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White Dwarf – White Dwarf background in the LISA data

White Dwarf – White Dwarf background in the LISA data. Andrzej Królak Albert Einstein Institute Golm on leave from Institute of Mathematics Warsaw. Joint work with J. Edlund, G. Nelemans and M.Tinto. Data analysis problems. Stochastic signal. Interacting signals. Isolated signals. TDI.

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White Dwarf – White Dwarf background in the LISA data

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  1. White Dwarf – White Dwarf background in the LISA data Andrzej Królak Albert Einstein Institute Golm on leave from Institute of Mathematics Warsaw Joint work with J. Edlund, G. Nelemans and M.Tinto Annecy 15th December 2004

  2. Data analysis problems Stochastic signal Interacting signals Isolated signals TDI Long wavelength regime Short wavelength regime LISA motion; long observation times; network of detectors Annecy 15th December 2004

  3. wd-wd, wd-ns, ns-ns binaries with GW frequency within LISA band are observed.These sources are GUARANTEEDand the only ones that are guaranteed. Background signal and binary orientations uniformly distributed Sources uniformly distributed in the Galactic disc where H = 2.5kpc, zo = 200pc Annecy 15th December 2004

  4. Distribution of WD binaries (Nelemans) Total number of detatched binaries 208736473 Total number of interacting binaries 34291253 Annecy 15th December 2004

  5. Cyclostationary random processes Random process X(t) is cyclostationary if there exists period T such that E[X(s) X(t)] = C(s,t) = C(s + T, t + T) Annecy 15th December 2004

  6. Cyclostationary random processes cnd. • Spectra of cyclostationary process Let n(t) be a stationary process with spectral density S(f) and variance And let X(t) be a cyclostationary process uncorrelated with n(t) then and for k > 0 Annecy 15th December 2004

  7. Autocorrelation function of the background signal where Ak = 0 for k not zero 0 when sources isotropically distributed around the detector Ak not 0 for k not zero 0 for galactic disc distribution Annecy 15th December 2004

  8. Time domain data Annecy 15th December 2004

  9. Harmonics of the sample variance of data – least squares fit Annecy 15th December 2004 see also, Giampieri, Polnarev, 1997

  10. Analytic calculations vs. numerical estimates Annecy 15th December 2004

  11. Annecy 15th December 2004

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