The Mock LISA Data Challenges: from challenge 3 to challenge 4

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534

567

We review the expected science performance of the New Gravitational-Wave Observatory (NGO, a.k.a. eLISA), a mission under study by the European Space Agency for launch in the early 2020s. eLISA will survey the low-frequency gravitational-wave sky (from 0.1 mHz to 1 Hz), detecting and characterizing a broad variety of systems and events throughout the Universe, including the coalescences of massive black holes brought together by galaxy mergers; the inspirals of stellar-mass black holes and compact stars into central galactic black holes; several millions of ultra-compact binaries, both detached and mass transferring, in the Galaxy; and possibly unforeseen sources such as the relic gravitational-wave radiation from the early Universe. eLISA's high signal-tonoise measurements will provide new insight into the structure and history of the Universe, and they will test general relativity in its strong-field dynamical regime.

Section: Extreme-mass-ratio Inspirals (Emris) and The Astrophysics Ofmentioning

confidence: 58%

Low-frequency gravitational-wave science with eLISA/NGO

Amaro-Seoane¹,

Aoudia²,

Babak³

et al. 2012

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534

567

“…[26] and in the Mock LISA Data Challenges [27,28,29,30,31] by setting β = π/2 − θ, λ = φ, and ψ = −ψ.…”

Section: Gw Source Conventionsmentioning

confidence: 99%

“…We use the instrument noise of Eq. (17), with the assumptions on optical-path and proof-mass noises given in the 2011 LISA requirements [35], and spelled out in Table 1, where they are compared with the parameters used for the Mock LISA Data Challenges [27,28,29,30,31] and for the ESA 2011 "NGO" study [6,7].…”

Section: Computing the Sensitivitymentioning

confidence: 99%

“…For simplicity, in this paper we set η 0 = ξ 0 = 0; however, to map these orbits to those used in the LISA Simulator [26] and in the Mock LISA Data Challenges [27,28,29,30,31], we need to relabel spacecraft 1, 2, and 3 as 0, 2, and 1, and then set η 0 = κ, ξ 0 = 3π/2 − κ + λ, where κ and λ are the parameters defined below Eqs. (56) and (57) of Ref.…”

Section: Summary and Applicationsmentioning

confidence: 99%

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Non-sky-averaged sensitivity curves for space-based gravitational-wave observatories

Vallisneri¹,

Galley²

2012

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Abstract. The signal-to-noise ratio (SNR) is used in gravitational-wave observations as the basic figure of merit for detection confidence and, together with the Fisher matrix, for the amount of physical information that can be extracted from a detected signal. SNRs are usually computed from a sensitivity curve, which describes the gravitational-wave amplitude needed by a monochromatic source of given frequency to achieve a threshold SNR. Although the term "sensitivity" is used loosely to refer to the detector's noise spectral density, the two quantities are not the same: the sensitivity includes also the frequency-and orientationdependent response of the detector to gravitational waves, and takes into account the duration of observation. For interferometric space-based detectors similar to LISA, which are sensitive to long-lived signals and have constantly changing position and orientation, exact SNRs need to be computed on a source-bysource basis. For convenience, most authors prefer to work with sky-averaged sensitivities, accepting inaccurate SNRs for individual sources and giving up control over the statistical distribution of SNRs for source populations. In this paper, we describe a straightforward end-to-end recipe to compute the non-skyaveraged sensitivity of interferometric space-based detectors of any geometry. This recipe includes the effects of spacecraft motion and of seasonal variations in the partially subtracted confusion foreground from Galactic binaries, and it can be used to generate a sampling distribution of sensitivities for a given source population. In effect, we derive error bars for the sky-averaged sensitivity curve, which provide a stringent statistical interpretation for previously unqualified statements about sky-averaged SNRs. As a worked-out example, we consider isotropic and Galactic-disk populations of monochromatic sources, as observed with the "classic LISA" configuration. We confirm that the (standard) inverserms average sensitivity for the isotropic population remains the same whether or not the LISA orbits are included in the computation. However, detector motion tightens the distribution of sensitivities, so for 50% of sources the sensitivity is within 30% of its average. For the Galactic-disk population, the average and the distribution of the sensitivity for a moving detector turn out to be similar to the isotropic case. Non-sky-averaged sensitivity curves for space-based GW observatories 2

“…We tested our searches using data sets from the recent third Mock LISA Data Challenge (MLDC) [17,18]. Both our PyMC and MultiNest searches performed well in locating the global SNR maxima in parameter space, and our best-fit SNRs were within 1% of the true SNRs for all MLDC3 cases.…”

Section: Introductionmentioning

confidence: 99%

Searches for cosmic-string gravitational-wave bursts in Mock LISA Data

Cohen

Cutler

Vallisneri

2010

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Abstract. A network of observable, macroscopic cosmic (super-)strings may well have formed in the early Universe. If so, the cusps that generically develop on cosmic-string loops emit bursts of gravitational radiation that could be detectable by gravitational-wave interferometers, such as the ground-based LIGO/Virgo detectors and the planned, space-based LISA detector. Here we report on two versions of a LISA-oriented string-burst search pipeline that we have developed and tested within the context of the Mock LISA Data Challenges. The two versions rely on the publicly available MultiNest and PyMC software packages, respectively. To reduce the effective dimensionality of the search space, our implementations use the F -statistic to analytically maximize over the signal's amplitude and polarization, A and ψ, and use the FFT to search quickly over burst arrival times t C . The standard F -statistic is essentially a frequentist statistic that maximizes the likelihood; we also demonstrate an approximate, Bayesian version of the F -statistic that incorporates realistic priors on A and ψ. We calculate how accurately LISA can expect to measure the physical parameters of stringburst sources, and compare to results based on the Fisher-matrix approximation. To understand LISA's angular resolution for string-burst sources, we draw maps of the waveform fitting factor [maximized over (A, ψ, t C )] as a function of sky position; these maps dramatically illustrate why (for LISA) inferring the correct sky location of the emitting string loop will often be practically impossible. In addition, we identify and elucidate several symmetries that are imbedded in this search problem, and we derive the distribution of cut-off frequencies fmax for observable bursts.