Browsing by Author "Gozaliasl, G."
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- AXES-SDSS: comparison of SDSS galaxy groups with All-sky X-ray Extended Sources
A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä(2024-10-01) Damsted, S.; Finoguenov, A.; Lietzen, H.; Mamon, G. A.; Comparat, J.; Tempel, E.; Dmitrieva, I.; Clerc, N.; Collins, C.; Gozaliasl, G.; Eckert, D.Context. Advances in cosmological studies require us to improve our understanding of the baryonic content of galaxy groups. The key baryonic components of groups are galaxies and hot gas, while key non-baryonic mass tracers are the velocity dispersion of galaxies and the distribution of galaxies within the group. Aims. We revisit the picture of X-ray emission of groups through the study of systematic differences in the optical properties of groups, with and without X-ray emission, and we study the effect of the large-scale density field on scaling relations. Methods. We present the identification of X-ray galaxy groups using a combination of ROSAT All Sky Survey (RASS) and Sloan Digital Sky Survey (SDSS) data. We include a new X-ray reanalysis of RASS, covering very extended (up to a size of half a degree) sources, and we account for differences in the limiting sensitivity with respect to compact and very extended X-ray emission. We applied a screening of the identified X-ray sources, based on the optical properties, to achieve 95% clean catalogues. We used a mock SDSS survey to understand the performance of our FoF group finder and applied the CLEAN algorithm to revise group mass estimates and achieve a clean membership catalogue. Results. X-ray groups exhibit less scatter in the scaling relations and selecting the groups based on the extended X-ray emission leads to an additional scatter reduction. Most of the scatter for the optical groups is associated with a small (6%) fraction of outliers, primarily associated with low optical-luminosity groups found in dense regions of the cosmic web. These groups are primary candidates for the contaminants in the optical group catalogues. We find that removing only those groups from the optical group sample using optically measured properties leads to a substantial reduction in the scatter of the scaling relations of the optical groups. We report a dependence of both the X-ray and optical luminosity of groups on large-scale density, which we associate with the assembly bias. These results motivate an introduction of an additional characterization of galaxy clusters and shed light on the physical origin of anomalous clustering of galaxy clusters, found by the Dark Energy Survey (DES). - COSMOS brightest group galaxies. III. Evolution of stellar ages
A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä(2024-10-01) Gozaliasl, G.; Finoguenov, A.; Babul, A.; Ilbert, O.; Sargent, M.; Vardoulaki, E.; Faisst, A. L.; Liu, Z.; Shuntov, M.; Cooper, O.; Dolag, K.; Toft, S.; Magdis, G. E.; Toni, G.; Mobasher, B.; Barré, R.; Cui, W.; Rennehan, D.The unique characteristics of the brightest group galaxies (BGGs) serve as a link in the evolutionary continuum between galaxies such as the Milky Way and the more massive brightest cluster galaxies found in dense clusters. This research investigates the evolution of the stellar properties of BGGs over cosmic time (za =a 0.08a aa 1.30), extending the work from our prior studies. We analyzed the data of 246 BGGs selected from our X-ray galaxy group catalog within the COSMOS field, examining stellar age, mass, star-formation rate (SFR), specific SFR, and halo mass. We compared observations with the Millennium and Magneticum simulations. Additionally, we investigated whether stellar properties vary with the projected offset from the X-ray peak or the hosting halo center. We evaluated the accuracy of SED-derived stellar ages using a mock galaxy catalog, finding a mean absolute error of around 1 Gyr. Interestingly, the observed BGG age distributions exhibit a bias toward younger intermediate ages compared to both semi-Analytical models and the Magneticum simulation. Our analysis of stellar age versus mass unveils intriguing trends with a positive slope, hinting at complex evolutionary pathways across redshifts. We observed a negative correlation between stellar age and SFR across all redshift ranges. We employed a cosmic time dependent main sequence framework to identify star forming BGGs and find that approximately 20% of BGGs in the local universe continue to exhibit characteristics typical of star forming galaxies, with this proportion increasing to 50% at za =a 1.0. Our findings support an inside-out formation scenario for BGGs, where older stellar populations reside near the X-ray peak and younger populations at larger offsets indicate ongoing star-formation. The observed distribution of stellar ages, particularly for lower-mass BGGs in the range of 1010a-11-a-, deviates from the constant ages predicted by the models across all stellar mass ranges and redshifts. This discrepancy aligns with the current modelsa known limitations in accurately capturing galaxiesa complex star-formation histories. - The COSMOS-Web ring : In-depth characterization of an Einstein ring lensing system at z ∼ 2
A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä(2024-07-01) Mercier, W.; Shuntov, M.; Gavazzi, R.; Nightingale, J. W.; Arango, R.; Ilbert, O.; Amvrosiadis, A.; Ciesla, L.; Casey, C. M.; Jin, S.; Faisst, A. L.; Andika, I. T.; Drakos, N. E.; Enia, A.; Franco, M.; Gillman, S.; Gozaliasl, G.; Hayward, C. C.; Huertas-Company, M.; Kartaltepe, J. S.; Koekemoer, A. M.; Laigle, C.; Le Borgne, D.; Magdis, G.; Mahler, G.; Maraston, C.; Martin, C. L.; Massey, R.; McCracken, H. J.; Moutard, T.; Paquereau, L.; Rhodes, J. D.; Robertson, B. E.; Sanders, D. B.; Toft, S.; Trebitsch, M.; Tresse, L.; Vijayan, A. P.Aims. We provide an in-depth analysis of the COSMOS-Web ring, an Einstein ring at z ≈ 2 that we serendipitously discovered during the data reduction of the COSMOS-Web survey and that could be the most distant lens discovered to date. Methods. We extracted the visible and near-infrared photometry of the source and the lens from more than 25 bands. We combined these observations with far-infrared detections to study the dusty nature of the source and we derived the photometric redshifts and physical properties of both the lens and the source with three different spectral energy distribution (SED) fitting codes. Using JWST/NIRCam images, we also produced two lens models to (i) recover the total mass of the lens, (ii) derive the magnification of the system, (iii) reconstruct the morphology of the lensed source, and (iv) measure the slope of the total mass density profile of the lens. Results. We find the lens to be a very massive elliptical galaxy at z = 2.02 ± 0.02 with a total mass within the Einstein radius of Mtot(<θEin = (3.66 ± 0.36) × 1011 M· and a total stellar mass of M∗ = 1.37-0.11+0.14 × 1011 M·. We also estimate it to be compact and quiescent with a specific star formation rate below 10-13 yr. Compared to stellar-to-halo mass relations from the literature, we find that the total mass of the lens within the Einstein radius is consistent with the presence of a dark matter (DM) halo of total mass Mh = 1.09-0.57+1.46 × 1013 M·. In addition, the background source is a M∗ = (1.26 ± 0.17) × 1010 M· star-forming galaxy (SFR ≈ (78 ± 15) M· yr) at z = 5.48 ± 0.06. The morphology reconstructed in the source plane shows two clear components with different colors. Dust attenuation values from SED fitting and nearby detections in the far infrared also suggest that the background source could be at least partially dust-obscured. Conclusions. We find the lens at z ≈ 2. Its total, stellar, and DM halo masses are consistent within the Einstein ring, so we do not need any unexpected changes in our description of the lens such as changing its initial mass function or including a non-negligible gas contribution. The most likely solution for the lensed source is at z ≈ 5.5. Its reconstructed morphology is complex and highly wavelength dependent, possibly because it is a merger or a main sequence galaxy with a heterogeneous dust distribution. - Euclid preparation : L. Calibration of the halo linear bias in Λ(v)CDM cosmologies
