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- Hamaus, N., et al.
(author)
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Euclid : Forecasts from redshift-space distortions and the Alcock-Paczynski test with cosmic voids
- 2022
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In: Astronomy and Astrophysics. - : EDP Sciences. - 0004-6361 .- 1432-0746. ; 658
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Journal article (peer-reviewed)abstract
- Euclid is poised to survey galaxies across a cosmological volume of unprecedented size, providing observations of more than a billion objects distributed over a third of the full sky. Approximately 20 million of these galaxies will have their spectroscopy available, allowing us to map the three-dimensional large-scale structure of the Universe in great detail. This paper investigates prospects for the detection of cosmic voids therein and the unique benefit they provide for cosmological studies. In particular, we study the imprints of dynamic (redshift-space) and geometric (Alcock-Paczynski) distortions of average void shapes and their constraining power on the growth of structure and cosmological distance ratios. To this end, we made use of the Flagship mock catalog, a state-of-the-art simulation of the data expected to be observed with Euclid. We arranged the data into four adjacent redshift bins, each of which contains about 11000 voids and we estimated the stacked void-galaxy cross-correlation function in every bin. Fitting a linear-theory model to the data, we obtained constraints on f/b and DMH, where f is the linear growth rate of density fluctuations, b the galaxy bias, D-M the comoving angular diameter distance, and H the Hubble rate. In addition, we marginalized over two nuisance parameters included in our model to account for unknown systematic effects in the analysis. With this approach, Euclid will be able to reach a relative precision of about 4% on measurements of f/b and 0.5% on DMH in each redshift bin. Better modeling or calibration of the nuisance parameters may further increase this precision to 1% and 0.4%, respectively. Our results show that the exploitation of cosmic voids in Euclid will provide competitive constraints on cosmology even as a stand-alone probe. For example, the equation-of-state parameter, w, for dark energy will be measured with a precision of about 10%, consistent with previous more approximate forecasts.
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- Contarini, S., et al.
(author)
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Euclid : cosmological forecasts from the void size function
- 2022
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In: Astronomy and Astrophysics. - : EDP Sciences. - 0004-6361 .- 1432-0746. ; 667
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Journal article (peer-reviewed)abstract
- The Euclid mission - with its spectroscopic galaxy survey covering a sky area over 15 000 deg(2) in the redshift range 0.9 < z < 1.8 - will provide a sample of tens of thousands of cosmic voids. This paper thoroughly explores for the first time the constraining power of the void size function on the properties of dark energy (DE) from a survey mock catalogue, the official Euclid Flagship simulation. We identified voids in the Flagship light-cone, which closely matches the features of the upcoming Euclid spectroscopic data set. We modelled the void size function considering a state-of-the art methodology: we relied on the volume-conserving (Vdn) model, a modification of the popular Sheth & van de Weygaert model for void number counts, extended by means of a linear function of the large-scale galaxy bias. We found an excellent agreement between model predictions and measured mock void number counts. We computed updated forecasts for the Euclid mission on DE from the void size function and provided reliable void number estimates to serve as a basis for further forecasts of cosmological applications using voids. We analysed two different cosmological models for DE: the first described by a constant DE equation of state parameter, w, and the second by a dynamic equation of state with coefficients w(0) and w(a). We forecast 1 sigma errors on w lower than 10% and we estimated an expected figure of merit (FoM) for the dynamical DE scenario FoM(w0,wa) = 17 when considering only the neutrino mass as additional free parameter of the model. The analysis is based on conservative assumptions to ensure full robustness, and is a pathfinder for future enhancements of the technique. Our results showcase the impressive constraining power of the void size function from the Euclid spectroscopic sample, both as a stand-alone probe, and to be combined with other Euclid cosmological probes.
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- Pöntinen, M., et al.
