activity
20042011
most citedHot subdwarfs from the ESO Supernova Ia Progenitor Survey: II. Atmospheric parameters of subdwarf O stars

142 citations · 1k across the 19 of their papers we have counts for

collaborators

18 papers

astro-ph.SR2011

Detecting Double Degenerate Progenitors of SNe Ia with LISA

Alexander Stroeer, Matthew Benacquista, Frank Ceballos

The Galactic population of close white dwarf binaries is expected to provide the largest number of gravitational wave sources for low frequency detectors such as the Laser Interfer…

gr-qc2011★ 4 cited

Comparison of Signals from Gravitational Wave Detectors with Instantaneous Time-Frequency Maps

Alexander Stroeer, Lindy Blackburn, Jordan Camp

Gravitational wave astronomy relies on the use of multiple detectors, so that coincident detections may distinguish real signals from instrumental artifacts, and also so that relat…

gr-qc2009★ 10 cited

The influence of short term variations in AM CVn systems on LISA measurements

Alexander Stroeer, Gijs Nelemans

We study the effect of short term variations of the evolution of AM CVn systems on their gravitational wave emissions and in particular LISA observations. We model the systems acco…

astro-ph.IM2009★ 10 cited

A Bayesian approach to the study of white dwarf binaries in LISA data: The application of a reversible jump Markov chain Monte Carlo method

Alexander Stroeer, John Veitch

The Laser Interferometer Space Antenna (LISA) defines new demands on data analysis efforts in its all-sky gravitational wave survey, recording simultaneously thousands of galactic…

gr-qc2009★ 55 cited

Status of NINJA: the Numerical INJection Analysis project

Benjamin Aylott, John G. Baker, William D. Boggs +74

The 2008 NRDA conference introduced the Numerical INJection Analysis project (NINJA), a new collaborative effort between the numerical relativity community and the data analysis co…

physics.data-an2009★ 24 cited

Methods for detection and characterization of signals in noisy data with the Hilbert-Huang Transform

Alexander Stroeer, John K. Cannizzo, Jordan B. Camp +1

The Hilbert-Huang Transform is a novel, adaptive approach to time series analysis that does not make assumptions about the data form. Its adaptive, local character allows the decom…