Search

We reanalyse observations of type Ia supernovae (SNe) and Cepheids used in the local determination of the Hubble constant and find strong evidence that SN standardisation in the calibration sample (galaxies with observed Cepheids) require a steeper slope of the colour correction than in the cosmological sample (galaxies in the Hubble flow). The colour correction in the calibration sample is consistent with being entirely due to an extinction correction due to dust with properties similar to that of the Milky Way (R_B~4.6+/-0.4) and there is no evidence for intrinsic scatter in the SN peak magnitudes. An immediate consequence of this finding is that the local measurement of the Hubble constant becomes dependent on the choice of SN reference colour, i.e., the colour of an unreddened SN. Specifically, the Hubble constant inferred from the same observations decreases gradually with the reference colour assumed in the SN standardisation. We recover the Hubble constant measured by SH0ES for the standard choice of reference colour (SALT2 colour parameter c=0) while for a reference colour which coincides with the blue end of the observed SN colour distribution (c~-0.13), the Hubble constant from Planck observations of the CMB (assuming a flat LCDM cosmological model) is recovered. These results are intriguing in that they may provide an avenue for resolving the Hubble tension. However, since there is no obvious physical basis for the differences in colour corrections in the two SN samples, the origin of these require further investigations., Comment: 12 pages, 4 figures, 3 tables; accepted for publication in MNRAS

Gravitationally lensed Type Ia supernovae are an emerging probe with great potential for constraining dark energy, spatial curvature, and the Hubble constant. The multiple images and their time delayed and magnified fluxes may be unresolved, however, blended into a single lightcurve. We demonstrate methods without a fixed source template matching for extracting the individual images, determining whether there are one (no lensing) or two or four (lensed) images, and measuring the time delays between them that are valuable cosmological probes. We find 100% success for determining the number of images for time delays greater than $\sim10$ days., 9 pages, 6 figures; matches version published in MNRAS

Blind cleaning methods are currently the preferred strategy for handling foreground contamination in single-dish HI intensity mapping surveys. Despite the increasing sophistication of blind techniques, some signal loss will be inevitable across all scales. Constructing a corrective transfer function using mock signal injection into the contaminated data has been a practice relied on for HI intensity mapping experiments. However, assessing whether this approach is viable for future intensity mapping surveys where precision cosmology is the aim, remains unexplored. In this work, using simulations, we validate for the first time the use of a foreground transfer function to reconstruct power spectra of foreground-cleaned low-redshift intensity maps and look to expose any limitations. We reveal that even when aggressive foreground cleaning is required, which causes ${>}\,50\%$ negative bias on the largest scales, the power spectrum can be reconstructed using a transfer function to within sub-percent accuracy. We specifically outline the recipe for constructing an unbiased transfer function, highlighting the pitfalls if one deviates from this recipe, and also correctly identify how a transfer function should be applied in an auto-correlation power spectrum. We validate a method that utilises the transfer function variance for error estimation in foreground-cleaned power spectra. Finally, we demonstrate how incorrect fiducial parameter assumptions (up to ${\pm}100\%$ bias) in the generation of mocks, used in the construction of the transfer function, do not significantly bias signal reconstruction or parameter inference (inducing ${, 25 pages, 20 figures. See Figure 4 for the main demonstration of the transfer function's performance for reconstructing signal loss from foreground cleaning. Accepted for publication in MNRAS

Full list of authors: Lan, Ting-Wen; Tojeiro, R.; Armengaud, E.; Prochaska, J. Xavier; Davis, T. M.; Alexander, David M.; Raichoor, A.; Zhou, Rongpu; Yeche, Christophe; Balland, C.; BenZvi, S.; Berti, A.; Canning, R.; Carr, A.; Chittenden, H.; Cole, S.; Cousinou, M. -c.; Dawson, K.; Dey, Biprateep; Douglass, K.; Edge, A.; Escoffier, S.; Glanville, A.; Gontcho, S. Gontcho; Guy, J.; Hahn, C.; Howlett, C.; Hwang, Ho Seong; Jiang, L.; Kovacs, A.; Mezcua, M.; Moore, S.; Nadathur, S.; Oh, M.; Parkinson, D.; Rocher, A.; Ross, A. J.; Ruhlmann-Kleider, V.; Sabiu, C. G.; Said, K.; Saulder, C.; Sierra-Porta, D.; Weiner, B.; Yu, J.; Zarrouk, P.; Zhang, Y.; Zou, H.; Ahlen, S.; Bailey, S.; Brooks, D.; Cooper, A. P.; de la Macorra, A.; Dey, A.; Dhungana, G.; Doel, P.; Eftekharzadeh, S.; Fanning, K.; Font-Ribera, A.; Garrison, L.; Gaztanaga, E.; Kehoe, R.; Kisner, T.; Kremin, A.; Landriau, M.; Le Guillou, L.; Levi, Michael E.; Magneville, C.; Meisner, Aaron M.; Miquel, R.; Moustakas, J.; Myers, Adam D.; Newman, Jeffrey A.; Nie, J. D.; Palanque-Delabrouille, N.; Percival, W. J.; Poppett, C.; Prada, F.; Schubnell, M.; Tarle, Gregory; Weaver, B. A.; Zhang, K.; Zhou, Zhimin.--This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited., The Dark Energy Spectroscopic Instrument (DESI) Survey has obtained a set of spectroscopic measurements of galaxies to validate the final survey design and target selections. To assist in these tasks, we visually inspect DESI spectra of approximately 2500 bright galaxies, 3500 luminous red galaxies (LRGs), and 10,000 emission-line galaxies (ELGs) to obtain robust redshift identifications. We then utilize the visually inspected redshift information to characterize the performance of the DESI operation. Based on the visual inspection (VI) catalogs, our results show that the final survey design yields samples of bright galaxies, LRGs, and ELGs with purity greater than 99%. Moreover, we demonstrate that the precision of the redshift measurements is approximately 10 km s−1 for bright galaxies and ELGs and approximately 40 km s−1 for LRGs. The average redshift accuracy is within 10 km s−1 for the three types of galaxies. The VI process also helps improve the quality of the DESI data by identifying spurious spectral features introduced by the pipeline. Finally, we show examples of unexpected real astronomical objects, such as Lyα emitters and strong lensing candidates, identified by VI. These results demonstrate the importance and utility of visually inspecting data from incoming and upcoming surveys, especially during their early operation phases. © 2023. The Author(s). Published by the American Astronomical Society., W.L. is supported by the Ministry of Science and Technology (MOST 111-2112-M-002-015-MY3), the Ministry of Education, Taiwan (MOE Yushan Young Scholar grant Nos. NTU-110VV007 and NTU-110VV007-2), National Taiwan University research grant Nos. NTU-CC-111L894806, NTU-111L7318, and NTU-112L7302 and NSF grant No. AST-1911140. D.M.A. acknowledges the Science Technology and Facilities Council (STFC) for support through grant No. ST/T000244/1. This research is supported by the Director, Office of Science, Office of High Energy Physics of the U.S. Department of Energy under contract No. DE-AC02-05CH11231, and by the National Energy Research Scientific Computing Center, a DOE Office of Science User Facility under the same contract; additional support for DESI is provided by the U.S. National Science Foundation, Division of Astronomical Sciences under contract No. AST-0950945 to the NSF's National Optical-Infrared Astronomy Research Laboratory; the Science and Technologies Facilities Council of the United Kingdom; the Gordon and Betty Moore Foundation; the Heising-Simons Foundation; the French Alternative Energies and Atomic Energy Commission (CEA); the National Council of Science and Technology of Mexico (CONACYT); the Ministry of Science and Innovation of Spain (MICINN), and by the DESI Member Institutions: https://www.desi.lbl.gov/collaborating-institutions., With funding from the Spanish government through the "Severo Ochoa Centre of Excellence" accreditation (CEX2021-001131-S).

The various Euclid imaging surveys will become a reference for studies of galaxy morphology by delivering imaging over an unprecedented area of 15 000 square degrees with high spatial resolution. In order to understand the capabilities of measuring morphologies from Euclid-detected galaxies and to help implement measurements in the pipeline, we have conducted the Euclid Morphology Challenge, which we present in two papers. While the companion paper by Merlin et al. focuses on the analysis of photometry, this paper assesses the accuracy of the parametric galaxy morphology measurements in imaging predicted from within the Euclid Wide Survey. We evaluate the performance of five state-of-the-art surface-brightness-fitting codes DeepLeGATo, Galapagos-2, Morfometryka, Profit and SourceXtractor++ on a sample of about 1.5 million simulated galaxies resembling reduced observations with the Euclid VIS and NIR instruments. The simulations include analytic S\'ersic profiles with one and two components, as well as more realistic galaxies generated with neural networks. We find that, despite some code-specific differences, all methods tend to achieve reliable structural measurements (10% scatter on ideal S\'ersic simulations) down to an apparent magnitude of about 23 in one component and 21 in two components, which correspond to a signal-to-noise ratio of approximately 1 and 5 respectively. We also show that when tested on non-analytic profiles, the results are typically degraded by a factor of 3, driven by systematics. We conclude that the Euclid official Data Releases will deliver robust structural parameters for at least 400 million galaxies in the Euclid Wide Survey by the end of the mission. We find that a key factor for explaining the different behaviour of the codes at the faint end is the set of adopted priors for the various structural parameters., Comment: Accepted by A&A. 30 pages, 23+6 figures, Euclid pre-launch key paper. Companion paper: Euclid Collaboration XXV: Merlin et al. 2022 Minor corrections after journal review

