reconstructions using
the experimental correlation functions. The overall contribution to rotational
stimulus reconstruction of the second order kernels - measured by a chi-squared
averaged over the whole experiment - is only about 8% of the first order
contribution. Yet if we introduce an instant-dependent chi-square to measure
the contribution of second order kernels at special events, we observe an up to
100% improvement. As may be expected, for translational stimuli the
reconstructions are rather poor. The Gaussian-like representation could be a
valuable aid in population coding with large number of neurons
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