A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä(2024-11-01) Castro, T.; Fumagalli, A.; Angulo, R. E.; Bocquet, S.; Borgani, S.; Costanzi, M.; Dakin, J.; Dolag, K.; Monaco, P.; Saro, A.; Sefusatti, E.; Aghanim, N.; Amendola, L.; Andreon, S.; Baccigalupi, C.; Baldi, M.; Bodendorf, C.; Bonino, D.; Branchini, E.; Brescia, M.; Caillat, A.; Camera, S.; Capobianco, V.; Carbone, C.; Carretero, J.; Casas, S.; Castellano, M.; Castignani, G.; Cavuoti, S.; Cimatti, A.; Colodro-Conde, C.; Congedo, G.; Conselice, C. J.; Conversi, L.; Copin, Y.; Costille, A.; Courbin, F.; Courtois, H. M.; Da Silva, A.; Degaudenzi, H.; De Lucia, G.; Di Giorgio, A. M.; Douspis, M.; Niemi, S. M.; Sánchez, A. G.; Wang, Y.; Calabrese, M.; Gozaliasl, G.; Hall, A.; Hjorth, J.; , Euclid CollaborationThe Euclid mission, designed to map the geometry of the dark Universe, presents an unprecedented opportunity for advancing our understanding of the cosmos through its photometric galaxy cluster survey. Central to this endeavor is the accurate calibration of the mass- and redshift-dependent halo bias (HB), which is the focus of this paper. Our aim is to enhance the precision of HB predictions, which is crucial for deriving cosmological constraints from the clustering of galaxy clusters. Our study is based on the peak-background split (PBS) model linked to the halo mass function (HMF), and it extends it with a parametric correction to precisely align with results from an extended set of N-body simulations carried out with the OpenGADGET3 code. Employing simulations with fixed and paired initial conditions, we meticulously analyzed the matter-halo cross-spectrum and modeled its covariance using a large number of mock catalogs generated with Lagrangian perturbation theory simulations with the PINOCCHIO code. This ensures a comprehensive understanding of the uncertainties in our HB calibration. Our findings indicate that the calibrated HB model is remarkably resilient against changes in cosmological parameters, including those involving massive neutrinos. The robustness and adaptability of our calibrated HB model provide an important contribution to the cosmological exploitation of the cluster surveys to be provided by the Euclid mission. This study highlights the necessity of continuously refining the calibration of cosmological tools such as the HB to match the advancing quality of observational data. As we project the impact of our calibrated model on cosmological constraints, we find that given the sensitivity of the Euclid survey, a miscalibration of the HB could introduce biases in cluster cosmology analysis. Our work fills this critical gap, ensuring the HB calibration matches the expected precision of the Euclid survey. - Euclid preparation : XLIX. Selecting active galactic nuclei using observed colours
A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä(2024-11-01) Bisigello, L.; Massimo, M.; Tortora, C.; Fotopoulou, S.; Allevato, V.; Bolzonella, M.; Gruppioni, C.; Pozzetti, L.; Rodighiero, G.; Serjeant, S.; Cunha, P. A.C.; Gabarra, L.; Feltre, A.; Humphrey, A.; La Franca, F.; Landt, H.; Mannucci, F.; Prandoni, I.; Radovich, M.; Ricci, F.; Salvato, M.; Shankar, F.; Stern, D.; Spinoglio, L.; Vergani, D.; Vignali, C.; Zamorani, G.; Yung, L. Y.A.; Charlot, S.; Aghanim, N.; Amara, A.; Andreon, S.; Auricchio, N.; Baldi, M.; Bardelli, S.; Battaglia, P.; Bender, R.; Bonino, D.; Branchini, E.; Brau-Nogue, S.; Brescia, M.; Camera, S.; Capobianco, V.; Carbone, C.; Carretero, J.; Niemi, S. M.; Schneider, P.; Wang, Y.; Gozaliasl, G.; Sánchez, A. G.; , Euclid CollaborationThe Euclid space mission will cover over 14 000 deg2 with two optical and near-infrared spectro-photometric instruments, and is expected to detect around ten million active galactic nuclei (AGN). This unique data set will make a considerable impact on our understanding of galaxy evolution in general, and AGN in particular. For this work we identified the best colour selection criteria for AGN, based only on Euclid photometry or including ancillary photometric observations, such as the data that will be available with the Rubin Legacy Survey of Space and Time (LSST) and observations already available from Spitzer/IRAC. The analysis was performed for unobscured AGN, obscured AGN, and composite (AGN and star-forming) objects. We made use of the spectro-photometric realisations of infrared-selected targets at all-z (SPRITZ) to create mock catalogues mimicking both the Euclid Wide Survey (EWS) and the Euclid Deep Survey (EDS). Using these mock catalogues, we estimated the best colour selection, maximising the harmonic mean (F1) of: (a) completeness, that is, the fraction of AGN correctly selected with respect to the total AGN sample; and (b) purity, that is, the fraction of AGN inside the selection with respect to the selected sample. The selection of unobscured AGN in both Euclid surveys (Wide and Deep) is possible with Euclid photometry alone with F1 = 0.22-0.23 (Wide and Deep), which can increase to F1 = 0.43-0.38 (Wide and Deep) if we limit out study to objects at z > 0.7. Such a selection is improved once the Rubin/LSST filters, that is, a combination of the u, g, r, or z filters, are considered, reaching an F1 score of 0.84 and 0.86 for the EDS and EWS, respectively. The combination of a Euclid colour with the [3.6] - [4.5] colour, which is possible only in the EDS, results in an F1 score of 0.59, improving the results using only Euclid filters, but worse than the selection combining Euclid and LSST colours. The selection of composite (fAGN = 0.05-0.65 at 8-40 μm) and obscured AGN is challenging, with F1 ≤ 0.3 even when including Rubin/LSST or IRAC filters. This is unsurprising since it is driven by the similarities between the broad-band spectral energy distribution of these AGN and star-forming galaxies in the wavelength range 0.3-5 μm. - Euclid preparation : XXXIII. Characterization of convolutional neural networks for the identification of galaxy-galaxy strong-lensing events
