| 1. |
- Hamaus, N., et al.
(författare)
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Euclid : Forecasts from redshift-space distortions and the Alcock-Paczynski test with cosmic voids
- 2022
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Ingår i: Astronomy and Astrophysics. - : EDP Sciences. - 0004-6361 .- 1432-0746. ; 658
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Tidskriftsartikel (refereegranskat)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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| 2. |
- Contarini, S., et al.
(författare)
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Euclid : cosmological forecasts from the void size function
- 2022
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Ingår i: Astronomy and Astrophysics. - : EDP Sciences. - 0004-6361 .- 1432-0746. ; 667
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Tidskriftsartikel (refereegranskat)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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| 3. |
- 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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| 6. |
- Xing, Lucas Yixi, et al.
(författare)
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The ABC-Stroke Risk Score and Effects of Atrial Fibrillation Screening on Stroke Prevention : Results From the Randomized LOOP Study
- 2024
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Ingår i: Journal of the American Heart Association. - 2047-9980. ; 13:4
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Tidskriftsartikel (refereegranskat)abstract
- BACKGROUND: The ABC-stroke score is a risk scheme for prediction of stroke or systemic embolism (SE) in atrial fibrillation (AF). This study sought to examine whether the score could be useful in predicting stroke in AF-naïve individuals and risk stratifying for AF screening. METHODS AND RESULTS: The LOOP (Atrial Fibrillation Detected by Continuous ECG Monitoring Using Implantable Loop Recorder to Prevent Stroke in High-Risk Individuals) study randomized 6004 AF-naïve individuals aged 70 to 90 years with stroke risk factors to either screening with an implantable loop recorder and anticoagulation upon detection of new-onset AF episodes ≥6 minutes, or usual care. A total of 5781 participants had available ABC-stroke score at baseline and were included in this secondary analysis: 4170 (72.1%) with an estimated stroke/SE risk ≤1%/year versus 1611 (27.9%) with an estimated stroke/SE risk >1%/year. Having an annual ABC-stroke risk >1% was associated with stroke/SE, stroke/SE/cardiovascular death, and allcause death (hazard ratio, 1.82 [95% CI, 1.44–2.21], 2.17 [95% CI, 1.80–2.62], and 2.19 [95% CI, 1.87–2.56], respectively). For screening with implantable loop recorder versus usual care, no significant reduction in these study outcomes was obtained in any ABC-stroke risk groups (P>0.0500 for all), with no signal toward interaction (Pinteraction >0.2500 for all). Similar findings were yielded when assessing the ABC-stroke score as a continuous variable. CONCLUSIONS: In an elderly, AF-naïve population with additional stroke risk factors, a higher ABC-stroke score could identify individuals with increased stroke risk. However, this risk score may not be useful in pinpointing those more likely to benefit from AF screening and subsequent preventive treatment. These findings should be considered as hypothesis generating and warrant further study.
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