2,385 research outputs found
Resonant structures based on amorphous silicon sub-oxide doped with Er3+ with silicon nanoclusters for an efficient emission at 1550 nm
We present a resonant approach to enhance 1550nm emission efficiency of
amorphous silicon sub-oxide doped with Er3+ (a-SiOx) layers with silicon
nanoclusters (Si-NC). Two distinct techniques were combined to provide a
structure that allowed increasing approximately 12x the 1550nm emission. First,
layers of SiO2 were obtained by conventional wet oxidation and a-SiOx
matrix was deposited by reactive RF co-sputtering. Secondly, an extra pump
channel (4I15/2 to 4I9/2) of Er3+ was created due to Si-NC formation on the
same a-SiOx matrix via a hard annealing at 1150 C. The SiO2 and the
a-SiOx thicknesses were designed to support resonances near the pumping
wavelength (~500nm), near the Si-NC emission (~800nm) and near the a-SiOx
emission (~1550nm) enhancing the optical pumping process.Comment: 14 pages, 4 figures, in submissio
Bayesian parameter estimation in the second LISA Pathfinder Mock Data Challenge
A main scientific output of the LISA Pathfinder mission is to provide a noise
model that can be extended to the future gravitational wave observatory, LISA.
The success of the mission depends thus upon a deep understanding of the
instrument, especially the ability to correctly determine the parameters of the
underlying noise model. In this work we estimate the parameters of a simplified
model of the LISA Technology Package (LTP) instrument. We describe the LTP by
means of a closed-loop model that is used to generate the data, both injected
signals and noise. Then, parameters are estimated using a Bayesian framework
and it is shown that this method reaches the optimal attainable error, the
Cramer-Rao bound. We also address an important issue for the mission: how to
efficiently combine the results of different experiments to obtain a unique set
of parameters describing the instrument.Comment: 14 pages, 4 figures, submitted to PR
Time domain maximum likelihood parameter estimation in LISA Pathfinder Data Analysis
LISA is the upcoming space-based Gravitational Wave telescope. LISA
Pathfinder, to be launched in the coming years, will prove and verify the
detection principle of the fundamental Doppler link of LISA on a flight
hardware identical in design to that of LISA. LISA Pathfinder will collect a
picture of all noise disturbances possibly affecting LISA, achieving the
unprecedented pureness of geodesic motion necessary for the detection of
gravitational waves. The first steps of both missions will crucially depend on
a very precise calibration of the key system parameters. Moreover, robust
parameters estimation is of fundamental importance in the correct assessment of
the residual force noise, an essential part of the data processing for LISA. In
this paper we present a maximum likelihood parameter estimation technique in
time domain being devised for this calibration and show its proficiency on
simulated data and validation through Monte Carlo realizations of independent
noise runs. We discuss its robustness to non-standard scenarios possibly
arising during the real-life mission, as well as its independence to the
initial guess and non-gaussianities. Furthermore, we apply the same technique
to data produced in mission-like fashion during operational exercises with a
realistic simulator provided by ESA.Comment: 16 pages (two columns), 15 figures, 5 tables, submitted to Phys. Rev.
Local Isometric immersions of pseudo-spherical surfaces and evolution equations
The class of differential equations describing pseudo-spherical surfaces,
first introduced by Chern and Tenenblat [3], is characterized by the property
that to each solution of a differential equation, within the class, there
corresponds a 2-dimensional Riemannian metric of curvature equal to . The
class of differential equations describing pseudo-spherical surfaces carries
close ties to the property of complete integrability, as manifested by the
existence of infinite hierarchies of conservation laws and associated linear
problems. As such, it contains many important known examples of integrable
equations, like the sine-Gordon, Liouville and KdV equations. It also gives
rise to many new families of integrable equations. The question we address in
this paper concerns the local isometric immersion of pseudo-spherical surfaces
in from the perspective of the differential equations that give
rise to the metrics. Indeed, a classical theorem in the differential geometry
of surfaces states that any pseudo-spherical surface can be locally
isometrically immersed in . In the case of the sine-Gordon
equation, one can derive an expression for the second fundamental form of the
immersion that depends only on a jet of finite order of the solution of the
pde. A natural question is to know if this remarkable property extends to
equations other than the sine-Gordon equation within the class of differential
equations describing pseudo-spherical surfaces. In an earlier paper [11], we
have shown that this property fails to hold for all other second order
equations, except for those belonging to a very special class of evolution
equations. In the present paper, we consider a class of evolution equations for
of order describing pseudo-spherical surfaces. We show that
whenever an isometric immersion in exists, depending on a jet of
finite order of , then the coefficients of the second fundamental forms are
functions of the independent variables and only.Comment: Fields Institute Communications, 2015, Hamiltonian PDEs and
Applications, pp.N
Parameter estimation in LISA Pathfinder operational exercises
The LISA Pathfinder data analysis team has been developing in the last years
the infrastructure and methods required to run the mission during flight
operations. These are gathered in the LTPDA toolbox, an object oriented MATLAB
toolbox that allows all the data analysis functionalities for the mission,
while storing the history of all operations performed to the data, thus easing
traceability and reproducibility of the analysis. The parameter estimation
methods in the toolbox have been applied recently to data sets generated with
the OSE (Off-line Simulations Environment), a detailed LISA Pathfinder
non-linear simulator that will serve as a reference simulator during mission
operations. These operational exercises aim at testing the on-orbit experiments
in a realistic environment in terms of software and time constraints. These
simulations, so called operational exercises, are the last verification step
before translating these experiments into tele-command sequences for the
spacecraft, producing therefore very relevant datasets to test our data
analysis methods. In this contribution we report the results obtained with
three different parameter estimation methods during one of these operational
exercises.Comment: 10 pages, 3 figures, prepared for the Proceedings of the 9th Edoardo
Amaldi Conference on Gravitational Waves, JPC
Nonlocal aspects of -symmetries and ODEs reduction
A reduction method of ODEs not possessing Lie point symmetries makes use of
the so called -symmetries (C. Muriel and J. L. Romero, \emph{IMA J.
Appl. Math.} \textbf{66}, 111-125, 2001). The notion of covering for an ODE
is used here to recover -symmetries of as
nonlocal symmetries. In this framework, by embedding into a
suitable system determined by the function ,
any -symmetry of can be recovered by a local symmetry of
. As a consequence, the reduction method of Muriel and
Romero follows from the standard method of reduction by differential invariants
applied to .Comment: 13 page
From Uterus to Brain: An Update on Epidemiology, Clinical Features, and Treatment of Brain Metastases From Gestational Trophoblastic Neoplasia
In this review, we provide the state of the art about brain metastases (BMs) from gestational trophoblastic neoplasia (GTN), a rare condition. Data concerning the epidemiology, clinical presentation, innovations in therapeutic modalities, and outcomes of GTN BMs are comprehensively presented with particular attention to the role of radiotherapy, neurosurgery, and the most recent chemotherapy regimens. Good response rates have been achieved thanks to multi-agent chemotherapy, but brain involvement by GTNs entails significant risks for patients’ health since sudden and extensive intracranial hemorrhages are possible. Moreover, despite the evolution of treatment protocols, a small proportion of these patients ultimately develops a resistant disease. To tackle this unmet clinical need, immunotherapy has been recently proposed. The role of this novel option for this subset of patients as well as the achieved results so far are also discussed
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