| 1. |
- Pöntinen, M., et al.
(författare)
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Euclid: Identification of asteroid streaks in simulated images using deep learning
- 2023
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Ingår i: Astronomy and Astrophysics. - : EDP Sciences. - 0004-6361 .- 1432-0746. ; 679
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Tidskriftsartikel (refereegranskat)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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| 2. |
- Ricci, M., et al.
(författare)
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The XXL Survey: XLIV. Sunyaev-Zel'dovich mapping of a low-mass cluster at z ∼1: A multi-wavelength approach
- 2020
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Ingår i: Astronomy and Astrophysics. - : EDP Sciences. - 0004-6361 .- 1432-0746. ; 642
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Tidskriftsartikel (refereegranskat)abstract
- High-mass clusters at low redshifts have been intensively studied at various wavelengths. However, while more distant objects at lower masses constitute the bulk population of future surveys, their physical state remain poorly explored to date. In this paper, we present resolved observations of the Sunyaev-Zel'dovich (SZ) effect, obtained with the NIKA2 camera, towards the cluster of galaxies XLSSC 102, a relatively low-mass system (M500 ∼ 2 × 1014 M·) at z = 0.97 detected from the XXL survey. We combine NIKA2 SZ data, XMM-Newton X-ray data, and Megacam optical data to explore, respectively, the spatial distribution of the gas electron pressure, the gas density, and the galaxies themselves. We find significant offsets between the X-ray peak, the SZ peak, the brightest cluster galaxy, and the peak of galaxy density. Additionally, the galaxy distribution and the gas present elongated morphologies. This is interpreted as the sign of a recent major merging event, which induced a local boost of the gas pressure towards the north of XLSSC 102 and stripped the gas out of the galaxy group. The NIKA2 data are also combined with XXL data to construct the thermodynamic profiles of XLSSC 102, obtaining relatively tight constraints up to about ∼r500, and revealing properties that are typical of disturbed systems. We also explore the impact of the cluster centre definition and the implication of local pressure substructure on the recovered profiles. Finally, we derive the global properties of XLSSC 102 and compare them to those of high-mass-and-low-redshift systems, finding no strong evidence for non-standard evolution. We also use scaling relations to obtain alternative mass estimates from our profiles. The variation between these different mass estimates reflects the difficulty to accurately measure the mass of low-mass clusters at z ∼ 1, especially with low signal-to-noise ratio data and for a disturbed system. However, it also highlights the strength of resolved SZ observations alone and in combination with survey-like X-ray data. This is promising for the study of high redshift clusters from the combination of eROSITA and high resolution SZ instruments and will complement the new generation of optical surveys from facilities such as LSST and Euclid.
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| 3. |
- Adam, R. M., et al.
(författare)
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The XXL Survey: LI. Pressure profile and Y SZ -M scaling relation in three low-mass galaxy clusters at z∼1 observed with NIKA2
- 2024
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Ingår i: Astronomy and Astrophysics. - 0004-6361 .- 1432-0746. ; 684
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Tidskriftsartikel (refereegranskat)abstract
- Context. The thermodynamical properties of the intracluster medium (ICM) are driven by scale-free gravitational collapse, but they also reflect the rich astrophysical processes at play in galaxy clusters. At low masses (∼1014M) and high redshift (z≳1), these properties remain poorly constrained, observationally speaking, due to the difficulty in obtaining resolved and sensitive data. Aims. We aim to investigate the inner structure of the ICM as seen through the Sunyaev-Zel’dovich (SZ) effect in this regime of mass and redshift. We focused on the thermal pressure profile and the scaling relation between SZ flux and mass, namely the YSZ-M scaling relation. Methods. The three galaxy clusters XLSSC 072 (z=1.002), XLSSC 100 (z=0.915), and XLSSC 102 (z=0.969), with M500∼2×1014M, were selected from the XXL X-ray survey and observed with the NIKA2 millimeter camera to image their SZ signal. XMM-Newton X-ray data were used as a complement to the NIKA2 data to derive masses based on the YX-M relation and the hydrostatic equilibrium. Results. The SZ images of the three clusters, along with the X-ray and optical data, indicate dynamical activity related to merging events. The pressure profile is consistent with that expected for morphologically disturbed systems, with a relatively flat core and a shallow outer slope. Despite significant disturbances in the ICM, the three high-redshift low-mass clusters follow the YSZ-M relation expected from standard evolution remarkably well. Conclusions. These results indicate that the dominant physics that drives cluster evolution is already in place by z∼1, at least for systems with masses above M500∼1014M.
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