3,311 research outputs found

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

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    The Mock LISA Data Challenges are a program to demonstrate LISA data-analysis capabilities and to encourage their development. Each round of challenges consists of one or more datasets containing simulated instrument noise and gravitational waves from sources of undisclosed parameters. Participants analyze the datasets and report best-fit solutions for the source parameters. Here we present the results of the third challenge, issued in Apr 2008, which demonstrated the positive recovery of signals from chirping Galactic binaries, from spinning supermassive--black-hole binaries (with optimal SNRs between ~ 10 and 2000), from simultaneous extreme-mass-ratio inspirals (SNRs of 10-50), from cosmic-string-cusp bursts (SNRs of 10-100), and from a relatively loud isotropic background with Omega_gw(f) ~ 10^-11, slightly below the LISA instrument noise.Comment: 12 pages, 2 figures, proceedings of the 8th Edoardo Amaldi Conference on Gravitational Waves, New York, June 21-26, 200

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

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    The Mock LISA Data Challenges are a program to demonstrate LISA data-analysis capabilities and to encourage their development. Each round of challenges consists of one or more datasets containing simulated instrument noise and gravitational waves from sources of undisclosed parameters. Participants analyze the datasets and report best-fit solutions for the source parameters. Here we present the results of the third challenge, issued in April 2008, which demonstrated the positive recovery of signals from chirping galactic binaries, from spinning supermassive-black-hole binaries (with optimal SNRs between ~10 and 2000), from simultaneous extreme-mass-ratio inspirals (SNRs of 10–50), from cosmic-string-cusp bursts (SNRs of 10–100), and from a relatively loud isotropic background with Ω_(gw)(f) ~ 10^(−11), slightly below the LISA instrument noise

    Detection of a Fully-resolved Compton Shoulder of the Iron K-alpha Line in the Chandra X-ray Spectrum of GX 301-2

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    We report the detection of a fully-resolved, Compton-scattered emission line in the X-ray spectrum of the massive binary GX 301-2 obtained with the High Energy Transmission Grating Spectrometer onboard the Chandra X-ray Observatory. The iron K-alpha fluorescence line complex observed in this system consists of an intense narrow component centered at an energy of E = 6.40 keV and a redward shoulder that extends down to ~6.24 keV, which corresponds to an energy shift of a Compton back-scattered iron K-alpha photon. From detailed Monte Carlo simulations and comparisons with the observed spectra, we are able to directly constrain the physical properties of the scattering medium, including the electron temperature and column density, as well as an estimate for the metal abundance.Comment: 13 pages, 4 figures, 1 table, accepted for publication in ApJ Lette

    Filaments of the radio cosmic web: opportunities and challenges for SKA

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    The detection of the diffuse gas component of the cosmic web remains a formidable challenge. In this work we study synchrotron emission from the cosmic web with simulated SKA1 observations, which can represent an fundamental probe of the warm-hot intergalactic medium. We investigate radio emission originated by relativistic electrons accelerated by shocks surrounding cosmic filaments, assuming diffusive shock acceleration and as a function of the (unknown) large-scale magnetic fields. The detection of the brightest parts of large (>10Mpc>10 \rm Mpc) filaments of the cosmic web should be within reach of the SKA1-LOW, if the magnetic field is at the level of a 10\sim 10 percent equipartition with the thermal gas, corresponding to 0.1μG\sim 0.1 \mu G for the most massive filaments in simulations. In the course of a 2-years survey with SKA1-LOW, this will enable a first detection of the "tip of the iceberg" of the radio cosmic web, and allow for the use of the SKA as a powerful tool to study the origin of cosmic magnetism in large-scale structures. On the other hand, the SKA1-MID and SKA1-SUR seem less suited for this science case at low redshift (z0.4z \leq 0.4), owing to the missing short baselines and the consequent lack of signal from the large-scale brightness fluctuations associated with the filaments. In this case only very long exposures (1000\sim 1000 hr) may enable the detection of 12\sim 1-2 filament for field of view in the SKA1-SUR PAF Band1.Comment: 10 pages, 4 figures, to appear in Proceedings of 'Advancing Astrophysics with the SKA (AASKA14) - Cosmic Magnetism' Chapter