A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä(2024-01-01) Leuzzi, L.; Meneghetti, M.; Angora, G.; Metcalf, R. B.; Moscardini, L.; Rosati, P.; Bergamini, P.; Calura, F.; Clément, B.; Gavazzi, R.; Gentile, F.; Lochner, M.; Grillo, C.; Vernardos, G.; Aghanim, N.; Amara, A.; Amendola, L.; Auricchio, N.; Bodendorf, C.; Bonino, D.; Branchini, E.; Brescia, M.; Brinchmann, J.; Camera, S.; Capobianco, V.; Carbone, C.; Carretero, J.; Castellano, M.; Cavuoti, S.; Cimatti, A.; Cledassou, R.; Congedo, G.; Conselice, C. J.; Conversi, L.; Copin, Y.; Corcione, L.; Courbin, F.; Cropper, M.; Da Silva, A.; Degaudenzi, H.; Dinis, J.; Dubath, F.; Dupac, X.; Dusini, S.; Farrens, S.; Niemi, S. M.; Schneider, P.; Wang, Y.; Gozaliasl, G.; Sánchez, A. G.; , Euclid CollaborationForthcoming imaging surveys will increase the number of known galaxy-scale strong lenses by several orders of magnitude. For this to happen, images of billions of galaxies will have to be inspected to identify potential candidates. In this context, deep-learning techniques are particularly suitable for finding patterns in large data sets, and convolutional neural networks (CNNs) in particular can efficiently process large volumes of images. We assess and compare the performance of three network architectures in the classification of strong-lensing systems on the basis of their morphological characteristics. In particular, we implemented a classical CNN architecture, an inception network, and a residual network. We trained and tested our networks on different subsamples of a data set of 40 000 mock images whose characteristics were similar to those expected in the wide survey planned with the ESA mission Euclid, gradually including larger fractions of faint lenses. We also evaluated the importance of adding information about the color difference between the lens and source galaxies by repeating the same training on single- and multiband images. Our models find samples of clear lenses with 90% precision and completeness. Nevertheless, when lenses with fainter arcs are included in the training set, the performance of the three models deteriorates with accuracy values of ~0.87 to ~0.75, depending on the model. Specifically, the classical CNN and the inception network perform similarly in most of our tests, while the residual network generally produces worse results. Our analysis focuses on the application of CNNs to high-resolution space-like images, such as those that the Euclid telescope will deliver. Moreover, we investigated the optimal training strategy for this specific survey to fully exploit the scientific potential of the upcoming observations. We suggest that training the networks separately on lenses with different morphology might be needed to identify the faint arcs. We also tested the relevance of the color information for the detection of these systems, and we find that it does not yield a significant improvement. The accuracy ranges from ~0.89 to ~0.78 for the different models. The reason might be that the resolution of the Euclid telescope in the infrared bands is lower than that of the images in the visual band. - Euclid preparation LI. Forecasting the recovery of galaxy physical properties and their relations with template-fitting and machine-learning methods
A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä(2024-11-01) Enia, A.; Bolzonella, M.; Pozzetti, L.; Humphrey, A.; Cunha, P. A.C.; Hartley, W. G.; Dubath, F.; Paltani, S.; Lopez Lopez, X.; Quai, S.; Bardelli, S.; Bisigello, L.; Cavuoti, S.; De Lucia, G.; Ginolfi, M.; Grazian, A.; Siudek, M.; Tortora, C.; Zamorani, G.; Aghanim, N.; Altieri, B.; Amara, A.; Andreon, S.; Auricchio, N.; Baccigalupi, C.; Baldi, M.; Bender, R.; Bodendorf, C.; Bonino, D.; Branchini, E.; Brescia, M.; Brinchmann, J.; Camera, S.; Capobianco, V.; Carbone, C.; Carretero, J.; Casas, S.; Castander, F. J.; Castellano, M.; Castignani, G.; Cimatti, A.; Colodro-Conde, C.; Congedo, G.; Niemi, S. M.; Schneider, P.; Wang, Y.; Calabrese, M.; Gozaliasl, G.; Hall, A.; Hjorth, J.; , Euclid CollaborationEuclid will collect an enormous amount of data during the mission’s lifetime, observing billions of galaxies in the extragalactic sky. Along with traditional template-fitting methods, numerous machine learning (ML) algorithms have been presented for computing their photometric redshifts and physical parameters (PPs), requiring significantly less computing effort while producing equivalent performance measures. However, their performance is limited by the quality and amount of input information entering the model (the features), to a level where the recovery of some well-established physical relationships between parameters might not be guaranteed – for example, the star-forming main sequence (SFMS). To forecast the reliability of Euclid photo-zs and PPs calculations, we produced two mock catalogs simulating the photometry with the UNIONS ugriz and Euclid filters. We simulated the Euclid Wide Survey (EWS) and Euclid Deep Fields (EDF), alongside two auxiliary fields. We tested the performance of a template-fitting algorithm (Phosphoros) and four ML methods in recovering photo-zs, PPs (stellar masses and star formation rates), and the SFMS on the simulated Euclid fields. To mimic the Euclid processing as closely as possible, the models were trained with Phosphoros-recovered labels and tested on the simulated ground truth. For the EWS, we found that the best results are achieved with a mixed labels approach, training the models with wide survey features and labels from the Phosphoros results on deeper photometry, that is, with the best possible set of labels for a given photometry. This imposes a prior to the input features, helping the models to better discern cases in degenerate regions of feature space, that is, when galaxies have similar magnitudes and colors but different redshifts and PPs, with performance metrics even better than those found with Phosphoros. We found no more than 3% performance degradation using a COSMOS-like reference sample or removing u band data, which will not be available until after data release DR1. The best results are obtained for the EDF, with appropriate recovery of photo-z, PPs, and the SFMS. - Euclid preparation LI. Forecasting the recovery of galaxy physical properties and their relations with template-fitting and machine-learning methods
A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä(2024-11-01) Enia, A.; Bolzonella, M.; Pozzetti, L.; Humphrey, A.; Cunha, P. A.C.; Hartley, W. G.; Dubath, F.; Paltani, S.; Lopez Lopez, X.; Quai, S.; Bardelli, S.; Bisigello, L.; Cavuoti, S.; De Lucia, G.; Ginolfi, M.; Grazian, A.; Siudek, M.; Tortora, C.; Zamorani, G.; Aghanim, N.; Altieri, B.; Amara, A.; Andreon, S.; Auricchio, N.; Baccigalupi, C.; Baldi, M.; Bender, R.; Bodendorf, C.; Bonino, D.; Branchini, E.; Brescia, M.; Brinchmann, J.; Camera, S.; Capobianco, V.; Carbone, C.; Carretero, J.; Casas, S.; Castander, F. J.; Castellano, M.; Castignani, G.; Cimatti, A.; Colodro-Conde, C.; Congedo, G.; Niemi, S. M.; Schneider, P.; Wang, Y.; Calabrese, M.; Gozaliasl, G.; Hall, A.; Hjorth, J.; , Euclid CollaborationEuclid will collect an enormous amount of data during the mission’s lifetime, observing billions of galaxies in the extragalactic sky. Along with traditional template-fitting methods, numerous machine learning (ML) algorithms have been presented for computing their photometric redshifts and physical parameters (PPs), requiring significantly less computing effort while producing equivalent performance measures. However, their performance is limited by the quality and amount of input information entering the model (the features), to a level where the recovery of some well-established physical relationships between parameters might not be guaranteed – for example, the star-forming main sequence (SFMS). To forecast the reliability of Euclid photo-zs and PPs