4,743 research outputs found
High-cadence spectroscopy of M-dwarfs – II. Searching for stellar pulsations with HARPS
Stellar oscillations appear all across the Hertzsprung–Russell diagram. Recent theoretical studies support their existence also in the atmosphere of M dwarfs. These studies predict for them short periodicities ranging from 20 min to 3 h. Our Cool Tiny Beats (CTB) programme aims at finding these oscillations for the very first time. With this goal, CTB explores the short time domain of M dwarfs using radial velocity data from the High Accuracy Radial velocity Planet Searcher (HARPS)-European Southern Observatory and HARPS-N high-precision spectrographs. Here we present the results for the two most long-term stable targets observed to date with CTB, GJ 588 and GJ 699 (i.e. Barnard's star). In the first part of this work we detail the correction of several instrumental effects. These corrections are especially relevant when searching for subnight signals. Results show no significant signals in the range where M dwarfs pulsations were predicted. However, we estimate that stellar pulsations with amplitudes larger than ∼0.5 m s−1 can be detected with a 90 per cent completeness with our observations. This result, along with the excess of power regions detected in the periodograms, opens the possibility of non-resolved very low amplitude pulsation signals. Next generation more precise instrumentation would be required to detect such oscillations. However, the possibility of detecting pulsating M-dwarf stars with larger amplitudes is feasible due to the short size of the analysed sample. This motivates the need for completeness of the CTB survey
TEMPO2, a new pulsar timing package. I: Overview
Contemporary pulsar timing experiments have reached a sensitivity level where
systematic errors introduced by existing analysis procedures are limiting the
achievable science. We have developed tempo2, a new pulsar timing package that
contains propagation and other relevant effects implemented at the 1ns level of
precision (a factor of ~100 more precise than previously obtainable). In
contrast with earlier timing packages, tempo2 is compliant with the general
relativistic framework of the IAU 1991 and 2000 resolutions and hence uses the
International Celestial Reference System, Barycentric Coordinate Time and
up-to-date precession, nutation and polar motion models. Tempo2 provides a
generic and extensible set of tools to aid in the analysis and visualisation of
pulsar timing data. We provide an overview of the timing model, its accuracy
and differences relative to earlier work. We also present a new scheme for
predictive use of the timing model that removes existing processing artifacts
by properly modelling the frequency dependence of pulse phase.Comment: Accepted by MNRA
OMP-type Algorithm with Structured Sparsity Patterns for Multipath Radar Signals
A transmitted, unknown radar signal is observed at the receiver through more
than one path in additive noise. The aim is to recover the waveform of the
intercepted signal and to simultaneously estimate the direction of arrival
(DOA). We propose an approach exploiting the parsimonious time-frequency
representation of the signal by applying a new OMP-type algorithm for
structured sparsity patterns. An important issue is the scalability of the
proposed algorithm since high-dimensional models shall be used for radar
signals. Monte-Carlo simulations for modulated signals illustrate the good
performance of the method even for low signal-to-noise ratios and a gain of 20
dB for the DOA estimation compared to some elementary method
A comparison of Bayesian and Fourier methods for frequency determination in asteroseismology
Bayesian methods are becoming more widely used in asteroseismic analysis. In
particular, they are being used to determine oscillation frequencies, which are
also commonly found by Fourier analysis. It is important to establish whether
the Bayesian methods provide an improvement on Fourier methods. We compare,
using simulated data, the standard iterative sine-wave fitting method against a
Markov Chain Monte Carlo (MCMC) code that has been introduced to infer purely
the frequencies of oscillation modes (Brewer et al. 2007). A uniform prior
probability distribution function is used for the MCMC method. We find the
methods do equally well at determining the correct oscillation frequencies,
although the Bayesian method is able to highlight the possibility of a
misidentification due to aliasing, which can be useful. In general, we suggest
that the least computationally intensive method is preferable.Comment: 11 pages, 8 figures, accepted for publication in Communications in
Asterosesimolog
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