WEAVE, the new wide-field, massively multiplexed spectroscopic survey facility for the William Herschel Telescope, will see first light in late 2022. WEAVE comprises a new 2-degree field-of-view prime-focus corrector system, a nearly 1000-multiplex fibre positioner, 20 individually deployable 'mini' integral field units (IFUs), and a single large IFU. These fibre systems feed a dual-beam spectrograph covering the wavelength range 366$-$959\,nm at $R\sim5000$, or two shorter ranges at $R\sim20\,000$. After summarising the design and implementation of WEAVE and its data systems, we present the organisation, science drivers and design of a five- to seven-year programme of eight individual surveys to: (i) study our Galaxy's origins by completing Gaia's phase-space information, providing metallicities to its limiting magnitude for $\sim$3 million stars and detailed abundances for $\sim1.5$ million brighter field and open-cluster stars; (ii) survey $\sim0.4$ million Galactic-plane OBA stars, young stellar objects and nearby gas to understand the evolution of young stars and their environments; (iii) perform an extensive spectral survey of white dwarfs; (iv) survey $\sim400$ neutral-hydrogen-selected galaxies with the IFUs; (v) study properties and kinematics of stellar populations and ionised gas in $z1$ million spectra of LOFAR-selected radio sources; (viii) trace structures using intergalactic/circumgalactic gas at $z>2$. Finally, we describe the WEAVE Operational Rehearsals using the WEAVE Simulator., 41 pages, 27 figures, accepted for publication by MNRAS

Support by grant 2020750 from the United States- Israel Binational Science Foundation (BSF) and grant 2109066 from the United States National Science Foundation (NSF), and by the Ministry of Science and Technology, Israel. J.C. acknowl- edges funding from the ‘FirstGalaxies’ Advanced Grant from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation program (Grant agreement No. 789056). E.C.L. acknowledges support of an STFC Webb Fellowship (ST/W001438/1). K.K. acknowledges the support by JSPS KAKENHI Grant Number JP17H06130 and the NAOJ ALMA Scientific Research Grant Number 2017–06B. D.E. acknowledges support from a Beatriz Galindo senior fellowship (BG20/00224) from the Spanish Ministry of Science and Innovation, projects PID2020-114414GB-100 and PID2020-113689GB-I00 financed by MCIN/AEI/10.13039/501100011033, project P20-00334 financed by the Junta de Andaluc´ıa, and project A-FQM-510-UGR20 of the FEDER/Junta de Andaluc´ıa-Consejer´ıa de Transformaci ´on Econ ´omica, Industria, Conocimiento y Universidades. G.E.M. ac- knowledges financial support from the Villum Young Investiga- tor grant 37440 and 13160 and the The Cosmic Dawn Center (DAWN), funded by the Danish National Research Foundation under grant No. 140. F.E.B. acknowledges support from ANID- Chile BASAL CATA FB210003, FONDECYT Regular 1200495 and 1190818, and Millennium Science Initiative Program–ICN12 009. K.K.K. acknowledges support from the Knut and Alice Wallenberg Foundation., We report the discovery of a triply imaged active galactic nucleus (AGN), lensed by the galaxy cluster MACS J0035.4−2015 (z d = 0.352). The object is detected in Hubble Space Telescope imaging taken for the RELICS program. It appears to have a quasi-stellar nucleus consistent with a point-source, with a de-magnified radius of re ≲ 100 pc. The object is spectroscopically confirmed to be an AGN at z spec = 2.063 ± 0.005 showing broad rest-frame UV emission lines, and detected in both X-ray observations with Chandra and in ALCS ALMA band 6 (1.2 mm) imaging. It has a relatively faint rest-frame UV luminosity for a quasar-like object, MUV, 1450 = −19.7 ± 0.2. The object adds to just a few quasars or other X-ray sources known to be multiply lensed by a galaxy cluster. Some diffuse emission from the host galaxy is faintly seen around the nucleus, and there is a faint object nearby sharing the same multiple-imaging symmetry and geometric redshift, possibly an interacting galaxy or a star-forming knot in the host. We present an accompanying lens model, calculate the magnifications and time delays, and infer the physical properties of the source. We find the rest-frame UV continuum and emission lines to be dominated by the AGN, and the optical emission to be dominated by the host galaxy of modest stellar mass M✶ ≃ 109.2 M⊙. We also observe some variation in the AGN emission with time, which may suggest that the AGN used to be more active. This object adds a low-redshift counterpart to several relatively faint AGN recently uncovered at high redshifts with HST and JWST., Horizon 2020 Framework Programme H2020, Consejería de Transformación Económica, Industria, Conocimiento y Universidades 13160, 37440, Science and Technology Facilities Council ST/W001438/1 STFC, European Research Council ERC, Fondo Nacional de Desarrollo Científico y Tecnológico 1190818, 1200495, ICN12_009 FONDECYT, Ministerio de Ciencia e Innovación MCIN/AEI/10.13039/501100011033, P20-00334, PID2020-113689GB-I00, PID2020-114414GB-100 MICINN, Horizon 2020 789056, European Regional Development Fund ERDF, Junta de Andalucía A-FQM-510-UGR20

We characterize the selection cuts and clustering properties of a magnitude-limited sample of bright galaxies that is part of the Bright Galaxy Survey (BGS) of the Dark Energy Spectroscopic Instrument (DESI) using the ninth data release of the Legacy Imaging Surveys (DR9). We describe changes in the DR9 selection compared to the DR8 one and we also compare the DR9 selection in three distinct regions: BASS/MzLS in the north Galactic Cap (NGC), DECaLS in the NGC, and DECaLS in the south Galactic Cap (SGC). We investigate the systematics associated with the selection and assess its completeness by matching the BGS targets with the Galaxy and Mass Assembly (GAMA) survey. We measure the angular clustering for the overall bright sample (rmag ≤ 19.5) and as function of apparent magnitude and colour. This enables to determine the clustering strength r0 and slope γ by fitting a power-law model that can be used to generate accurate mock catalogues for this tracer. We use a counts-in-cells technique to explore higher order statistics and cross-correlations with external spectroscopic data sets in order to check the evolution of the clustering with redshift and the redshift distribution of the BGS targets using clustering redshifts. While this work validates the properties of the BGS bright targets, the final target selection pipeline and clustering properties of the entire DESI BGS will be fully characterized and validated with the spectroscopic data of Survey Validation. © 2021 The Author(s)., PZ, OR-M, SC, PN, and CB acknowledge support from the Science Technology Facilities Council through ST/P000541/1 andST/T000244/1. OR-M is supported by the Mexican National Council of Science and Technology (CONACyT) through grant No. 297228/440775 and funding from the European Union’s Horizon 2020 Research and Innovation Programme under the Marie Sklodowska-Curie grant agreement No 734374. JM gratefully acknowledges support from the U.S. Department of Energy, Office of Science, Office of High Energy Physics under Award Number DESC0020086 and from the National Science Foundation under grant AST-1616414. Authors want to thank the GAMA collaboration for early access to GAMA DR4 data for this work. Some of the results in this paper have been derived using the healpy and HEALPIX package. We acknowledge the usage of the HyperLeda database (http://leda.univ-lyon1.fr).This work also made extensive use of the NASA Astrophysics Data System and of the astro-ph preprint archive at arXiv.org. This work used the DiRAC@Durham facility managed by the Institute for Computational Cosmology on behalf of the STFC DiRAC HPC Facility (www.dirac.ac.uk). The equipment was funded by BEIS capital funding via STFC capital grants ST/K00042X/1, ST/P002293/1, and ST/R002371/1, Durham University and STFC operations grant ST/R000832/1. DiRAC is part of the National e-Infrastructure. This research used resources of the National Energy Research Scientific Computing Center (NERSC). NERSC is a U.S. Department of Energy Office of Science User Facility operated under Contract No. DE-AC02-05CH11231. This research is supported by the Director, Office of Science, Office of High Energy Physics of the U.S. Department of Energy under Contract No. DE-AC02-05CH1123, and by the National Energy Research Scientific Computing Center, a DOE Office of Science User Facility under the same contract; additional support for DESI is provided by the U.S. National Science Foundation, Division of Astronomical Sciences under Contract No. AST-0950945 to the NSF’s National Optical-Infrared Astronomy Research Laboratory; the Science and Technologies Facilities Council of the United Kingdom; the Gordon and Betty Moore Foundation; the Heising-Simons Foundation; the French Alternative Energies and Atomic Energy Commission (CEA); the National Council of Science and Technology of Mexico; the Ministry of Economy of Spain, and by the DESI Member Institutions. The authors are honored to be permitted to conduct astronomical research on Iolkam Du’ag (Kitt Peak), a mountain with particular significance to the Tohono O’odham Nation., With funding from the Spanish government through the Severo Ochoa Centre of Excellence accreditation SEV-2017-0709.

This is an Open Access article, published by EDP Sciences, under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited., Having two “sibling” Type Ia supernovae (SNe Ia) in the same galaxy offers additional advantages in reducing a variety of systematic errors involved in estimating the Hubble constant, H0. NGC 4414 is a nearby galaxy included in the Hubble Space Telescope Key Project to measure its distance using Cepheid variables. It hosts two sibling SNe Ia: SN 2021J and SN 1974G. This provides the opportunity to improve the precision of the previous estimate of H0, which was based solely on SN 1974G. Here we present new optical BVRI photometry obtained at the Observatorio de Sierra Nevada and complement it with Swift UVOT UBV data, which cover the first 70 days of emission of SN 2021J. A first look at SN 2021J optical spectra obtained with the Gran Telescopio Canarias (GTC) reveals typical SN type Ia features. The main SN luminosity parameters for the two sibling SNe are obtained by using SNooPy, a light curve fitting code based on templates. Using a hierarchical bayesian approach, we build the Hubble diagram with a sample of 96 SNe Ia obtained from the Combined Pantheon Sample in the redshift range z = 0.02 − 0.075, and calibrate the zero point with the two sibling type-Ia SNe in NGC 4414. We report a value of the Hubble constant H0 = 72.19 ± 2.32 (stat.) ±3.42 (syst.) km s−1 Mpc−1. We expect a reduction of the systematic error after a new analysis of the Cepheids period-luminosity relation using the upcoming Gaia DR4 and additional Cepheids from the HST and JWST. © E. Gallego-Cano et al. 2022., The authors acknowledge financial support from the State Agency for Research of the Spanish MICINN through the “Center of Excellence Severo Ochoa” award to the Instituto de Astrofísica de Andalucía (SEV-2017-0709). EGC thanks the incentive grant by the Ministry of Economic Transformation, Industry, Knowledge and Universities REF. P20_00880, project co-financed by 80% by funds from the operational program FEDER de Andalucía 2014–2020. LI and NK were supported by two grants from VILLUM FONDEN (project number 16599 and 25501). CDT, FP and EP thank the support of the Spanish Ministry of Science and Innovation funding grant PGC2018-101931-B-I00. CDT thanks the Instituto de Astrofísica de Canarias for the use of its facilities to carry out this work. Based on observations collected at the Observatorio de Sierra Nevada, operated by the Instituto de Astrofísica de Andalucía (IAA-CSIC). Partly based on observations made with the Gran Telescopio Canarias (GTC), installed at the Spanish Observatorio del Roque de los Muchachos of the Instituto de Astrofísica de Canarias, in the island of La Palma. The authors thank the GTC support staff for performing the observations.