calculations, we produced two mock catalogs simulating the photometry with the UNIONS ugriz and Euclid filters. We simulated the Euclid Wide Survey (EWS) and Euclid Deep Fields (EDF), alongside two auxiliary fields. We tested the performance of a template-fitting algorithm (Phosphoros) and four ML methods in recovering photo-zs, PPs (stellar masses and star formation rates), and the SFMS on the simulated Euclid fields. To mimic the Euclid processing as closely as possible, the models were trained with Phosphoros-recovered labels and tested on the simulated ground truth. For the EWS, we found that the best results are achieved with a mixed labels approach, training the models with wide survey features and labels from the Phosphoros results on deeper photometry, that is, with the best possible set of labels for a given photometry. This imposes a prior to the input features, helping the models to better discern cases in degenerate regions of feature space, that is, when galaxies have similar magnitudes and colors but different redshifts and PPs, with performance metrics even better than those found with Phosphoros. We found no more than 3% performance degradation using a COSMOS-like reference sample or removing u band data, which will not be available until after data release DR1. The best results are obtained for the EDF, with appropriate recovery of photo-z, PPs, and the SFMS. - Euclid preparation XLI. Galaxy power spectrum modelling in real space
A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä(2024-07-01) Pezzotta, A.; Moretti, C.; Zennaro, M.; Dizgah, A. Moradinezhad; Crocce, M.; Sefusatti, E.; Ferrero, I.; Pardede, K.; Eggemeier, A.; Barreira, A.; Angulo, R. E.; Marinucci, M.; Quevedo, B. Camacho; de la Torre, S.; Alkhanishvili, D.; Biagetti, M.; Breton, M. A.; Castorina, E.; D’Amico, G.; Desjacques, V.; Guidi, M.; Kärcher, M.; Oddo, A.; Ibanez, M. Pellejero; Porciani, C.; Pugno, A.; Salvalaggio, J.; Sarpa, E.; Veropalumbo, A.; Vlah, Z.; Amara, A.; Andreon, S.; Auricchio, N.; Baldi, M.; Bardelli, S.; Bender, R.; Bodendorf, C.; Bonino, D.; Branchini, E.; Brescia, M.; Brinchmann, J.; Camera, S.; Capobianco, V.; Carbone, C.; Niemi, S. M.; Schneider, P.; Wang, Y.; Gozaliasl, G.; Hall, A.; Sánchez, A. G.; , Euclid CollaborationWe investigate the accuracy of the perturbative galaxy bias expansion in view of the forthcoming analysis of the Euclid spectroscopic galaxy samples. We compare the performance of a Eulerian galaxy bias expansion using state-of-the-art prescriptions from the effective field theory of large-scale structure (EFTofLSS) with a hybrid approach based on Lagrangian perturbation theory and high-resolution simulations. These models are benchmarked against comoving snapshots of the flagship I N-body simulation at z = (0.9, 1.2, 1.5, 1.8), which have been populated with Hα galaxies leading to catalogues of millions of objects within a volume of about 58 h−3 Gpc3. Our analysis suggests that both models can be used to provide a robust inference of the parameters (h, ωc) in the redshift range under consideration, with comparable constraining power. We additionally determine the range of validity of the EFTofLSS model in terms of scale cuts and model degrees of freedom. From these tests, it emerges that the standard third-order Eulerian bias expansion – which includes local and non-local bias parameters, a matter counter term, and a correction to the shot-noise contribution – can accurately describe the full shape of the real-space galaxy power spectrum up to the maximum wavenumber of kmax = 0.45 hMpc−1, and with a measurement precision of well below the percentage level. Fixing either of the tidal bias parameters to physically motivated relations still leads to unbiased cosmological constraints, and helps in reducing the severity of projection effects due to the large dimensionality of the model. We finally show how we repeated our analysis assuming a volume that matches the expected footprint of Euclid, but without considering observational effects, such as purity and completeness, showing that we can get constraints on the combination (h, ωc) that are consistent with the fiducial values to better than the 68% confidence interval over this range of scales and redshifts. - Euclid preparation XLI. Galaxy power spectrum modelling in real space
A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä(2024-07-01) Pezzotta, A.; Moretti, C.; Zennaro, M.; Dizgah, A. Moradinezhad; Crocce, M.; Sefusatti, E.; Ferrero, I.; Pardede, K.; Eggemeier, A.; Barreira, A.; Angulo, R. E.; Marinucci, M.; Quevedo, B. Camacho; de la Torre, S.; Alkhanishvili, D.; Biagetti, M.; Breton, M. A.; Castorina, E.; D’Amico, G.; Desjacques, V.; Guidi, M.; Kärcher, M.; Oddo, A.; Ibanez, M. Pellejero; Porciani, C.; Pugno, A.; Salvalaggio, J.; Sarpa, E.; Veropalumbo, A.; Vlah, Z.; Amara, A.; Andreon, S.; Auricchio, N.; Baldi, M.; Bardelli, S.; Bender, R.; Bodendorf, C.; Bonino, D.; Branchini, E.; Brescia, M.; Brinchmann, J.; Camera, S.; Capobianco, V.; Carbone, C.; Niemi, S. M.; Schneider, P.; Wang, Y.; Gozaliasl, G.; Hall, A.; Sánchez, A. G.; , Euclid CollaborationWe investigate the accuracy of the perturbative galaxy bias expansion in view of the forthcoming analysis of the Euclid spectroscopic galaxy samples. We compare the performance of a Eulerian galaxy bias expansion using state-of-the-art prescriptions from the effective field theory of large-scale structure (EFTofLSS) with a hybrid approach based on Lagrangian perturbation theory and high-resolution simulations. These models are benchmarked against comoving snapshots of the flagship I N-body simulation at z = (0.9, 1.2, 1.5, 1.8), which have been populated with Hα galaxies leading to catalogues of millions of objects within a volume of about 58 h−3 Gpc3. Our analysis suggests that both models can be used to provide a robust inference of the parameters (h, ωc) in the redshift range under consideration, with comparable constraining power. We additionally determine the range of validity of the EFTofLSS model in terms of scale cuts and model degrees of freedom. From these tests, it emerges that the standard third-order Eulerian bias expansion – which includes local and non-local bias parameters, a matter counter term, and a correction to the shot-noise contribution – can accurately describe the full shape of the real-space galaxy power spectrum up to the maximum wavenumber of kmax = 0.45 hMpc−1, and with a measurement precision of well below the percentage level. Fixing either of the tidal bias parameters to physically motivated relations still leads to unbiased cosmological constraints, and helps in reducing the severity of projection effects due to the large dimensionality of the model. We finally show how we repeated our analysis assuming a volume that matches the expected footprint of Euclid, but without considering observational effects, such as purity and completeness, showing that we can get constraints on the combination (h, ωc) that are consistent with the fiducial values to better than the 68% confidence interval over this range of scales and redshifts. - Euclid preparation XLIII. Measuring detailed galaxy morphologies for Euclid with machine learning