(author)
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Euclid: Identification of asteroid streaks in simulated images using deep learning
- 2023
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In: Astronomy and Astrophysics. - : EDP Sciences. - 0004-6361 .- 1432-0746. ; 679
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Journal article (peer-reviewed)abstract
- The material composition of asteroids is an essential piece of knowledge in the quest to understand the formation and evolution of the Solar System. Visual to near-infrared spectra or multiband photometry is required to constrain the material composition of asteroids, but we currently have such data, especially in the near-infrared wavelengths, for only a limited number of asteroids. This is a significant limitation considering the complex orbital structures of the asteroid populations. Up to 150 000 asteroids will be visible in the images of the upcoming ESA Euclid space telescope, and the instruments of Euclid will offer multiband visual to near-infrared photometry and slitless near-infrared spectra of these objects. Most of the asteroids will appear as streaks in the images. Due to the large number of images and asteroids, automated detection methods are needed. A non-machine-learning approach based on the Streak Det software was previously tested, but the results were not optimal for short and/or faint streaks. We set out to improve the capability to detect asteroid streaks in Euclid images by using deep learning. We built, trained, and tested a three-step machine-learning pipeline with simulated Euclid images. First, a convolutional neural network (CNN) detected streaks and their coordinates in full images, aiming to maximize the completeness (recall) of detections. Then, a recurrent neural network (RNN) merged snippets of long streaks detected in several parts by the CNN. Lastly, gradient-boosted trees (XGBoost) linked detected streaks between different Euclid exposures to reduce the number of false positives and improve the purity (precision) of the sample. The deep-learning pipeline surpasses the completeness and reaches a similar level of purity of a non-machine-learning pipeline based on the StreakDet software. Additionally, the deep-learning pipeline can detect asteroids 0.25–0.5 magnitudes fainter than StreakDet. The deep-learning pipeline could result in a 50% increase in the number of detected asteroids compared to the StreakDet software. There is still scope for further refinement, particularly in improving the accuracy of streak coordinates and enhancing the completeness of the final stage of the pipeline, which involves linking detections across multiple exposures.
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- Telloni, D., et al.
(author)
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Study of two interacting interplanetary coronal mass ejections encountered by Solar Orbiter during its first perihelion passage Observations and modeling
- 2021
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In: Astronomy and Astrophysics. - : EDP Sciences. - 0004-6361 .- 1432-0746. ; 656
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Journal article (peer-reviewed)abstract
- Context. Solar Orbiter, the new-generation mission dedicated to solar and heliospheric exploration, was successfully launched on February 10, 2020, 04:03 UTC from Cape Canaveral. During its first perihelion passage in June 2020, two successive interplanetary coronal mass ejections (ICMEs), propagating along the heliospheric current sheet (HCS), impacted the spacecraft.Aims. This paper addresses the investigation of the ICMEs encountered by Solar Orbiter on June 7-8, 2020, from both an observational and a modeling perspective. The aim is to provide a full description of those events, their mutual interaction, and their coupling with the ambient solar wind and the HCS.Methods. Data acquired by the MAG magnetometer, the Energetic Particle Detector suite, and the Radio and Plasma Waves instrument are used to provide information on the ICMEs' magnetic topology configuration, their magnetic connectivity to the Sun, and insights into the heliospheric plasma environment where they travel, respectively. On the modeling side, the Heliospheric Upwind eXtrapolation model, the 3D COronal Rope Ejection technique, and the EUropean Heliospheric FORecasting Information Asset (EUHFORIA) tool are used to complement Solar Orbiter observations of the ambient solar wind and ICMEs, and to simulate the evolution and interaction of the ejecta in the inner heliosphere, respectively.Results. Both data analysis and numerical simulations indicate that the passage of two distinct, dynamically and magnetically interacting (via magnetic reconnection processes) ICMEs at Solar Orbiter is a possible scenario, supported by the numerous similarities between EUHFORIA time series at Solar Orbiter and Solar Orbiter data.Conclusions. The combination of in situ measurements and numerical simulations (together with remote sensing observations of the corona and inner heliosphere) will significantly lead to a deeper understanding of the physical processes occurring during the CME-CME interaction.
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- Broderick, J. W., et al.
(author)
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LOFAR 144-MHz follow-up observations of GW170817
- 2020
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In: Monthly Notices of the Royal Astronomical Society. - : Oxford University Press (OUP). - 0035-8711 .- 1365-2966. ; 494:4, s. 5110-5117
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Journal article (peer-reviewed)abstract
- We present low-radio-frequency follow-up observations of AT 2017gfo, the electromagnetic counterpart of GW170817, which was the first binary neutron star merger to be detected by Advanced LIGO-Virgo. These data, with a central frequency of 144 MHz, were obtained with LOFAR, the Low-Frequency Array. The maximum elevation of the target is just 13 degrees.7 when observed with LOFAR, making our observations particularly challenging to calibrate and significantly limiting the achievable sensitivity. On time-scales of 130-138 and 371-374 d after the merger event, we obtain 3s upper limits for the afterglow component of 6.6 and 19.5mJy beam(-1), respectively. Using our best upper limit and previously published, contemporaneous higher frequency radio data, we place a limit on any potential steepening of the radio spectrum between 610 and 144 MHz: the two-point spectral index alpha(610)(144) greater than or similar to -2.5. We also show that LOFAR can detect the afterglows of future binary neutron star merger events occurring at more favourable elevations.
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