The quasar target selection for the upcoming survey of the Dark Energy Spectroscopic Instrument (DESI) will be fixed for the next 5 yr. The aim of this work is to validate the quasar selection by studying the impact of imaging systematics as well as stellar and galactic contaminants, and to develop a procedure to mitigate them. Density fluctuations of quasar targets are found to be related to photometric properties such as seeing and depth of the Data Release 9 of the DESI Legacy Imaging Surveys. To model this complex relation, we explore machine learning algorithms (random forest and multilayer perceptron) as an alternative to the standard linear regression. Splitting the footprint of the Legacy Imaging Surveys into three regions according to photometric properties, we perform an independent analysis in each region, validating our method using extended Baryon Oscillation Spectroscopic Survey (eBOSS) EZ-mocks. The mitigation procedure is tested by comparing the angular correlation of the corrected target selection on each photometric region to the angular correlation function obtained using quasars from the Sloan Digital Sky Survey (SDSS) Data Release 16. With our procedure, we recover a similar level of correlation between DESI quasar targets and SDSS quasars in two-thirds of the total footprint and we show that the excess of correlation in the remaining area is due to a stellar contamination that should be removed with DESI spectroscopic data. We derive the Limber parameters in our three imaging regions and compare them to previous measurements from SDSS and the 2dF QSO Redshift Survey., This research is supported by the Director, Office of Science, Office of High Energy Physics of the U.S. Department of Energy under contract no. DE-AC02-05CH11231, and by the National Energy Research Scientific Computing Center, a DOE Office of Science User Facility under the same contract; additional support for DESI is provided by the U.S. National Science Foundation, Division of Astronomical Sciences under contract no. AST-0950945 to the NSF’s National Optical–Infrared Astronomy Research Laboratory; the Science and Technology Facilities Council of the United Kingdom; the Gordon and Betty Moore Foundation; the Heising-Simons Foundation; the French Alternative Energies and Atomic Energy Commission (CEA); the National Council of Science and Technology, Mexico; the Ministry of Economy of Spain, and by the DESI Member Institutions. ADM was supported by the U.S. Department of Energy, Office of Science, Office of High Energy Physics, under Award Number DE-SC0019022.

In preparation for photometric classification of transients from the Legacy Survey of Space and Time (LSST) we run tests with different training data sets. Using estimates of the depth to which the 4-metre Multi-Object Spectroscopic Telescope (4MOST) Time Domain Extragalactic Survey (TiDES) can classify transients, we simulate a magnitude-limited sample reaching $r_{\textrm{AB}} \approx$ 22.5 mag. We run our simulations with the software snmachine, a photometric classification pipeline using machine learning. The machine-learning algorithms struggle to classify supernovae when the training sample is magnitude-limited, in contrast to representative training samples. Classification performance noticeably improves when we combine the magnitude-limited training sample with a simulated realistic sample of faint, high-redshift supernovae observed from larger spectroscopic facilities; the algorithms' range of average area under ROC curve (AUC) scores over 10 runs increases from 0.547-0.628 to 0.946-0.969 and purity of the classified sample reaches 95 per cent in all runs for 2 of the 4 algorithms. By creating new, artificial light curves using the augmentation software avocado, we achieve a purity in our classified sample of 95 per cent in all 10 runs performed for all machine-learning algorithms considered. We also reach a highest average AUC score of 0.986 with the artificial neural network algorithm. Having `true' faint supernovae to complement our magnitude-limited sample is a crucial requirement in optimisation of a 4MOST spectroscopic sample. However, our results are a proof of concept that augmentation is also necessary to achieve the best classification results., MNRAS accepted version Aug 2021

Studying galaxies at different cosmic epochs entails several observational effects that need to be taken into account to compare populations across a large time-span in a consistent manner. We use a sample of 166 nearby galaxies that hosted type Ia supernovae (SNe Ia) and have been observed with the integral field spectrograph MUSE as part of the AMUSING survey. Here, we present a study of the systematic errors and bias on the host stellar mass with increasing redshift, which are generally overlooked in SNe Ia cosmological analyses. We simulate observations at different redshifts (0.1 < z < 2.0) using four photometric bands (griz, similar to the Dark Energy Survey-SN program) to then estimate the host galaxy properties across cosmic time. We find that stellar masses are systematically underestimated as we move towards higher redshifts, due mostly to different rest-frame wavelength coverage, with differences reaching 0.3 dex at z ∼ 1. We used the newly derived corrections as a function of redshift to correct the stellar masses of a known sample of SN Ia hosts and derive cosmological parameters. We show that these corrections have a small impact on the derived cosmological parameters. The most affected is the value of the mass step ΔM, which is reduced by ∼0.004 (6% lower). The dark energy equation of state parameter w changes by Δw∼ 0.006 (0.6% higher) and the value of Ωm increases at most by 0.001 (∼0.3%), all within the derived uncertainties of the model. While the systematic error found in the estimate of the host stellar mass does not significantly affect the derived cosmological parameters, it is an important source of systematic error that needs to be corrected for as we enter a new era of precision cosmology., This work was supported by Fundação para a Ciência e a Tecnologia (FCT) through the research grant UIDB/00099/2020 and the CRISP project PTDC/FIS-AST-31546/2017. L.G. acknowledges financial support from the Spanish Ministry of Science, Innovation and Universities (MICIU) under the 2019 Ramón y Cajal program RYC2019-027683 and from the Spanish MICIU project HOSTFLOWS PID2020-115253GA-I00. CRA was supported by grants from VILLUM FONDEN (project numbers 16599 and 25501). J.D.L. acknowledges support from a UK Research and Innovation Future Leaders Fellowship (MR/T020784/1). Computations were performed at the cluster “Baltasar-Sete-Sóis”, supported by the H2020 ERC Grant “Matter and strong field gravity: New frontiers in Einstein’s theory” grant agreement no. MaGRaTh-646597, and at COIN, the CosmoStatistics Initiative, whose purchase was made possible due to a CNRS MOMENTUM 2018–2020 under the project “Active Learning for large scale sky surveys”. This work was only possible by the use of the following PYTHON packages: NumPy & SciPy (Walt et al. 2011; Jones et al. 2001), Matplotlib (Hunter 2007), and Astropy (Astropy Collaboration et al. 2013).

While most purpose-built 21cm intensity mapping experiments are close-packed interferometer arrays, general-purpose dish arrays should also be capable of measuring the cosmological 21cm signal. This can be achieved most efficiently if the array is used as a collection of scanning autocorrelation dishes rather than as an interferometer. As a first step towards demonstrating the feasibility of this observing strategy, we show that we are able to successfully calibrate dual-polarisation autocorrelation data from 64 MeerKAT dishes in the L-band (856-1712 MHz, 4096 channels), with 10.5 hours of data retained from six nights of observing. We describe our calibration pipeline, which is based on multi-level RFI flagging, periodic noise diode injection to stabilise gain drifts and an absolute calibration based on a multi-component sky model. We show that it is sufficiently accurate to recover maps of diffuse celestial emission and point sources over a 10 deg x 30 deg patch of the sky overlapping with the WiggleZ 11hr field. The reconstructed maps have a good level of consistency between per-dish maps and external datasets, with the estimated thermal noise limited to 1.4 x the theoretical noise level (~ 2 mK). The residual maps have rms amplitudes below 0.1 K, corresponding to, 24 pages, 34 figures, accepted for publication in MNRAS

Gatti, M., et al. (DES Collaboration), We present and characterize the galaxy shape catalogue from the first 3 yr of Dark Energy Survey (DES) observations, over an effective area of 4143 deg2 of the southern sky. We describe our data analysis process and our self-calibrating shear measurement pipeline metacalibration, which builds and improves upon the pipeline used in the DES Year 1 analysis in several aspects. The DES Year 3 weak-lensing shape catalogue consists of 100 204 026 galaxies, measured in the riz bands, resulting in a weighted source number density of neff = 5.59 gal arcmin-2 and corresponding shape noise σe = 0.261. We perform a battery of internal null tests on the catalogue, including tests on systematics related to the point spread function (PSF) modelling, spurious catalogue B-mode signals, catalogue contamination, and galaxy properties., Based in part on observations at Cerro Tololo Inter-American Observatory at NSF’s NOIRLab (NOIRLab Prop. ID 2012B-0001; PI: J. Frieman), which is managed by the Association of Universities for Research in Astronomy (AURA) under a cooperative agreement with the National Science Foundation. The DES data management system is supported by the National Science Foundation under grants AST-1138766 and AST-1536171. The DES participants from Spanish institutions are partially supported by MINECO under grants AYA2015-71825, ESP2015-66861, FPA2015-68048, SEV-2016-0588, SEV-2016-0597, and MDM-2015-0509, some of which include ERDF funds from the European Union. IFAE is partially funded by the CERCA programme of the Generalitat de Catalunya. Research leading to these results has received funding from the European Research Council under the European Union’s Seventh Framework Program (FP7/2007-2013) including ERC grant agreements 240672, 291329, and 306478. We acknowledge support from the Brazilian Instituto Nacional de Ciência e Tecnologia (INCT) e-Universe (CNPq grant 465376/2014-2).