A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä(2024-09-01) Aussel, B.; Kruk, S.; Walmsley, M.; Huertas-Company, M.; Castellano, M.; Conselice, C. J.; Delli Veneri, M.; Domínguez Sánchez, H.; Duc, P. A.; Knapen, J. H.; Kuchner, U.; La Marca, A.; Margalef-Bentabol, B.; Marleau, F. R.; Stevens, G.; Toba, Y.; Tortora, C.; Wang, L.; Aghanim, N.; Altieri, B.; Amara, A.; Andreon, S.; Auricchio, N.; Baldi, M.; Bardelli, S.; Bender, R.; Bodendorf, C.; Bonino, D.; Branchini, E.; Brescia, M.; Brinchmann, J.; Camera, S.; Capobianco, V.; Carbone, C.; Carretero, J.; Casas, S.; Cavuoti, S.; Cimatti, A.; Congedo, G.; Conversi, L.; Copin, Y.; Courbin, F.; Courtois, H. M.; Niemi, S. M.; Schneider, P.; Starck, J. L.; Wang, Y.; Gozaliasl, G.; Hall, A.; Sánchez, A. G.; , Euclid CollaborationThe Euclid mission is expected to image millions of galaxies at high resolution, providing an extensive dataset with which to study galaxy evolution. Because galaxy morphology is both a fundamental parameter and one that is hard to determine for large samples, we investigate the application of deep learning in predicting the detailed morphologies of galaxies in Euclid using Zoobot, a convolutional neural network pretrained with 450 000 galaxies from the Galaxy Zoo project. We adapted Zoobot for use with emulated Euclid images generated based on Hubble Space Telescope COSMOS images and with labels provided by volunteers in the Galaxy Zoo: Hubble project. We experimented with different numbers of galaxies and various magnitude cuts during the training process. We demonstrate that the trained Zoobot model successfully measures detailed galaxy morphology in emulated Euclid images. It effectively predicts whether a galaxy has features and identifies and characterises various features, such as spiral arms, clumps, bars, discs, and central bulges. When compared to volunteer classifications, Zoobot achieves mean vote fraction deviations of less than 12% and an accuracy of above 91% for the confident volunteer classifications across most morphology types. However, the performance varies depending on the specific morphological class. For the global classes, such as disc or smooth galaxies, the mean deviations are less than 10%, with only 1000 training galaxies necessary to reach this performance. On the other hand, for more detailed structures and complex tasks, such as detecting and counting spiral arms or clumps, the deviations are slightly higher, of namely around 12% with 60 000 galaxies used for training. In order to enhance the performance on complex morphologies, we anticipate that a larger pool of labelled galaxies is needed, which could be obtained using crowd sourcing. We estimate that, with our model, the detailed morphology of approximately 800 million galaxies of the Euclid Wide Survey could be reliably measured and that approximately 230 million of these galaxies would display features. Finally, our findings imply that the model can be effectively adapted to new morphological labels. We demonstrate this adaptability by applying Zoobot to peculiar galaxies. In summary, our trained Zoobot CNN can readily predict morphological catalogues for Euclid images. - Euclid preparation XLIII. Measuring detailed galaxy morphologies for Euclid with machine learning
A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä(2024-09-01) Aussel, B.; Kruk, S.; Walmsley, M.; Huertas-Company, M.; Castellano, M.; Conselice, C. J.; Delli Veneri, M.; Domínguez Sánchez, H.; Duc, P. A.; Knapen, J. H.; Kuchner, U.; La Marca, A.; Margalef-Bentabol, B.; Marleau, F. R.; Stevens, G.; Toba, Y.; Tortora, C.; Wang, L.; Aghanim, N.; Altieri, B.; Amara, A.; Andreon, S.; Auricchio, N.; Baldi, M.; Bardelli, S.; Bender, R.; Bodendorf, C.; Bonino, D.; Branchini, E.; Brescia, M.; Brinchmann, J.; Camera, S.; Capobianco, V.; Carbone, C.; Carretero, J.; Casas, S.; Cavuoti, S.; Cimatti, A.; Congedo, G.; Conversi, L.; Copin, Y.; Courbin, F.; Courtois, H. M.; Niemi, S. M.; Schneider, P.; Starck, J. L.; Wang, Y.; Gozaliasl, G.; Hall, A.; Sánchez, A. G.; , Euclid CollaborationThe Euclid mission is expected to image millions of galaxies at high resolution, providing an extensive dataset with which to study galaxy evolution. Because galaxy morphology is both a fundamental parameter and one that is hard to determine for large samples, we investigate the application of deep learning in predicting the detailed morphologies of galaxies in Euclid using Zoobot, a convolutional neural network pretrained with 450 000 galaxies from the Galaxy Zoo project. We adapted Zoobot for use with emulated Euclid images generated based on Hubble Space Telescope COSMOS images and with labels provided by volunteers in the Galaxy Zoo: Hubble project. We experimented with different numbers of galaxies and various magnitude cuts during the training process. We demonstrate that the trained Zoobot model successfully measures detailed galaxy morphology in emulated Euclid images. It effectively predicts whether a galaxy has features and identifies and characterises various features, such as spiral arms, clumps, bars, discs, and central bulges. When compared to volunteer classifications, Zoobot achieves mean vote fraction deviations of less than 12% and an accuracy of above 91% for the confident volunteer classifications across most morphology types. However, the performance varies depending on the specific morphological class. For the global classes, such as disc or smooth galaxies, the mean deviations are less than 10%, with only 1000 training galaxies necessary to reach this performance. On the other hand, for more detailed structures and complex tasks, such as detecting and counting spiral arms or clumps, the deviations are slightly higher, of namely around 12% with 60 000 galaxies used for training. In order to enhance the performance on complex morphologies, we anticipate that a larger pool of labelled galaxies is needed, which could be obtained using crowd sourcing. We estimate that, with our model, the detailed morphology of approximately 800 million galaxies of the Euclid Wide Survey could be reliably measured and that approximately 230 million of these galaxies would display features. Finally, our findings imply that the model can be effectively adapted to new morphological labels. We demonstrate this adaptability by applying Zoobot to peculiar galaxies. In summary, our trained Zoobot CNN can readily predict morphological catalogues for Euclid images. - Euclid preparation XLVI. The near-infrared background dipole experiment with Euclid
