46,532 research outputs found
Prediction of signalâtoânoise ratio gain for passive higherâorder correlation detection of energy transients
In general, higherâorder correlation detectors perform well in passive detection for signals of high thirdâ and fourthâorder moments. Previous studies by the authors have shown that the normalized thirdâ and fourthâorder signal moments are reliable indicators of higherâorder correlation detector performance [Pflug et al. (1992b)]. For a deterministic energy transient of known moments through fourth order, it is possible to predict theoretically the amount of gain over an ordinary crossâcorrelation detector for a bicorrelation or tricorrelation detector applied in a noise environment of known variance. In this paper, formulas that predict detector performance for passive detection at the minimum detectable level are derived. The noise is assumed to be stationary and zero mean with Gaussian correlation central ordinate probability density functions. To test the formulas, SNR detection and gain curves are generated using hypothesis testing and Monte Carlo simulations on a set of test signals. The test signals are created by varying the time width of a pulseâlike signal in a sampling window of fixed time duration, resulting in a set of test signals with varying signal moments. Good agreement is found between the simulated and theoretical results. The effects of observation time (length of detection window) and sampling interval on detector performance are also discussed and illustrated with computer simulations. The prediction formulas indicate that decreasing the observation time or the sampling interval (assuming the signal is sufficiently sampled and the detection window contains the entire signal) improves detection performance. However, the rate of improvement is different for the three detectors. The SNR required to achieve the minimum detectable level of detection performance at a given probability of false alarm (Pfa) decreases with the fourth root of the observation time and sampling interval for the crossâcorrelation detector, the sixth root for the bicorrelation detector, and the eighth root for the tricorrelation detector. Relative detector performance also varies with Pfa. The probability of detection (Pd) for higherâorder detectors degrades less rapidly with decreasing Pfa than the Pd for ordinary correlations. Thus higherâorder correlators can be especially appropriate when a very low Pfa is required
Dynamic effects in nonlinear magneto-optics of atoms and molecules
A brief review is given of topics relating to dynamical processes arising in
nonlinear interactions between light and resonant systems (atoms or molecules)
in the presence of a magnetic field.Comment: 15 pages, 11 figure
X-Ray Detection of Transient Magnetic Moments Induced by a Spin Current in Cu
We have used a MHz lock-in x-ray spectro-microscopy technique to directly
detect changes of magnetic moments in Cu due to spin injection from an adjacent
Co layer. The elemental and chemical specificity of x-rays allows us to
distinguish two spin current induced effects. We detect the creation of
transient magnetic moments of on Cu atoms
within the bulk of the 28 nm thick Cu film due to spin-accumulation. The moment
value is compared to predictions by Mott's two current model. We also observe
that the hybridization induced existing magnetic moments on Cu interface atoms
are transiently increased by about 10% or .
This reveals the dominance of spin-torque alignment over Joule heat induced
disorder of the interfacial Cu moments during current flow
Anisotropic relaxation in NADH excited states studied by polarization-modulation pump-probe transient spectroscopy
We present the results of experimental and theoretical studies of fast
anisotropic relaxation and rotational diffusion in the first electron excited
state of biological coenzyme NADH in water-ethanol solutions. The experiments
have been carried out by means of a novel polarization-modulation transient
method and fluorescence polarization spectroscopy. For interpretation of the
experimental results a model of the anisotropic relaxation in terms of scalar
and vector properties of transition dipole moments and based on the
Born-Oppenheimer approximation has been developed. The results obtained suggest
that the dynamics of anisotropic rovibronic relaxation in NADH under excitation
with 100~fs pump laser pulses can be characterised by a single vibration
relaxation time laying in the range 2--15~ps and a single rotation
diffusion time laying in the range 100--450~ps a subject of ethanol
concentration. The dependence of the times and on the
solution polarity (static permittivity) and viscosity has been determined and
analyzed. Limiting values of an important parameter describing the rotation of the transition dipole
moment in the course of vibrational relaxation has been determined from
experiment as function of the ethanol concentration and analyzed.Comment: 14 pages, 13 figure
A learning approach to the detection of gravitational wave transients
We investigate the class of quadratic detectors (i.e., the statistic is a
bilinear function of the data) for the detection of poorly modeled
gravitational transients of short duration. We point out that all such
detection methods are equivalent to passing the signal through a filter bank
and linearly combine the output energy. Existing methods for the choice of the
filter bank and of the weight parameters rely essentially on the two following
ideas: (i) the use of the likelihood function based on a (possibly
non-informative) statistical model of the signal and the noise, (ii) the use of
Monte-Carlo simulations for the tuning of parametric filters to get the best
detection probability keeping fixed the false alarm rate. We propose a third
approach according to which the filter bank is "learned" from a set of training
data. By-products of this viewpoint are that, contrarily to previous methods,
(i) there is no requirement of an explicit description of the probability
density function of the data when the signal is present and (ii) the filters we
use are non-parametric. The learning procedure may be described as a two step
process: first, estimate the mean and covariance of the signal with the
training data; second, find the filters which maximize a contrast criterion
referred to as deflection between the "noise only" and "signal+noise"
hypothesis. The deflection is homogeneous to the signal-to-noise ratio and it
uses the quantities estimated at the first step. We apply this original method
to the problem of the detection of supernovae core collapses. We use the
catalog of waveforms provided recently by Dimmelmeier et al. to train our
algorithm. We expect such detector to have better performances on this
particular problem provided that the reference signals are reliable.Comment: 22 pages, 4 figure
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