Rosell, A., et al. (DES Collaboration), In this paper, we present and validate the galaxy sample used for the analysis of the baryon acoustic oscillation (BAO) signal in the Dark Energy Survey (DES) Y3 data. The definition is based on a colour and redshift-dependent magnitude cut optimized to select galaxies at redshifts higher than 0.5, while ensuring a high-quality determination. The sample covers ~4100 deg2 to a depth of i = 22.3 (AB) at 10s. It contains 7031 993 galaxies in the redshift range from z = 0.6 to 1.1, with a mean effective redshift of 0.835. Redshifts are estimated with the machine learning algorithm DNF, and are validated using the VIPERS PDR2 sample. We find a mean redshift bias of zbias~0.01 and a mean uncertainty, in units of 1 + z, of σ68~0.03. We evaluate the galaxy population of the sample, showing it is mostly built upon Elliptical to Sbc types. Furthermore, we find a low level of stellar contamination of ≤ 4 per cent. We present the method used to mitigate the effect of spurious clustering coming from observing conditions and other large-scale systematics.We apply it to the BAO sample and calculate weights that are used to get a robust estimate of the galaxy clustering signal. This paper is one of a series dedicated to the analysis of the BAO signal in DES Y3. In the companion papers, we present the galaxy mock catalogues used to calibrate the analysis and the angular diameter distance constraints obtained through the fitting to the BAO scale., The DES data management system is supported by the National Science Foundation under Grant Numbers AST-1138766 and AST-1536171. The DES participants from Spanish institutions are partially supported by MICINN under grants ESP2017-89838,PGC2018-094773, PGC2018-102021, SEV-2016-0588, SEV-2016-0597, and MDM-2015-0509, some of which include ERDF funds from the European Union. IFAE is partially funded by the CERCA program of the Generalitat de Catalunya. Research leading to these results has received funding from the European Research Council under the European Union’s Seventh Framework Program (FP7/2007-2013) including ERC grant agreements 240672, 291329, and 306478. We acknowledge support from the Brazilian Instituto Nacional de Ciência e Tecnologia (INCT) do e-Universo (CNPq grant 465376/2014-2). ACR acknowledges financial support from the Spanish Ministry of Science, Innovation and Universities (MICIU) under grant AYA2017-84061-P, co-financed by FEDER (European Regional Development Funds) and by the Spanish Space Research Program ‘Participation in the NISP instrument and preparation for the science of EUCLID’ (ESP2017-84272-C2-1-R). SA was supported by the MICUES project, funded by the EU’s H2020 MSCA grant agreement no. 713366 (InterTalentum UAM).

An accurate covariance matrix is essential for obtaining reliable cosmological results when using a Gaussian likelihood. In this paper we study the covariance of pseudo-Cℓ estimates of tomographic cosmic shear power spectra. Using two existing publicly available codes in combination, we calculate the full covariance matrix, including mode-coupling contributions arising from both partial sky coverage and non-linear structure growth. For three different sky masks, we compare the theoretical covariance matrix to that estimated from publicly available N-body weak lensing simulations, finding good agreement. We find that as a more extreme sky cut is applied, a corresponding increase in both Gaussian off-diagonal covariance and non-Gaussian super-sample covariance is observed in both theory and simulations, in accordance with expectations. Studying the different contributions to the covariance in detail, we find that the Gaussian covariance dominates along the main diagonal and the closest off-diagonals, but farther away from the main diagonal the super-sample covariance is dominant. Forming mock constraints in parameters that describe matter clustering and dark energy, we find that neglecting non-Gaussian contributions to the covariance can lead to underestimating the true size of confidence regions by up to 70 per cent. The dominant non-Gaussian covariance component is the super-sample covariance, but neglecting the smaller connected non-Gaussian covariance can still lead to the underestimation of uncertainties by 10–20 per cent. A real cosmological analysis will require marginalisation over many nuisance parameters, which will decrease the relative importance of all cosmological contributions to the covariance, so these values should be taken as upper limits on the importance of each component.

Upham, R.E., et al. (Euclid Consortium), An accurate covariance matrix is essential for obtaining reliable cosmological results when using a Gaussian likelihood. In this paper we study the covariance of pseudo-Cestimates of tomographic cosmic shear power spectra. Using two existing publicly available codes in combination, we calculate the full covariance matrix, including mode-coupling contributions arising from both partial sky coverage and non-linear structure growth. For three different sky masks, we compare the theoretical covariance matrix to that estimated from publicly available N-body weak lensing simulations, finding good agreement. We find that as a more extreme sky cut is applied, a corresponding increase in both Gaussian off-diagonal covariance and non-Gaussian super-sample covariance is observed in both theory and simulations, in accordance with expectations. Studying the different contributions to the covariance in detail, we find that the Gaussian covariance dominates along the main diagonal and the closest off-diagonals, but farther away from the main diagonal the super-sample covariance is dominant. Forming mock constraints in parameters that describe matter clustering and dark energy, we find that neglecting non-Gaussian contributions to the covariance can lead to underestimating the true size of confidence regions by up to 70 per cent. The dominant non-Gaussian covariance component is the super-sample covariance, but neglecting the smaller connected non-Gaussian covariance can still lead to the underestimation of uncertainties by 10-20 per cent. A real cosmological analysis will require marginalisation over many nuisance parameters, which will decrease the relative importance of all cosmological contributions to the covariance, so these values should be taken as upper limits on the importance of each component., This work would not have been possible without the contributions to the community from the developers of NaMaster (Alonso et al. 2019; García-García et al. 2019), CosmoLike (Krause & Eifler 2017; Fang et al. 2020) and the simulations of Takahashi et al. (2017).

An accurate covariance matrix is essential for obtaining reliable cosmological results when using a Gaussian likelihood. In this paper we study the covariance of pseudo-Cestimates of tomographic cosmic shear power spectra. Using two existing publicly available codes in combination, we calculate the full covariance matrix, including mode-coupling contributions arising from both partial sky coverage and non-linear structure growth. For three different sky masks, we compare the theoretical covariance matrix to that estimated from publicly available N-body weak lensing simulations, finding good agreement. We find that as a more extreme sky cut is applied, a corresponding increase in both Gaussian off-diagonal covariance and non-Gaussian super-sample covariance is observed in both theory and simulations, in accordance with expectations. Studying the different contributions to the covariance in detail, we find that the Gaussian covariance dominates along the main diagonal and the closest off-diagonals, but farther away from the main diagonal the super-sample covariance is dominant. Forming mock constraints in parameters that describe matter clustering and dark energy, we find that neglecting non-Gaussian contributions to the covariance can lead to underestimating the true size of confidence regions by up to 70 per cent. The dominant non-Gaussian covariance component is the super-sample covariance, but neglecting the smaller connected non-Gaussian covariance can still lead to the underestimation of uncertainties by 10-20 per cent. A real cosmological analysis will require marginalisation over many nuisance parameters, which will decrease the relative importance of all cosmological contributions to the covariance, so these values should be taken as upper limits on the importance of each component.

The ionizing photon escape fraction [Lyman continuum (LyC) f(esc)] of star-forming galaxies is the single greatest unknown in the reionization budget. Stochastic sightline effects prohibit the direct separation of LyC leakers from non-leakers at significant redshifts. Here we circumvent this uncertainty by inferring f(esc) using resolved (R > 4000) Lyman alpha (Ly alpha) profiles from the X-SHOOTER Ly alpha survey at z = 2 (XLS-z2). With empirically motivated criteria, we use Ly alpha profiles to select leakers (f(esc) > 20 per cent) and non-leakers (f(esc) < 5 per cent) from a representative sample of >0.2L* Lyman alpha emitters (LAEs). We use median stacked spectra of these subsets over lambda(rest) approximate to 1000-8000 angstrom to investigate the conditions for LyC f(esc). Our stacks show similar mass, metallicity, M-UV, and beta(UV). We find the following differences between leakers versus non-leakers: (i) strong nebular C IV and He II emission versus non-detections; (ii) [O III]/[O II] approximate to 8.5 versus approximate to 3; (iii) H alpha/H beta indicating no dust versus E(B - V) approximate to 0.3; (iv) Mg II emission close to the systemic velocity versus redshifted, optically thick Mg II; and (v) Ly alpha f(esc) of approximate to 50 per cent versus approximate to 10 per cent. The extreme equivalent widths (EWs) in leakers ([O III]+H beta approximate to 1100 Arest frame) constrain the characteristic time-scale of LyC escape to approximate to 3-10 Myr bursts when short-lived stars with the hardest ionizing spectra shine. The defining traits of leakers - extremely ionizing stellar populations, low column densities, a dust-free, high-ionization state interstellar medium (ISM) - occur simultaneously in the f(esc) > 20 per cent stack, suggesting they are causally connected, and motivating why indicators like [O III]/[O II] may suffice to constrain f(esc) at z > 6 with the James Webb Space Telescope (JWST). The leakers comprise half of our sample, have a median LyC f(esc) approximate to 50 per cent (conservative range: 20-55 per cent), and an ionizing production efficiency log(xi(ion)/Hz erg(-1)) approximate to 25.9 (conservative range: 25.7-25.9). These results show LAEs - the type of galaxies rare at z approximate to 2, but that become the norm at higher redshift - are highly efficient ionizers, with extreme xi(ion) and prolific f(esc) occurring in sync.