A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä(2024-09-01) Kashlinsky, A.; Arendt, R. G.; Ashby, M. L.N.; Atrio-Barandela, F.; Scaramella, R.; Strauss, M. A.; Altieri, B.; Amara, A.; Andreon, S.; Auricchio, N.; Baldi, M.; Bardelli, S.; Bender, R.; Bodendorf, C.; Branchini, E.; Brescia, M.; Brinchmann, J.; Camera, S.; Capobianco, V.; Carbone, C.; Carretero, J.; Casas, S.; Castellano, M.; Cavuoti, S.; Cimatti, A.; Congedo, G.; Conselice, C. J.; Conversi, L.; Copin, Y.; Corcione, L.; Courbin, F.; Courtois, H. M.; Da Silva, A.; Degaudenzi, H.; Di Giorgio, A. M.; Dinis, J.; Dubath, F.; Dupac, X.; Dusini, S.; Ealet, A.; Farina, M.; Farrens, S.; Ferriol, S.; Frailis, M.; Franceschi, E.; Niemi, S. M.; Schneider, P.; Wang, Y.; Gozaliasl, G.; Hall, A.; , Euclid CollaborationVerifying the fully kinematic nature of the long-known cosmic microwave background (CMB) dipole is of fundamental importance in cosmology. In the standard cosmological model with the Friedman–Lemaitre–Robertson–Walker (FLRW) metric from the inflationary expansion, the CMB dipole should be entirely kinematic. Any non-kinematic CMB dipole component would thus reflect the preinflationary structure of space-time probing the extent of the FLRW applicability. Cosmic backgrounds from galaxies after the matter-radiation decoupling should have a kinematic dipole component identical in velocity to the CMB kinematic dipole. Comparing the two can lead to isolating the CMB non-kinematic dipole. It was recently proposed that such a measurement can be done using the near-infrared cosmic infrared background (CIB) measured with the currently operating Euclid telescope, and later with Roman. The proposed method reconstructs the resolved CIB, the integrated galaxy light (IGL), from Euclid’s Wide Survey and probes its dipole with a kinematic component amplified over that of the CMB by the Compton–Getting effect. The amplification coupled with the extensive galaxy samples forming the IGL would determine the CIB dipole with an overwhelming signal-to-noise ratio, isolating its direction to sub-degree accuracy. We developed details of the method for Euclid’s Wide Survey in four bands spanning from 0.6 to 2 µm. We isolated the systematic and other uncertainties and present methodologies to minimize them, after confining the sample to the magnitude range with a negligible IGL–CIB dipole from galaxy clustering. These include the required star–galaxy separation, accounting for the extinction correction dipole using the new method developed here achieving total separation, and accounting for the Earth’s orbital motion and other systematic effects. Finally, we applied the developed methodology to the simulated Euclid galaxy catalogs, successfully testing the upcoming applications. With the techniques presented, one would indeed measure the IGL–CIB dipole from Euclid’s Wide Survey with high precision, probing the non-kinematic CMB dipole. - Euclid preparation XXXIV. The effect of linear redshift-space distortions in photometric galaxy clustering and its cross-correlation with cosmic shear
A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä(2024-03-01) Tanidis, K.; Cardone, V. F.; Martinelli, M.; Tutusaus, I.; Camera, S.; Aghanim, N.; Amara, A.; Andreon, S.; Auricchio, N.; Baldi, M.; Bardelli, S.; Branchini, E.; Brescia, M.; Brinchmann, J.; Capobianco, V.; Carbone, C.; Carretero, J.; Casas, S.; Castellano, M.; Cavuoti, S.; Cimatti, A.; Cledassou, R.; Congedo, G.; Conversi, L.; Copin, Y.; Corcione, L.; Courbin, F.; Courtois, H. M.; Da Silvay, A.; Degaudenzi, H.; Dinis, J.; Dubath, F.; Dupac, X.; Dusini, S.; Farina, M.; Farrens, S.; Ferriol, S.; Fosalba, P.; Frailis, M.; Franceschi, E.; Fumana, M.; Galeotta, S.; Garilli, B.; Gillard, W.; Gillis, B.; Niemi, S. M.; Schneider, P.; Wang, Y.; Gozaliasl, G.; Sánchez, A. G.; , Euclid CollaborationContext. The cosmological surveys that are planned for the current decade will provide us with unparalleled observations of the distribution of galaxies on cosmic scales, by means of which we can probe the underlying large-scale structure (LSS) of the Universe. This will allow us to test the concordance cosmological model and its extensions. However, precision pushes us to high levels of accuracy in the theoretical modelling of the LSS observables, so that no biases are introduced into the estimation of the cosmological parameters. In particular, effects such as redshift-space distortions (RSD) can become relevant in the computation of harmonic-space power spectra even for the clustering of the photometrically selected galaxies, as has previously been shown in literature. Aims. In this work, we investigate the contribution of linear RSD, as formulated in the Limber approximation by a previous work, in forecast cosmological analyses with the photometric galaxy sample of the Euclid survey. We aim to assess their impact and to quantify the bias on the measurement of cosmological parameters that would be caused if this effect were neglected. Methods. We performed this task by producing mock power spectra for photometric galaxy clustering and weak lensing, as is expected to be obtained from the Euclid survey. We then used a Markov chain Monte Carlo approach to obtain the posterior distributions of cosmological parameters from these simulated observations. Results. When the linear RSD is neglected, significant biases are caused when galaxy correlations are used alone and when they are combined with cosmic shear in the so-called 3 × 2 pt approach. These biases can be equivalent to as much as 5σ when an underlying ΛCDM cosmology is assumed. When the cosmological model is extended to include the equation-of-state parameters of dark energy, the extension parameters can be shifted by more than 1σ. - Euclid preparation XXXIV. The effect of linear redshift-space distortions in photometric galaxy clustering and its cross-correlation with cosmic shear
A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä(2024-03-01) Tanidis, K.; Cardone, V. F.; Martinelli, M.; Tutusaus, I.; Camera, S.; Aghanim, N.; Amara, A.; Andreon, S.; Auricchio, N.; Baldi, M.; Bardelli, S.; Branchini, E.; Brescia, M.; Brinchmann, J.; Capobianco, V.; Carbone, C.; Carretero, J.; Casas, S.; Castellano, M.; Cavuoti, S.; Cimatti, A.; Cledassou, R.; Congedo, G.; Conversi, L.; Copin, Y.; Corcione, L.; Courbin, F.; Courtois, H. M.; Da Silvay, A.; Degaudenzi, H.; Dinis, J.; Dubath, F.; Dupac, X.; Dusini, S.; Farina, M.; Farrens, S.; Ferriol, S.; Fosalba, P.; Frailis, M.; Franceschi, E.; Fumana, M.; Galeotta, S.; Garilli, B.; Gillard, W.; Gillis, B.; Niemi, S. M.; Schneider, P.; Wang, Y.; Gozaliasl, G.; Sánchez, A. G.; , Euclid CollaborationContext. The cosmological surveys that are planned for the current decade will provide us with unparalleled observations of the distribution of galaxies on cosmic scales, by means of which we can probe the underlying large-scale structure (LSS) of the Universe. This will allow us to test the concordance cosmological model and its extensions. However, precision pushes us to high levels of accuracy in the theoretical modelling of the LSS observables, so that no biases are introduced into the estimation of the cosmological parameters. In particular, effects such as redshift-space distortions (RSD) can become relevant in the computation of harmonic-space power spectra even for the clustering of the photometrically selected galaxies, as has previously been shown in literature. Aims. In this work, we investigate the contribution of linear RSD, as formulated in the Limber approximation by a previous work, in forecast cosmological analyses with the photometric galaxy sample of the Euclid survey. We aim to assess their impact and to quantify the bias on the measurement of cosmological parameters that would be caused if this effect were neglected. Methods. We performed this task by producing mock power spectra for photometric galaxy clustering and weak lensing, as is expected to be obtained from the Euclid survey. We then used a Markov chain Monte Carlo approach to obtain the posterior distributions of cosmological parameters from these simulated observations. Results. When the linear RSD is neglected, significant biases are caused when galaxy correlations are used alone and when they are combined with cosmic shear in the so-called 3 × 2 pt approach. These biases can be equivalent to as much as 5σ when an underlying ΛCDM cosmology is assumed. When the cosmological model is extended to include the equation-of-state parameters of dark energy, the extension parameters can be shifted by more than 1σ. - Euclid preparation XXXVII. Galaxy colour selections with Euclid and ground photometry for cluster weak-lensing analyses