    The Optimal Gravitational Lens Telescope

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    Given an observed gravitational lens mirage produced by a foreground deflector (cf. galaxy, quasar, cluster,...), it is possible via numerical lens inversion to retrieve the real source image, taking full advantage of the magnifying power of the cosmic lens. This has been achieved in the past for several remarkable gravitational lens systems. Instead, we propose here to invert an observed multiply imaged source directly at the telescope using an ad-hoc optical instrument which is described in the present paper. Compared to the previous method, this should allow one to detect fainter source features as well as to use such an optimal gravitational lens telescope to explore even fainter objects located behind and near the lens. Laboratory and numerical experiments illustrate this new approach

    Bayesian optimisation for likelihood-free cosmological inference

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    Many cosmological models have only a finite number of parameters of interest, but a very expensive data-generating process and an intractable likelihood function. We address the problem of performing likelihood-free Bayesian inference from such black-box simulation-based models, under the constraint of a very limited simulation budget (typically a few thousand). To do so, we adopt an approach based on the likelihood of an alternative parametric model. Conventional approaches to approximate Bayesian computation such as likelihood-free rejection sampling are impractical for the considered problem, due to the lack of knowledge about how the parameters affect the discrepancy between observed and simulated data. As a response, we make use of a strategy previously developed in the machine learning literature (Bayesian optimisation for likelihood-free inference, BOLFI), which combines Gaussian process regression of the discrepancy to build a surrogate surface with Bayesian optimisation to actively acquire training data. We extend the method by deriving an acquisition function tailored for the purpose of minimising the expected uncertainty in the approximate posterior density, in the parametric approach. The resulting algorithm is applied to the problems of summarising Gaussian signals and inferring cosmological parameters from the Joint Lightcurve Analysis supernovae data. We show that the number of required simulations is reduced by several orders of magnitude, and that the proposed acquisition function produces more accurate posterior approximations, as compared to common strategies.Comment: 16+9 pages, 12 figures. Matches PRD published version after minor modification

    Time-ordered data simulation and map-making for the PIXIE Fourier transform spectrometer

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    We develop a time-ordered data simulator and map-maker for the proposed PIXIE Fourier transform spectrometer and use them to investigate the impact of polarization leakage, imperfect collimation, elliptical beams, sub-pixel effects, correlated noise and spectrometer mirror jitter on the PIXIE data analysis. We find that PIXIE is robust to all of these effects, with the exception of mirror jitter which could become the dominant source of noise in the experiment if the jitter is not kept significantly below 0.1μms0.1\mu m\sqrt{s}. Source code is available at https://github.com/amaurea/pixie.Comment: 27 pages, 15 figures. Accepted for publication in JCA

    The InfraRed Imaging Spectrograph (IRIS) for TMT: latest science cases and simulations

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    The Thirty Meter Telescope (TMT) first light instrument IRIS (Infrared Imaging Spectrograph) will complete its preliminary design phase in 2016. The IRIS instrument design includes a near-infrared (0.85 - 2.4 micron) integral field spectrograph (IFS) and imager that are able to conduct simultaneous diffraction-limited observations behind the advanced adaptive optics system NFIRAOS. The IRIS science cases have continued to be developed and new science studies have been investigated to aid in technical performance and design requirements. In this development phase, the IRIS science team has paid particular attention to the selection of filters, gratings, sensitivities of the entire system, and science cases that will benefit from the parallel mode of the IFS and imaging camera. We present new science cases for IRIS using the latest end-to-end data simulator on the following topics: Solar System bodies, the Galactic center, active galactic nuclei (AGN), and distant gravitationally-lensed galaxies. We then briefly discuss the necessity of an advanced data management system and data reduction pipeline.Comment: 15 pages, 7 figures, SPIE (2016) 9909-0
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