We introduce a new software package for modeling the point-spread function (PSF) of astronomical images, called Piff (PSFs In the Full FOV), which we apply to the first three years (known as Y3) of the Dark Energy Survey (DES) data. We describe the relevant details about the algorithms used by Piff to model the PSF, including how the PSF model varies across the field of view (FOV). Diagnostic results show that the systematic errors from the PSF modeling are very small over the range of scales that are important for the DES Y3 weak lensing analysis. In particular, the systematic errors from the PSF modeling are significantly smaller than the corresponding results from the DES year one (Y1) analysis. We also briefly describe some planned improvements to Piff that we expect to further reduce the modeling errors in future analyses., Comment: 19 pages, accepted/published by MNRAS. See https://www.darkenergysurvey.org/des-year-3-cosmology-results-papers/ for the full DES Y3 cosmology release

Relativistic effects in clustering observations have been shown to introduce scale-dependent corrections to the galaxy over-density field on large scales, which may hamper the detection of primordial non-Gaussianity $f_\textrm{NL}$ through the scale-dependent halo bias. The amplitude of relativistic corrections depends not only on the cosmological background expansion, but also on the redshift evolution and sensitivity to the luminosity threshold of the tracer population being examined, as parametrised by the evolution bias $b_\textrm{e}$ and magnification bias $s$. In this work, we propagate luminosity function measurements from the extended Baryon Oscillation Spectroscopic Survey (eBOSS) to $b_\textrm{e}$ and $s$ for the quasar (QSO) sample, and thereby derive constraints on relativistic corrections to its power spectrum multipoles. Although one could mitigate the impact on the $f_\textrm{NL}$ signature by adjusting the redshift range or the luminosity threshold of the tracer sample being considered, we suggest that, for future surveys probing large cosmic volumes, relativistic corrections should be forward modelled from the tracer luminosity function including its uncertainties. This will be important to quasar clustering measurements on scales $k \sim 10^{-3} h \, \textrm{Mpc}^{-1}$ in upcoming surveys such as the Dark Energy Spectroscopic Instrument (DESI), where relativistic corrections can overwhelm the expected $f_\textrm{NL}$ signature at low redshifts $z \lesssim 1$ and become comparable to $f_\textrm{NL} \simeq 1$ in the power spectrum quadrupole at redshifts $z \gtrsim 2.5$., Comment: Published by MNRAS, 7 figures and 1 table; changes made after peer review; public code HorizonGRound available at http://github.com/MikeSWang/HorizonGRound

We present infrared luminosity functions and dust mass functions for the EAGLE cosmological simulation, based on synthetic multi-wavelength observations generated with the SKIRT radiative transfer code. In the local Universe, we reproduce the observed infrared luminosity and dust mass functions very well. Some minor discrepancies are encountered, mainly in the high luminosity regime, where the EAGLE-SKIRT luminosity functions mildly but systematically underestimate the observed ones. The agreement between the EAGLE-SKIRT infrared luminosity functions and the observed ones gradually worsens with increasing lookback time. Fitting modified Schechter functions to the EAGLE-SKIRT luminosity and dust mass functions at different redshifts up to $z=1$, we find that the evolution is compatible with pure luminosity/mass evolution. The evolution is relatively mild: within this redshift range, we find an evolution of $L_{\star,250}\propto(1+z)^{1.68}$, $L_{\star,\text{TIR}}\propto(1+z)^{2.51}$ and $M_{\star,\text{dust}}\propto(1+z)^{0.83}$ for the characteristic luminosity/mass. For the luminosity/mass density we find $\varepsilon_{250}\propto(1+z)^{1.62}$, $\varepsilon_{\text{TIR}}\propto(1+z)^{2.35}$ and $\rho_{\text{dust}}\propto(1+z)^{0.80}$, respectively. The mild evolution of the dust mass density is in relatively good agreement with observations, but the slow evolution of the infrared luminosity underestimates the observed luminosity evolution significantly. We argue that these differences can be attributed to increasing limitations in the radiative transfer treatment due to increasingly poorer resolution, combined with a slower than observed evolution of the SFR density in the EAGLE simulation and the lack of AGN emission in our EAGLE-SKIRT post-processing recipe., Comment: 13 pages, 6 pages, accepted for publication in MNRAS

In this work we compare three catalogues of cosmological filaments identified in the Sloan Digital Sky Survey by means of different algorithms by Tempel et al., Pereyra et al., and Mart\'inez et al. We analyse how different identification techniques determine differences in the filament statistical properties: length, elongation, redshift distribution, and abundance. We find that the statistical properties of the filaments strongly depend on the identification algorithm. We use a volume limited sample of galaxies to characterise other properties of filaments such as: galaxy overdensity, luminosity function of galaxies, mean galaxy luminosity, filament luminosity, and the overdensity profile of galaxies around filaments. In general, we find that these properties primarily depended on filament length. Shorter filaments have larger overdensities, are more populated by red galaxies, and have better defined galaxy overdensity profiles, than longer filaments. Concluding that galaxies belonging to filaments have characteristic signatures depending on the identification algorithm used., Comment: 14 pages, 17 figures. Accepted for publication in MNRAS

Planck Collaboration: et al., arXiv:1905.05697v1, We analyse the Planck full-mission cosmic microwave background (CMB) temperature and E-mode polarization maps to obtain constraints on primordial non-Gaussianity (NG). We compare estimates obtained from separable template-fitting, binned, and optimal modal bispectrum estimators, finding consistent values for the local, equilateral, and orthogonal bispectrum amplitudes. Our combined temperature and polarization analysis produces the following final results: fNLlocal = −0.9 ± 5.1; fNLequil = −26 ± 47; and fNLortho = −38 ± 24 (68% CL, statistical). These results include low-multipole (4 ≤ ℓ < 40) polarization data that are not included in our previous analysis. The results also pass an extensive battery of tests (with additional tests regarding foreground residuals compared to 2015), and they are stable with respect to our 2015 measurements (with small fluctuations, at the level of a fraction of a standard deviation, which is consistent with changes in data processing). Polarization-only bispectra display a significant improvement in robustness; they can now be used independently to set primordial NG constraints with a sensitivity comparable to WMAP temperature-based results and they give excellent agreement. In addition to the analysis of the standard local, equilateral, and orthogonal bispectrum shapes, we consider a large number of additional cases, such as scale-dependent feature and resonance bispectra, isocurvature primordial NG, and parity-breaking models, where we also place tight constraints but do not detect any signal. The non-primordial lensing bispectrum is, however, detected with an improved significance compared to 2015, excluding the null hypothesis at 3.5σ. Beyond estimates of individual shape amplitudes, we also present model-independent reconstructions and analyses of the Planck CMB bispectrum. Our final constraint on the local primordial trispectrum shape is gNLlocal = (−5.8 ± 6.5) × 104 (68% CL, statistical), while constraints for other trispectrum shapes are also determined. Exploiting the tight limits on various bispectrum and trispectrum shapes, we constrain the parameter space of different early-Universe scenarios that generate primordial NG, including general single-field models of inflation, multi-field models (e.g. curvaton models), models of inflation with axion fields producing parity-violation bispectra in the tensor sector, and inflationary models involving vector-like fields with directionally-dependent bispectra. Our results provide a high-precision test for structure-formation scenarios, showing complete agreement with the basic picture of the ΛCDM cosmology regarding the statistics of the initial conditions, with cosmic structures arising from adiabatic, passive, Gaussian, and primordial seed perturbations., The Planck Collaboration acknowledges the support of: ESA; CNES and CNRS/INSU-IN2P3-INP (France); ASI, CNR, and INAF (Italy); NASA and DoE (USA); STFC and UKSA (UK); CSIC, MINECO, JA, and RES (Spain); Tekes, AoF, and CSC (Finland); DLR and MPG (Germany); CSA (Canada); DTU Space (Denmark); SER/SSO (Switzerland); RCN (Norway); SFI (Ireland); FCT/MCTES (Portugal); and ERC and PRACE (EU).

The key challenge in the observation of the redshifted 21-cm signal from cosmic reionization is its separation from the much brighter foreground emission. Such separation relies on the different spectral properties of the two components, although, in real life, the foreground intrinsic spectrum is often corrupted by the instrumental response, inducing systematic effects that can further jeopardize the measurement of the 21-cm signal. In this paper, we use Gaussian Process Regression to model both foreground emission and instrumental systematics in $\sim 2$ hours of data from the Hydrogen Epoch of Reionization Array. We find that a simple co-variance model with three components matches the data well, giving a residual power spectrum with white noise properties. These consist of an "intrinsic" and instrumentally corrupted component with a coherence-scale of 20 MHz and 2.4 MHz respectively (dominating the line of sight power spectrum over scales $k_{\parallel} \le 0.2$ h cMpc$^{-1}$) and a baseline dependent periodic signal with a period of $\sim 1$ MHz (dominating over $k_{\parallel} \sim 0.4 - 0.8$h cMpc$^{-1}$) which should be distinguishable from the 21-cm EoR signal whose typical coherence-scales is $\sim 0.8$ MHz., 15 pages, 15 figures, 1 table, Accepted to MNRAS

The PRObabilistic Value-Added Bright Galaxy Survey (PROVABGS) catalog will provide measurements of galaxy properties, such as stellar mass ($M_*$), star formation rate (${\rm SFR}$), stellar metallicity ($Z_{\rm MW}$), and stellar age ($t_{\rm age, MW}$), for >10 million galaxies of the DESI Bright Galaxy Survey. Full posterior distributions of the galaxy properties will be inferred using state-of-the-art Bayesian spectral energy distribution (SED) modeling of DESI spectroscopy and Legacy Surveys photometry. In this work, we present the SED model, Bayesian inference framework, and methodology of PROVABGS. Furthermore, we apply the PROVABGS SED modeling on realistic synthetic DESI spectra and photometry, constructed using the L-GALAXIES semi-analytic model. We compare the inferred galaxy properties to the true galaxy properties of the simulation using a hierarchical Bayesian framework to quantify accuracy and precision. Overall, we accurately infer the true $M_*$, ${\rm SFR}$, $Z_{\rm MW}$, and $t_{\rm age, MW}$ of the simulated galaxies. However, the priors on galaxy properties induced by the SED model have a significant impact on the posteriors. They impose a ${\rm SFR}{>}10^{-1} M_\odot/{\rm yr}$ lower bound on ${\rm SFR}$, a ${\sim}0.3$ dex bias on $\log Z_{\rm MW}$ for galaxies with low spectral signal-to-noise, and $t_{\rm age, MW} < 8\,{\rm Gyr}$ upper bound on stellar age. This work also demonstrates that a joint analysis of spectra and photometry significantly improves the constraints on galaxy properties over photometry alone and is necessary to mitigate the impact of the priors. With the methodology presented and validated in this work, PROVABGS will maximize information extracted from DESI observations and provide a probabilistic value-added galaxy catalog that will extend current galaxy studies to new regimes and unlock cutting-edge probabilistic analyses., 40 pages, 17 figures, submitted to ApJ, the PROVABGS SED modeling pipeline is publicly available at https://github.com/changhoonhahn/provabgs