A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä(2024-04-01) Lesci, G. F.; Sereno, M.; Radovich, M.; Castignani, G.; Bisigello, L.; Marulli, F.; Moscardini, L.; Baumont, L.; Covone, G.; Farrens, S.; Giocoli, C.; Ingoglia, L.; Miranda La Hera, S.; Vannier, M.; Biviano, A.; Maurogordato, S.; Aghanim, N.; Amara, A.; Andreon, S.; Auricchio, N.; Baldi, M.; Bardelli, S.; Bender, R.; Bodendorf, C.; Bonino, D.; Branchini, E.; Brescia, M.; Brinchmann, J.; Camera, S.; Capobianco, V.; Carbone, C.; Carretero, J.; Casas, S.; Castander, F. J.; Castellano, M.; Cavuoti, S.; Cimatti, A.; Congedo, G.; Conselice, C. J.; Conversi, L.; Copin, Y.; Corcione, L.; Courbin, F.; Courtois, H. M.; Niemi, S. M.; Schneider, P.; Starck, J. L.; Wang, Y.; Gozaliasl, G.; Sánchez, A. G.; , Euclid CollaborationAims. We derived galaxy colour selections from Euclid and ground-based photometry, aiming to accurately define background galaxy samples in cluster weak-lensing analyses. These selections have been implemented in the Euclid data analysis pipelines for galaxy clusters. Methods. Given any set of photometric bands, we developed a method for the calibration of optimal galaxy colour selections that maximises the selection completeness, given a threshold on purity. Such colour selections are expressed as a function of the lens redshift. Results. We calibrated galaxy selections using simulated ground-based griz and Euclid YEJEHE photometry. Both selections produce a purity higher than 97%. The griz selection completeness ranges from 30% to 84% in the lens redshift range zl ∈ [0.2, 0.8]. With the full grizYEJEHE selection, the completeness improves by up to 25 percentage points, and the zl range extends up to zl = 1.5. The calibrated colour selections are stable to changes in the sample limiting magnitudes and redshift, and the selection based on griz bands provides excellent results on real external datasets. Furthermore, the calibrated selections provide stable results using alternative photometric aperture definitions obtained from different ground-based telescopes. The griz selection is also purer at high redshift and more complete at low redshift compared to colour selections found in the literature. We find excellent agreement in terms of purity and completeness between the analysis of an independent, simulated Euclid galaxy catalogue and our calibration sample, except for galaxies at high redshifts, for which we obtain up to 50 percentage points higher completeness. The combination of colour and photo-z selections applied to simulated Euclid data yields up to 95% completeness, while the purity decreases down to 92% at high zl. We show that the calibrated colour selections provide robust results even when observations from a single band are missing from the ground-based data. Finally, we show that colour selections do not disrupt the shear calibration for stage III surveys. The first Euclid data releases will provide further insights into the impact of background selections on the shear calibration. - Euclid preparation XXXVII. Galaxy colour selections with Euclid and ground photometry for cluster weak-lensing analyses
A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä(2024-04-01) Lesci, G. F.; Sereno, M.; Radovich, M.; Castignani, G.; Bisigello, L.; Marulli, F.; Moscardini, L.; Baumont, L.; Covone, G.; Farrens, S.; Giocoli, C.; Ingoglia, L.; Miranda La Hera, S.; Vannier, M.; Biviano, A.; Maurogordato, S.; Aghanim, N.; Amara, A.; Andreon, S.; Auricchio, N.; Baldi, M.; Bardelli, S.; Bender, R.; Bodendorf, C.; Bonino, D.; Branchini, E.; Brescia, M.; Brinchmann, J.; Camera, S.; Capobianco, V.; Carbone, C.; Carretero, J.; Casas, S.; Castander, F. J.; Castellano, M.; Cavuoti, S.; Cimatti, A.; Congedo, G.; Conselice, C. J.; Conversi, L.; Copin, Y.; Corcione, L.; Courbin, F.; Courtois, H. M.; Niemi, S. M.; Schneider, P.; Starck, J. L.; Wang, Y.; Gozaliasl, G.; Sánchez, A. G.; , Euclid CollaborationAims. We derived galaxy colour selections from Euclid and ground-based photometry, aiming to accurately define background galaxy samples in cluster weak-lensing analyses. These selections have been implemented in the Euclid data analysis pipelines for galaxy clusters. Methods. Given any set of photometric bands, we developed a method for the calibration of optimal galaxy colour selections that maximises the selection completeness, given a threshold on purity. Such colour selections are expressed as a function of the lens redshift. Results. We calibrated galaxy selections using simulated ground-based griz and Euclid YEJEHE photometry. Both selections produce a purity higher than 97%. The griz selection completeness ranges from 30% to 84% in the lens redshift range zl ∈ [0.2, 0.8]. With the full grizYEJEHE selection, the completeness improves by up to 25 percentage points, and the zl range extends up to zl = 1.5. The calibrated colour selections are stable to changes in the sample limiting magnitudes and redshift, and the selection based on griz bands provides excellent results on real external datasets. Furthermore, the calibrated selections provide stable results using alternative photometric aperture definitions obtained from different ground-based telescopes. The griz selection is also purer at high redshift and more complete at low redshift compared to colour selections found in the literature. We find excellent agreement in terms of purity and completeness between the analysis of an independent, simulated Euclid galaxy catalogue and our calibration sample, except for galaxies at high redshifts, for which we obtain up to 50 percentage points higher completeness. The combination of colour and photo-z selections applied to simulated Euclid data yields up to 95% completeness, while the purity decreases down to 92% at high zl. We show that the calibrated colour selections provide robust results even when observations from a single band are missing from the ground-based data. Finally, we show that colour selections do not disrupt the shear calibration for stage III surveys. The first Euclid data releases will provide further insights into the impact of background selections on the shear calibration. - Euclid preparation. LII. Forecast impact of super-sample covariance on 3A- 2pt analysis with Euclid
