2,504 research outputs found
Calibrating spectral estimation for the LISA Technology Package with multichannel synthetic noise generation
The scientific objectives of the Lisa Technology Package (LTP) experiment, on
board of the LISA Pathfinder mission, demand for an accurate calibration and
validation of the data analysis tools in advance of the mission launch. The
levels of confidence required on the mission outcomes can be reached only with
an intense activity on synthetically generated data. A flexible procedure
allowing the generation of cross-correlated stationary noise time series was
set-up. Multi-channel time series with the desired cross correlation behavior
can be generated once a model for a multichannel cross-spectral matrix is
provided. The core of the procedure is the synthesis of a noise coloring
multichannel filter through a frequency-by-frequency eigendecomposition of the
model cross-spectral matrix and a Z-domain fit. The common problem of initial
transients in noise time series is solved with a proper initialization of the
filter recursive equations. The noise generator performances were tested in a
two dimensional case study of the LTP dynamics along the two principal channels
of the sensing interferometer.Comment: Accepted for publication in Physical Review D (http://prd.aps.org/
Best chirplet chain: near-optimal detection of gravitational wave chirps
The list of putative sources of gravitational waves possibly detected by the
ongoing worldwide network of large scale interferometers has been continuously
growing in the last years. For some of them, the detection is made difficult by
the lack of a complete information about the expected signal. We concentrate on
the case where the expected GW is a quasi-periodic frequency modulated signal
i.e., a chirp. In this article, we address the question of detecting an a
priori unknown GW chirp. We introduce a general chirp model and claim that it
includes all physically realistic GW chirps. We produce a finite grid of
template waveforms which samples the resulting set of possible chirps. If we
follow the classical approach (used for the detection of inspiralling binary
chirps, for instance), we would build a bank of quadrature matched filters
comparing the data to each of the templates of this grid. The detection would
then be achieved by thresholding the output, the maximum giving the individual
which best fits the data. In the present case, this exhaustive search is not
tractable because of the very large number of templates in the grid. We show
that the exhaustive search can be reformulated (using approximations) as a
pattern search in the time-frequency plane. This motivates an approximate but
feasible alternative solution which is clearly linked to the optimal one.
[abridged version of the abstract]Comment: 23 pages, 9 figures. Accepted for publication in Phys. Rev D Some
typos corrected and changes made according to referee's comment
Ripple oscillations in the left temporal neocortex are associated with impaired verbal episodic memory encoding
Background: We sought to determine if ripple oscillations (80-120Hz),
detected in intracranial EEG (iEEG) recordings of epilepsy patients, correlate
with an enhancement or disruption of verbal episodic memory encoding. Methods:
We defined ripple and spike events in depth iEEG recordings during list
learning in 107 patients with focal epilepsy. We used logistic regression
models (LRMs) to investigate the relationship between the occurrence of ripple
and spike events during word presentation and the odds of successful word
recall following a distractor epoch, and included the seizure onset zone (SOZ)
as a covariate in the LRMs. Results: We detected events during 58,312 word
presentation trials from 7,630 unique electrode sites. The probability of
ripple on spike (RonS) events was increased in the seizure onset zone (SOZ,
p<0.04). In the left temporal neocortex RonS events during word presentation
corresponded with a decrease in the odds ratio (OR) of successful recall,
however this effect only met significance in the SOZ (OR of word recall 0.71,
95% CI: 0.59-0.85, n=158 events, adaptive Hochberg p<0.01). Ripple on
oscillation events (RonO) that occurred in the left temporal neocortex non-SOZ
also correlated with decreased odds of successful recall (OR 0.52, 95% CI:
0.34-0.80, n=140, adaptive Hochberg , p<0.01). Spikes and RonS that occurred
during word presentation in the left middle temporal gyrus during word
presentation correlated with the most significant decrease in the odds of
successful recall, irrespective of the location of the SOZ (adaptive Hochberg,
p<0.01). Conclusion: Ripples and spikes generated in left temporal neocortex
are associated with impaired verbal episodic memory encoding
Accurate estimators of power spectra in N-body simulations
abridged] A method to rapidly estimate the Fourier power spectrum of a point
distribution is presented. This method relies on a Taylor expansion of the
trigonometric functions. It yields the Fourier modes from a number of FFTs,
which is controlled by the order N of the expansion and by the dimension D of
the system. In three dimensions, for the practical value N=3, the number of
FFTs required is 20. We apply the method to the measurement of the power
spectrum of a periodic point distribution that is a local Poisson realization
of an underlying stationary field. We derive explicit analytic expression for
the spectrum, which allows us to quantify--and correct for--the biases induced
by discreteness and by the truncation of the Taylor expansion, and to bound the
unknown effects of aliasing of the power spectrum. We show that these aliasing
effects decrease rapidly with the order N. The only remaining significant
source of errors is reduced to the unavoidable cosmic/sample variance due to
the finite size of the sample. The analytical calculations are successfully
checked against a cosmological N-body experiment. We also consider the initial
conditions of this simulation, which correspond to a perturbed grid. This
allows us to test a case where the local Poisson assumption is incorrect. Even
in that extreme situation, the third-order Fourier-Taylor estimator behaves
well. We also show how to reach arbitrarily large dynamic range in Fourier
space (i.e., high wavenumber), while keeping statistical errors in control, by
appropriately "folding" the particle distribution.Comment: 18 Pages, 9 Figures. Accepted for publication in MNRAS. The
Fourier-Taylor module as well as the associated power spectrum estimator tool
we propose is available as an F90 package, POWMES, at
http://www.projet-horizon.fr or on request from the author
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