Artículo escrito por un elevado núnmero de autores, sólo se referencian el qque aparece en primer lugar, los autores pertenecientes a la UAM y el nombre del grupo de colaboración, si lo hubiere, We present a new infrared survey covering the three Euclid deep fields and four other Euclid calibration fields using Spitzer Space Telescope's Infrared Array Camera (IRAC). We combined these new observations with all relevant IRAC archival data of these fields in order to produce the deepest possible mosaics of these regions. In total, these observations represent nearly 11 % of the total Spitzer Space Telescope mission time. The resulting mosaics cover a total of approximately 71.5 deg2 in the 3.6 and 4.5 μm bands, and approximately 21.8 deg2 in the 5.8 and 8 μm bands. They reach at least 24 AB magnitude (measured to 5σ, in a 2″​​.5 aperture) in the 3.6 μm band and up to ∼5 mag deeper in the deepest regions. The astrometry is tied to the Gaia astrometric reference system, and the typical astrometric uncertainty for sources with 16 "< "[3.6]< 19 is ≲ 0″​​.15. The photometric calibration is in excellent agreement with previous WISE measurements. We extracted source number counts from the 3.6 μm band mosaics, and they are in excellent agreement with previous measurements. Given that the Spitzer Space Telescope has now been decommissioned, these mosaics are likely to be the definitive reduction of these IRAC data. This survey therefore represents an essential first step in assembling multi-wavelength data on the Euclid deep fields, which are set to become some of the premier fields for extragalactic astronomy in the 2020s

This paper aims to quantify how the lowest halo mass that can be detected with galaxy-galaxy strong gravitational lensing depends on the quality of the observations and the characteristics of the observed lens systems. Using simulated data, we measure the lowest detectable NFW mass at each location of the lens plane, in the form of detailed \emph{sensitivity maps}. In summary, we find that: (i) the lowest detectable mass $M_{\rm low}$ decreases linearly as the signal-to-noise ratio (SNR) increases and the sensitive area is larger when we decrease the noise; (ii) a moderate increase in angular resolution (0.07" vs 0.09") and pixel scale (0.01" vs 0.04") improves the sensitivity by on average 0.25 dex in halo mass, with more significant improvement around the most sensitive regions; (iii) the sensitivity to low-mass objects is largest for bright and complex lensed galaxies located inside the caustic curves and lensed into larger Einstein rings (i.e $r_{E}\geq1.0"$). We find that for the sensitive mock images considered in this work, the minimum mass that we can detect at the redshift of the lens lies between $1.5\times10^{8}$ and $3\times10^{9}M_{\odot}$. We derive analytic relations between $M_{\rm low}$, the SNR and resolution and discuss the impact of the lensing configuration and source structure. Our results start to fill the gap between approximate predictions and real data and demonstrate the challenging nature of calculating precise forecasts for gravitational imaging. In light of our findings, we discuss possible strategies for designing strong lensing surveys and the prospects for HST, Keck, ALMA, Euclid and other future observations., Comment: 17 pages, 11 figures, accepted for publication in MNRAS. Comments welcome

This is a pre-copyedited, author-produced PDF of an article accepted for publication in Monthly Notices of the Royal Astronomical Society following peer review. The version of record Monthly Notices of the Royal Astronomical Society 510.1 (2022): 581-592 is available online at: https://academic.oup.com/mnras/article-abstract/510/1/581/6445057?redirectedFrom=fulltext, Galaxy clusters grow by accreting galaxies from the field and along filaments of the cosmic web. As galaxies are accreted they are affected by their local environment before they enter (pre-processing), and traverse the cluster potential. Observations that aim to constrain pre-processing are challenging to interpret because filaments comprise a heterogeneous range of environments including groups of galaxies embedded within them and backsplash galaxies that contain a record of their previous passage through the cluster. This motivates using modern cosmological simulations to dissect the population of galaxies found in filaments that are feeding clusters, to better understand their history, and aid the interpretation of observations. We use zoom-in simulations from The ThreeHundred project to track haloes through time and identify their environment. We establish a benchmark for galaxies in cluster infall regions that supports the reconstruction of the different modes of pre-processing. We find that up to 45 per cent of all galaxies fall into clusters via filaments (closer than 1 h-1Mpc from the filament spine). 12 per cent of these filament galaxies are long-established members of groups and between 30 and 60 per cent of filament galaxies at R200 are backsplash galaxies. This number depends on the cluster's dynamical state and sharply drops with distance. Backsplash galaxies return to clusters after deflecting widely from their entry trajectory, especially in relaxed clusters. They do not have a preferential location with respect to filaments and cannot collapse to form filaments. The remaining pristine galaxies (∼30-60 per cent) are environmentally affected by cosmic filaments alone

Since the discovery of the accelerating expansion of the Universe more than two decades ago, Type Ia Supernovae (SNe Ia) have been extensively used as standardisable candles in the optical. However, SNe Ia have shown to be more homogeneous in the near-infrared (NIR), where the effect of dust extinction is also attenuated. In this work, we explore the possibility of using a low number of NIR observations for accurate distance estimations, given the homogeneity at these wavelengths. We found that one epoch in J and/or H band, plus good gr-band coverage, gives an accurate estimation of peak magnitudes in the J (Jmax) and H (Hmax) bands. The use of a single NIR epoch only introduces an additional scatter of ∼0.05 mag for epochs around the time of B-band peak magnitude (Tmax). We also tested the effect of optical cadence and signal-to-noise ratio (S/N) in the estimation of Tmax and its uncertainty propagation to the NIR peak magnitudes. Both cadence and S/N have a similar contribution, where we constrained the introduced scatter of each to < 0.02 mag in Jmax and < 0.01 in Hmax. However, these effects are expected to be negligible, provided the data quality is comparable to that obtained for observations of nearby SNe (z ≲ 0.1). The effect of S/N in the NIR was tested as well. For SNe Ia at 0.08, TEMB and LG acknowledge financial support from the Spanish Ministerio de Ciencia e Innovación (MCIN), the Agencia Estatal de Investigación (AEI) 10.13039/501100011033 under the PID2020-115253GA-I00 HOSTFLOWS project, and from Centro Superior de Investigaciones Científicas (CSIC) under the PIE project 20215AT016, and the I-LINK 2021 LINKA20409. TEMB and LG are also partially supported by the program Unidad de Excelencia María de Maeztu CEX2020-001058-M. LG also acknowledges MCIN, AEI and the European Social Fund (ESF) “Investing in your future” under the 2019 Ramón y Cajal program RYC2019-027683-I. The Aarhus SN group is support by a Villum Experiment grant (number 28021) from VILLUM FONDEN and a Project 1 grant (8021-00170B) from the Independent Research Fund Denmark. PH acknowledge support by the National Science Foundation (NSF) grant AST-1715133. The work of the Carnegie Supernova Project has been supported by the NSF under the grants AST0306969, AST0607438, AST1008343, AST1613426, AST1613472 and AST613455. Software: matplotlib (Hunter 2007), seaborn (Waskom et al. 2017), numpy (Harris et al. 2020), pandas (McKinney 2010), scipy (Virtanen et al. 2020), emcee (Foreman-Mackey et al. 2013), coner (Foreman-Mackey 2016), george (Ambikasaran et al. 2016), astropy (Astropy Collaboration 2013, 2018), peakutils (Negri & Vestri 2017).

Euclid Consortium: N. Hamaus et al., 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 11 000 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, DM 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., NH, GP and JW are supported by the Excellence Cluster ORIGINS, which is funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under Germany’s Excellence Strategy – EXC-2094 – 390783311. MA, MCC and SE are supported by the eBOSS ANR grant (under contract ANR-16-CE31-0021) of the French National Research Agency, the OCEVU LABEX (Grant No. ANR-11-LABX-0060) and the A*MIDEX project (Grant No. ANR-11-IDEX-0001-02) funded by the Investissements d’Avenir French government program, and by CNES, the French National Space Agency. AP is supported by NASA ROSES grant 12-EUCLID12-0004, and NASA grant 15-WFIRST15-0008 to the Nancy Grace Roman Space Telescope Science Investigation Team “Cosmology with the High Latitude Survey”. GL is supported by the ANR BIG4 project, grant ANR-16-CE23-0002 of the French Agence Nationale de la Recherche. PN is funded by the Centre National d’Etudes Spatiales (CNES). We acknowledge use of the Python libraries NumPy (Harris et al. 2020), SciPy (Virtanen et al. 2020), Matplotlib (Hunter 2007), Astropy (Astropy Collaboration 2013, 2018), emcee (Foreman-Mackey et al. 2019), GetDist (Lewis 2019), healpy (Górski et al. 2005; Zonca et al. 2019), and PyAbel (Hickstein et al. 2019). This work has made use of CosmoHub (Carretero et al. 2017; Tallada et al. 2020). CosmoHub has been developed by the Port d’Informació Científica (PIC), maintained through a collaboration of the Institut de Física d’Altes Energies (IFAE) and the Centro de Investigaciones Energéticas, Medioambientales y Tecnológicas (CIEMAT) and the Institute of Space Sciences (CSIC & IEEC), and was partially funded by the “Plan Estatal de Investigación Científica y Técnica y de Innovación” program of the Spanish government. The Euclid Consortium acknowledges the European Space Agency and a number of agencies and institutes that have supported the development of Euclid, in particular the Academy of Finland, the Agenzia Spaziale Italiana, the Belgian Science Policy, the Canadian Euclid Consortium, the Centre National d’Etudes Spatiales, the Deutsches Zentrum für Luft- und Raumfahrt, the Danish Space Research Institute, the Fundação para a Ciência e a Tecnologia, the Ministerio de Economia y Competitividad, the National Aeronautics and Space Administration, the Netherlandse Onderzoekschool Voor Astronomie, the Norwegian Space Agency, the Romanian Space Agency, the State Secretariat for Education, Research and Innovation (SERI) at the Swiss Space Office (SSO), and the United Kingdom Space Agency.