A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä(2024-11-01) Sciotti, D.; Gouyou Beauchamps, S.; Cardone, V. F.; Camera, S.; Tutusaus, I.; Lacasa, F.; Barreira, A.; Bonici, M.; Gorce, A.; Aubert, M.; Baratta, P.; Upham, R. E.; Carbone, C.; Casas, S.; Iliac, S.; Martinelli, M.; Sakr, Z.; Schneider, A.; Maoli, R.; Scaramella, R.; Escoffier, S.; Gillard, W.; Aghanim, N.; Amara, A.; Andreon, S.; Auricchio, N.; Baccigalupi, C.; Baldi, M.; Bardelli, S.; Bernardeau, F.; Bonino, D.; Branchini, E.; Brescia, M.; Brinchmann, J.; Capobianco, V.; Carretero, J.; Castander, F. J.; Castellano, M.; Castignani, G.; Cavuoti, S.; Cimatti, A.; Cledassou, R.; Colodro-Conde, C.; Congedo, G.; Niemi, S. M.; Sánchez, A. G.; Schneider, P.; Starck, J. L.; Wang, Y.; Gozaliasl, G.; , Euclid CollaborationContext. Deviations from Gaussianity in the distribution of the fields probed by large-scale structure surveys generate additional terms in the data covariance matrix, increasing the uncertainties in the measurement of the cosmological parameters. Super-sample covariance (SSC) is among the largest of these non-Gaussian contributions, with the potential to significantly degrade constraints on some of the parameters of the cosmological model under study - especially for weak-lensing cosmic shear. Aims. We compute and validate the impact of SSC on the forecast uncertainties on the cosmological parameters for the Euclid photo-metric survey, and investigate how its impact depends on the specific details of the forecast. Methods. We followed the recipes outlined by the Euclid Collaboration (EC) to produce 1 constraints through a Fisher matrix analysis, considering the Gaussian covariance alone and adding the SSC term, which is computed through the public code PySSC. The constraints are produced both by using Euclid's photometric probes in isolation and by combining them in the '3A- 2pt'analysis. Results. We meet EC requirements on the forecasts validation, with an agreement at the 10% level between the mean results of the two pipelines considered, and find the SSC impact to be non-negligible - halving the figure of merit (FoM) of the dark energy parameters (w0, wa) in the 3A- 2pt case and substantially increasing the uncertainties on Ωm,0,w0, w0, and 8 for the weak-lensing probe. We find photometric galaxy clustering to be less affected as a consequence of the lower probe response. The relative impact of SSC, while highly dependent on the number and type of nuisance parameters varied in the analysis, does not show significant changes under variations of the redshift binning scheme. Finally, we explore how the use of prior information on the shear and galaxy bias changes the impact of SSC. We find that improving shear bias priors has no significant influence, while galaxy bias must be calibrated to a subpercent level in order to increase the FoM by the large amount needed to achieve the value when SSC is not included. - Euclid preparation. LIII. LensMC, weak lensing cosmic shear measurement with forward modelling and Markov Chain Monte Carlo sampling
A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä(2024-11-01) Congedo, G.; Miller, L.; Taylor, A. N.; Cross, N.; Duncan, C. A.J.; Kitching, T.; Martinet, N.; Matthew, S.; Schrabback, T.; Tewes, M.; Welikala, N.; Aghanim, N.; Amara, A.; Andreon, S.; Auricchio, N.; Baldi, M.; Bardelli, S.; Bender, R.; Bodendorf, C.; Bonino, D.; Branchini, E.; Brescia, M.; Brinchmann, J.; Camera, S.; Capobianco, V.; Carbone, C.; Cardone, V. F.; Carretero, J.; Casas, S.; Castander, F. J.; Castellano, M.; Cavuoti, S.; Cimatti, A.; Conselice, C. J.; Conversi, L.; Copin, Y.; Courbin, F.; Courtois, H. M.; Cropper, M.; Da Silva, A.; Degaudenzi, H.; Di Giorgio, A. M.; Dinis, J.; Dubath, F.; Niemi, S. M.; Schneider, P.; Wang, Y.; Gozaliasl, G.; Hall, A.; Sánchez, A. G.; , Euclid CollaborationLENSMC is a weak lensing shear measurement method developed for Euclid and Stage-IV surveys. It is based on forward modelling in order to deal with convolution by a point spread function (PSF) with comparable size to many galaxies, sampling the posterior distribution of galaxy parameters via Markov chain Monte Carlo, and marginalisation over nuisance parameters for each of the 1.5 billion galaxies observed by Euclid. We quantified the scientific performance through high-fidelity images based on the Euclid Flagship simulations and emulation of the Euclid VIS images, realistic clustering with a mean surface number density of 250 arcmin2 (IE < 29.5) for galaxies, and 6 arcmin2 (IE < 26) for stars, and a diffraction-limited chromatic PSF with a full width at half maximum of 02.22 and spatial variation across the field of view. LENSMC measured objects with a density of 90 arcmin2 (IE < 26.5) in 4500 deg2. The total shear bias was broken down into measurement (our main focus here) and selection effects (which will be addressed in future work). We found measurement multiplicative and additive biases of m1 = (3.6 ± 0.2) A- 103, m2 = (4.3 ± 0.2) A- 103, c1 = (1.78 ± 0.03) A- 104, and c2 = (0.09 ± 0.03) A- 104; a large detection bias with a multiplicative component of 1.2 A- 102 and an additive component of 3 A- 104; and a measurement PSF leakage of α1 = (9 ± 3) A- 104 and α2 = (2 ± 3) A- 104. When model bias is suppressed, the obtained measurement biases are close to Euclid requirement and largely dominated by undetected faint galaxies (5 A- 103). Although significant, model bias will be straightforward to calibrate given its weak sensitivity on galaxy morphology parameters. LENSMC is publicly available at gitlab.com/gcongedo/LensMC. - Euclid preparation. LIII. LensMC, weak lensing cosmic shear measurement with forward modelling and Markov Chain Monte Carlo sampling
A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä(2024-11-01) Congedo, G.; Miller, L.; Taylor, A. N.; Cross, N.; Duncan, C. A.J.; Kitching, T.; Martinet, N.; Matthew, S.; Schrabback, T.; Tewes, M.; Welikala, N.; Aghanim, N.; Amara, A.; Andreon, S.; Auricchio, N.; Baldi, M.; Bardelli, S.; Bender, R.; Bodendorf, C.; Bonino, D.; Branchini, E.; Brescia, M.; Brinchmann, J.; Camera, S.; Capobianco, V.; Carbone, C.; Cardone, V. F.; Carretero, J.; Casas, S.; Castander, F. J.; Castellano, M.; Cavuoti, S.; Cimatti, A.; Conselice, C. J.; Conversi, L.; Copin, Y.; Courbin, F.; Courtois, H. M.; Cropper, M.; Da Silva, A.; Degaudenzi, H.; Di Giorgio, A. M.; Dinis, J.; Dubath, F.; Niemi, S. M.; Schneider, P.; Wang, Y.; Gozaliasl, G.; Hall, A.; Sánchez, A. G.; , Euclid CollaborationLENSMC is a weak lensing shear measurement method developed for Euclid and Stage-IV surveys. It is based on forward modelling in order to deal with convolution by a point spread function (PSF) with comparable size to many galaxies, sampling the posterior distribution of galaxy parameters via Markov chain Monte Carlo, and marginalisation over nuisance parameters for each of the 1.5 billion galaxies observed by Euclid. We quantified the scientific performance through high-fidelity images based on the Euclid Flagship simulations and emulation of the Euclid VIS images, realistic clustering with a mean surface number density of 250 arcmin2 (IE < 29.5) for galaxies, and 6 arcmin2 (IE < 26) for stars, and a diffraction-limited chromatic PSF with a full width at half maximum of 02.22 and spatial variation across the field of view. LENSMC measured objects with a density of 90 arcmin2 (IE < 26.5) in 4500 deg2. The total shear bias was broken down into measurement (our main focus here) and selection effects (which will be addressed in future work). We found measurement multiplicative and additive biases of m1 = (3.6 ± 0.2) A- 103, m2 = (4.3 ± 0.2) A- 103, c1 = (1.78 ± 0.03) A- 104, and c2 = (0.09 ± 0.03) A- 104; a large detection bias with a multiplicative component of 1.2 A- 102 and an additive component of 3 A- 104; and a measurement PSF leakage of α1 = (9 ± 3) A- 104 and α2 = (2 ± 3) A- 104. When model bias is suppressed, the obtained measurement biases are close to Euclid requirement and largely dominated by undetected faint galaxies (5 A- 103). Although significant, model bias will be straightforward to calibrate given its weak sensitivity on galaxy morphology parameters. LENSMC is publicly available at gitlab.com/gcongedo/LensMC.