7,274 research outputs found
Neural networks for gamma-hadron separation in MAGIC
Neural networks have proved to be versatile and robust for particle
separation in many experiments related to particle astrophysics. We apply these
techniques to separate gamma rays from hadrons for the MAGIC Cerenkov
Telescope. Two types of neural network architectures have been used for the
classi cation task: one is the MultiLayer Perceptron (MLP) based on supervised
learning, and the other is the Self-Organising Tree Algorithm (SOTA), which is
based on unsupervised learning. We propose a new architecture by combining
these two neural networks types to yield better and faster classi cation
results for our classi cation problem.Comment: 6 pages, 4 figures, to be published in the Proceedings of the 6th
International Symposium ''Frontiers of Fundamental and Computational
Physics'' (FFP6), Udine (Italy), Sep. 26-29, 200
Asymptotic effects of boundary perturbations in excitable systems
A Neumann problem in the strip for the Fitzhugh Nagumo system is consid-
ered. The transformation in a non linear integral equation permits to deduce a
priori estimates for the solution. A complete asymptotic analysis shows that
for large t the effects of the initial data vanish while the effects of bound-
ary disturbances depend on the properties of the data. When they are convergent
for large t, the solution is everywhere bounded; when theirs first derivatives
belong to L one too, the effects are vanishing
Analytical probabilistic approach to the ground state of lattice quantum systems: exact results in terms of a cumulant expansion
We present a large deviation analysis of a recently proposed probabilistic
approach to the study of the ground-state properties of lattice quantum
systems. The ground-state energy, as well as the correlation functions in the
ground state, are exactly determined as a series expansion in the cumulants of
the multiplicities of the potential and hopping energies assumed by the system
during its long-time evolution. Once these cumulants are known, even at a
finite order, our approach provides the ground state analytically as a function
of the Hamiltonian parameters. A scenario of possible applications of this
analyticity property is discussed.Comment: 26 pages, 5 figure
Euler Polynomials and Identities for Non-Commutative Operators
Three kinds of identities involving non-commutating operators and Euler and
Bernoulli polynomials are studied. The first identity, as given by Bender and
Bettencourt, expresses the nested commutator of the Hamiltonian and momentum
operators as the commutator of the momentum and the shifted Euler polynomial of
the Hamiltonian. The second one, due to J.-C. Pain, links the commutators and
anti-commutators of the monomials of the position and momentum operators. The
third appears in a work by Figuieira de Morisson and Fring in the context of
non-Hermitian Hamiltonian systems. In each case, we provide several proofs and
extensions of these identities that highlight the role of Euler and Bernoulli
polynomials.Comment: 20 page
Comparison of Theory and Direct Numerical Simulations of Drag Reduction by Rodlike Polymers in Turbulent Channel Flows
Numerical simulations of turbulent channel flows, with or without additives,
are limited in the extent of the Reynolds number \Re and Deborah number \De.
The comparison of such simulations to theories of drag reduction, which are
usually derived for asymptotically high \Re and \De, calls for some care. In
this paper we present a study of drag reduction by rodlike polymers in a
turbulent channel flow using direct numerical simulation and illustrate how
these numerical results should be related to the recently developed theory
Self-Organising Networks for Classification: developing Applications to Science Analysis for Astroparticle Physics
Physics analysis in astroparticle experiments requires the capability of
recognizing new phenomena; in order to establish what is new, it is important
to develop tools for automatic classification, able to compare the final result
with data from different detectors. A typical example is the problem of Gamma
Ray Burst detection, classification, and possible association to known sources:
for this task physicists will need in the next years tools to associate data
from optical databases, from satellite experiments (EGRET, GLAST), and from
Cherenkov telescopes (MAGIC, HESS, CANGAROO, VERITAS)
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