We investigate the burstiness of star formation and the ionizing efficiency of a large sample of galaxies at $0.7 < z < 1.5$ using HST grism spectroscopy and deep ultraviolet (UV) imaging in the GOODS-N and GOODS-S fields. The star formation history (SFH) in these strong emission line low-mass galaxies indicates an elevated star formation rate (SFR) based on the H$\alpha$ emission line at a given stellar mass when compared to the standard main sequence. Moreover, when comparing the H$\alpha$ and UV SFR indicators, we find that an excess in SFR(H$\alpha$) compared to SFR(UV) is preferentially observed in lower-mass galaxies below $10^{9}$ M$\odot$, which are also the highest-EW galaxies. These findings suggest that the burstiness parameters of these strong emission line galaxies may differ from those inferred from hydrodynamical simulations and previous observations. For instance, a larger burstiness duty cycle would explain the observed SFR(H$\alpha$) excess. We also estimate the ionizing photon production efficiency $\xi_{ion}$, finding a median value of Log($\xi_{ion}$/erg$^{-1}$ Hz)$=24.80 \pm 0.26$ when adopting a Galactic dust correction for H$\alpha$ and an SMC one for the stellar component. We observe an increase of $\xi_{ion}$ with redshift, further confirming similar results at higher redshifts. We also find that $\xi_{ion}$ is strongly correlated with EW(H$\alpha$), which provides an approach for deriving $\xi_{ion}$ in early galaxies. Lower-mass, lower-luminosity galaxies have a higher $\xi_{ion}$. Overall, these results provide further support for faint galaxies playing a major role in the reionization of the Universe., Comment: 17 pages. Accepted for publication in MNRAS

We present a machine learning framework to simulate realistic galaxies for the Euclid Survey, producing more complex and realistic galaxies than the analytical simulations currently used in Euclid. The proposed method combines a control on galaxy shape parameters offered by analytic models with realistic surface brightness distributions learned from real Hubble Space Telescope observations by deep generative models. We simulate a galaxy field of 0.4 deg2 as it will be seen by the Euclid visible imager VIS, and we show that galaxy structural parameters are recovered to an accuracy similar to that for pure analytic Sérsic profiles. Based on these simulations, we estimate that the Euclid Wide Survey (EWS) will be able to resolve the internal morphological structure of galaxies down to a surface brightness of 22.5 mag arcsec−2, and the Euclid Deep Survey (EDS) down to 24.9 mag arcsec−2. This corresponds to approximately 250 million galaxies at the end of the mission and a 50% complete sample for stellar masses above 1010.6 M⊙ (resp. 109.6 M⊙) at a redshift z ∼ 0.5 for the EWS (resp. EDS). The approach presented in this work can contribute to improving the preparation of future high-precision cosmological imaging surveys by allowing simulations to incorporate more realistic galaxies. peerReviewed

We construct the halo mass function (HMF) from the GAMA galaxy group catalogue over the mass range 10^12.7M_sol to 10^15.5M_sol, and find good agreement with the expectation from LambdaCDM. In comparison to previous studies, this result extends the mass range over which the HMF has now been measured over by an order of magnitude. We combine the GAMA DR4 HMF with similar data from the SDSS DR12 and REFLEX II surveys, and fit a four-parameter Murray-Robotham-Power (MRP) function, valid at z~0.1, yielding: a density normalisation of: log10 (phi Mpc^3)=-3.96[+0.55,-0.82], a high mass turn-over of: log10(M/M_sol)=14.13[+0.43,-0.40], a low mass power law slope of: alpha=-1.68[+0.21,-0.24] , and a high mass softening parameter of: beta= 0.63[+0.25,-0.11]. If we fold in the constraint on Omega_M from Planck 2018 Cosmology, we are able to reduce these uncertainties further, but this relies on the assumption that the power-law trend can be extrapolated from 10^12.7M_sol to zero mass. Throughout, we highlight the effort needed to improve on our HMF measurement: improved halo mass estimates that do not rely on calibration to simulations; reduced halo mass uncertainties needed to mitigate the strong Eddington Bias that arises from the steepness of the HMF low mass slope; and deeper wider area spectroscopic surveys. To our halo mass limit of 10^12.7 M_sol, we are directly resolving (`seeing') 41+/-5 per cent of the total mass density, i.e. Omega_[M>12.7]=0.128+/-0.016, opening the door for the direct construction of 3D dark matter mass maps at Mpc resolution., Accepted for publication in MNRAS

We provide perturbation theory predictions for the HI intensity mapping power spectrum multipoles using the Effective Field Theory of Large Scale Structure (EFTofLSS), which should allow us to constrain cosmological parameters exploiting mildly nonlinear scales. Assuming survey specifications typical of proposed interferometric HI intensity mapping experiments like CHORD and PUMA, and realistic ranges of validity for the perturbation theory modelling, we run mock full shape MCMC analyses at a redshift bin centred at $z=0.5$, and compare with Stage-IV optical galaxy surveys. We include the impact of 21cm foreground removal using simulations-based prescriptions, and quantify the effects on the precision and accuracy of the parameter estimation. We vary 11 parameters in total: 3 cosmological parameters, 7 bias and counterterms parameters, and the HI brightness temperature. Amongst them, the 4 parameters of interest are: the cold dark matter density, $\omega_{\rm c}$, the Hubble parameter, $h$, the primordial amplitude of the power spectrum, $A_{\rm s}$, and the linear HI bias, $b_1$. For the best case scenario, we obtain unbiased constraints on all parameters with $, Comment: 11 pages, 1 table, 10 figures; matches version accepted for publication in MNRAS

Photometric data can be analysed using the 3D correlation function ξp to extract cosmological information via e.g. measurement of the Baryon Acoustic Oscillations (BAO). Previous studies modeled ξp assuming a Gaussian photo-z approximation. In this work we improve the modeling by incorporating realistic photo-z distribution. We show that the position of the BAO scale in ξp is determined by the photo-z distribution and the Jacobian of the transformation. The latter diverges at the transverse scale of the separation s⊥, and it explains why ξp traces the underlying correlation function at s⊥, rather than s, when the photo-z uncertainty σz/(1+ z) ≳ 0.02. We also obtain the Gaussian covariance for ξp. Due to photo-z mixing, the covariance of ξp shows strong off-diagonal elements. The high correlation of the data causes some issues to the data fitting. None the less, we find that either it can be solved by suppressing the largest eigenvalues of the covariance or it is not directly related to the BAO. We test our BAO fitting pipeline using a set of mock catalogs. The data set is dedicated for Dark Energy Survey Year 3 (DES Y3) BAO analyses and includes realistic photo-z distributions. The theory template is in good agreement with mock measurement. Based on the DES Y3 mocks, ξp statistic is forecast to constrain the BAO shift parameter α to be 1.001 ± 0.023, which is well consistent with the corresponding constraint derived from the angular correlation function measurements. Thus, ξp offers a competitive alternative for the photometric data analyses., KCC acknowledges the support from the National Science Foundation of China under the grant 11873102, the science research grants from the China Manned Space Project with NO. CMS-CSST-2021-B01, and the Science and Technology Program of Guangzhou, China (no. 202002030360). SA is supported by the MICUES project, funded by the EU H2020 Marie Sklodowska-Curie Actions grant no. 713366 (InterTalentum UAM) and ‘EU-HORIZON-2020-776247 Enabling Weak Lensing Cosmology (EWC)’. Funding for the DES Projects has been provided by the U.S. Department of Energy, the U.S. National Science Foundation, the Ministry of Science and Education of Spain, the Science and Technology Facilities Council of the United Kingdom, the Higher Education Funding Council for England, the National Center for Supercomputing Applications at the University of Illinois at Urbana-Champaign, the Kavli Institute of Cosmological Physics at the University of Chicago, the Center for Cosmology and Astro-Particle Physics at the Ohio State University, the Mitchell Institute for Fundamental Physics and Astronomy at Texas A&M University, Financiadora de Estudos e Projetos, Fundação Carlos Chagas Filho de Amparo à Pesquisa do Estado do Rio de Janeiro, Conselho Nacional de Desenvolvimento Científico e Tecnológico and the Ministério da Ciência, Tecnologia e Inovação, the Deutsche Forschungsgemeinschaft and the Collaborating Institutions in the Dark Energy Survey. The Collaborating Institutions are Argonne National Laboratory, the University of California at Santa Cruz, the University of Cambridge, Centro de Investigaciones Energéticas, Medioambientales y Tecnológicas-Madrid, the University of Chicago, University College London, the DES-Brazil Consortium, the University of Edinburgh, the Eidgenössische Technische Hochschule (ETH) Zürich, Fermi National Accelerator Laboratory, the University of Illinois at Urbana-Champaign, the Institut de Ciències de l’Espai (IEEC/CSIC), the Institut de Física d’Altes Energies, Lawrence Berkeley National Laboratory, the Ludwig-Maximilians Universität München and the associated Excellence Cluster Universe, the University of Michigan, NSF’s NOIRLab, the University of Nottingham, The Ohio State University, the University of Pennsylvania, the University of Portsmouth, SLAC National Accelerator Laboratory, Stanford University, the University of Sussex, Texas A&M University, and the OzDES Membership Consortium. Based in part on observations at Cerro Tololo Inter-American Observatory at NSF’s NOIRLab (NOIRLab Prop. ID 2012B-0001; PI: J. Frieman), which is managed by the Association of Universities for Research in Astronomy (AURA) under a cooperative agreement with the National Science Foundation. The DES data management system is supported by the National Science Foundation under grant numbers AST-1138766 and AST-1536171. The DES participants from Spanish institutions are partially supported by MICINN under grants ESP2017-89838, PGC2018-094773, PGC2018-102021, SEV-2016-0588, SEV-2016-0597, and MDM-2015-0509, some of which include ERDF funds from the European Union. IFAE is partially funded by the CERCA program of the Generalitat de Catalunya. Research leading to these results has received funding from the European Research Council under the European Union’s Seventh Framework Program (FP7/2007-2013), including ERC grant agreements 240672, 291329, and 306478. We acknowledge support from the Brazilian Instituto Nacional de Ciência e Tecnologia (INCT) do e-Universo (CNPq grant 465376/2014-2). This manuscript has been authored by Fermi Research Alliance, LLC under Contract No. DE-AC02-07CH11359 with the U.S. Department of Energy, Office of Science, Office of High Energy Physics.

Exploring Cosmic History and Origin (ECHO), popularly known as ‘CMB-Bha¯¯¯rat’, is a space mission that has been proposed to the Indian Space Research Organisation for the scientific exploitation of the cosmic microwave background (CMB) at the next level of precision and accuracy. The quest for the CMB polarization B-mode signals, generated by inflationary gravitational waves in the very early universe, is one of the key scientific goals of its experimental design. This work studies the potential of the proposed ECHO instrumental configuration to detect the target tensor-to-scalar ratio r ∼ 10−3 at 3σ significance level, which covers the predictions of a large class of inflationary models. We investigate the performance of two different component separation pipelines, NILC and Commander⁠, for the measurement of r in the presence of different physically motivated models of astrophysical foregrounds. For a simplistic foreground model (only polarized dust and synchrotron), both component separation pipelines can achieve the desired sensitivity of ECHO, i.e. σ(r = 0) ∼ (0.4–0.7) × 10−3. NILC performs better than Commander in terms of bias on recovered r for complex spectral models (power law and curved power law) of the synchrotron emission and complex dust models (dust decorrelation). Assuming 84 per cent delensing, we can achieve an improvement of σ(r = 0) by approximately 50 per cent as compared to the results obtained for the same configuration without any lensing correction. © 2022 The Author(s). Published by Oxford University Press on behalf of Royal Astronomical Society., DA acknowledges the University Grants Commission India for providing financial support as Senior Research Fellow. This work was supported by Science and Engineering Research Board, Department of Science and Technology, Govt. of India, grant number SERB/ECR/2018/000826. All the computation using the Commander code in this paper is done on the Pegasus cluster11 at IUCAA. The results in this paper have been derived using the HEALPIX package. DA acknowledges Prof. Hans Kristian Eriksen and Dr. Ranajoy Banerji for helping to install Commander and preparing the parameter files. DA also acknowledges Dr. Shabbir Shaikh for useful discussion. AS acknowledges the use of Padmanabha cluster12 at IISER-TVM for her work. AR acknowledges support from the ERC Consolidator Grant CMBSPEC (No. 725456) as part of the European Union’s Horizon 2020 research and innovation programme., With funding from the Spanish government through the Severo Ochoa Centre of Excellence accreditation SEV-2017-0709.

Astronomy & Astrophysics, 664, ISSN:0004-6361, ISSN:1432-0746

We present a new strong lensing (SL) model of the Hubble Frontier Fields galaxy cluster Abell 2744, at z=0.3072, by exploiting archival Hubble Space Telescope (HST) multi-band imaging and Multi Unit Spectroscopic Explorer (MUSE) follow-up spectroscopy. The lens model considers 90 spectroscopically confirmed multiple images (from 30 background sources), which represents the largest secure sample for this cluster field prior to the recently acquired James Webb Space Telescope observations. The inclusion of the sub-structures within several extended sources as model constraints allows us to accurately characterize the inner total mass distribution of the cluster and the position of the cluster critical lines. We include the lensing contribution of 225 cluster members, 202 of which are spectroscopically confirmed. We also measure the internal velocity dispersion of 85 cluster galaxies to independently estimate the role of the subhalo mass component in the lens model. We investigate the effect of the cluster environment on the total mass reconstruction of the cluster core with two different mass parameterizations. We consider the mass contribution from three external clumps, either based on previous weak-lensing studies, or extended HST imaging of luminous members around the cluster core. In the latter case, the observed positions of the multiple images are better reproduced, with a remarkable accuracy of 0.37", a factor of $\sim2$ smaller than previous lens models. We develop and make publicly available a Strong Lensing Online Tool (SLOT) to exploit the predictive power and the full statistical information of this and future models, through a simple graphical interface. We plan to apply our high-precision SL model to the first analysis of the GLASS-JWST-ERS program, specifically to measure the intrinsic physical properties of high-$z$ galaxies from robust magnification maps., Comment: 14 pages, 9 figures, 4 tables

We investigate how different mid-infrared (mid-IR) properties of galaxies trace the environment in which the galaxies are located. For this purpose, we first study the dependence of galaxy clustering on the absolute magnitude at 3.4 $\mu$m and redshift. Then, we look into the environmental dependence of mid-IR luminosities and the galaxy properties derived from these luminosities. We also explore how various infrared galaxy luminosity selections influence the galaxy clustering measurements. We use a set of W1 (3.4 $\mu$m) absolute magnitude ($M_\text{W1}$) selected samples from the Galaxy and Mass Assembly (GAMA) survey matched with mid-IR properties from the Wide-field Infrared Survey Explorer (WISE) in the redshift range $0.07 \leq z < 0.43$. We compute the galaxy two-point correlation function (2pCF) and compare the clustering lengths between subsamples binned in $M_\text{W1}$ and in redshift. We also measure the marked correlation functions (MCFs) using the luminosities in the WISE W1 to W4 (3.4 to 22 $\mu$m) bands as marks. Additionally, we compare the measurements of MCFs with different estimates of stellar mass and star formation rate used as marks. Finally, we check how different selections applied to the sample affect the clustering measurements. We show strong clustering dependence on the W1 absolute magnitude: galaxies brighter in the W1 band are more strongly clustered than their fainter counterparts. We also observe a lack of significant redshift dependence of clustering in the redshift range $0.07 \leq z < 0.43$. We show that although W1 and W2 bands are direct indicators of stellar mass, a galaxy sample selected based on W1 or W2 bands does not perfectly show the clustering behaviour of a stellar mass selected sample. Similar is the case with the proxy relation between W3 and W4 bands and star formation rate., Comment: 18 pages, 12 figures, matches the version published in A&A

Upcoming cosmological intensity mapping surveys will open new windows on the Universe, but they must first overcome a number of significant systematic effects, including polarization leakage. We present a formalism that uses scan strategy information to model the effect of different instrumental systematics on the recovered cosmological intensity signal for `single-dish' (autocorrelation) surveys. This modelling classifies different systematics according to their spin symmetry, making it particularly relevant for dealing with polarization leakage. We show how to use this formalism to calculate the expected contamination from different systematics as a function of the scanning strategy. Most importantly, we show how systematics can be disentangled from the intensity signal based on their spin properties via map-making. We illustrate this, using a set of toy models, for some simple instrumental systematics, demonstrating the ability to significantly reduce the contamination to the observed intensity signal. Crucially, unlike existing foreground removal techniques, this approach works for signals that are non-smooth in frequency, e.g. polarized foregrounds. These map-making approaches are simple to apply and represent an orthogonal and complementary approach to existing techniques for removing systematics from upcoming 21cm intensity mapping surveys.

One of the primary sources of uncertainties in modeling the cosmic-shear power spectrum on small scales is the effect of baryonic physics. Accurate cosmology for Stage-IV surveys requires knowledge of the matter power spectrum deep in the nonlinear regime at the percent level. Therefore, it is important to develop reliable mitigation techniques to take into account baryonic uncertainties if information from small scales is to be considered in the cosmological analysis. In this work, we develop a new mitigation method for dealing with baryonic physics for the case of the shear angular power spectrum. The method is based on an extended covariance matrix that incorporates baryonic uncertainties informed by hydrodynamical simulations. We use the results from 13 hydrodynamical simulations and the residual errors arising from a fit to a $\Lambda$CDM model using the extended halo model code {\tt HMCode} to account for baryonic physics. These residual errors are used to model a so-called theoretical error covariance matrix that is added to the original covariance matrix. In order to assess the performance of the method, we use the 2D tomographic shear from four hydrodynamical simulations that have different extremes of baryonic parameters as mock data and run a likelihood analysis comparing the residual bias on $\Omega_m$ and $\sigma_8$ of our method and the HMCode for an LSST-like survey. We use different modelling of the theoretical error covariance matrix to test the robustness of the method. We show that it is possible to reduce the bias in the determination of the tested cosmological parameters at the price of a modest decrease in the precision., Comment: 10 pages, 5 figures

Martinelli, M., et al., In physically realistic, scalar-field-based dynamical dark energy models (including, e.g., quintessence), one naturally expects the scalar field to couple to the rest of the model's degrees of freedom. In particular, a coupling to the electromagnetic sector leads to a time (redshift) dependence in the fine-structure constant and a violation of the weak equivalence principle. Here we extend the previous Euclid forecast constraints on dark energy models to this enlarged (but physically more realistic) parameter space, and forecast how well Euclid, together with high-resolution spectroscopic data and local experiments, can constrain these models. Our analysis combines simulated Euclid data products with astrophysical measurements of the fine-structure constant, α, and local experimental constraints, and it includes both parametric and non-parametric methods. For the astrophysical measurements of α, we consider both the currently available data and a simulated dataset representative of Extremely Large Telescope measurements that are expected to be available in the 2030s. Our parametric analysis shows that in the latter case, the inclusion of astrophysical and local data improves the Euclid dark energy figure of merit by between 8% and 26%, depending on the correct fiducial model, with the improvements being larger in the null case where the fiducial coupling to the electromagnetic sector is vanishing. These improvements would be smaller with the current astrophysical data. Moreover, we illustrate how a genetic algorithms based reconstruction provides a null test for the presence of the coupling. Our results highlight the importance of complementing surveys like Euclid with external data products, in order to accurately test the wider parameter spaces of physically motivated paradigms.

DES Collaboration: D. Zürcher et al., We constrain the matter density Ωm and the amplitude of density fluctuations σ8 within the ΛCDM cosmological model with shear peak statistics and angular convergence power spectra using mass maps constructed from the first three years of data of the Dark Energy Survey (DES Y3). We use tomographic shear peak statistics, including cross-peaks: peak counts calculated on maps created by taking a harmonic space product of the convergence of two tomographic redshift bins. Our analysis follows a forward-modelling scheme to create a likelihood of these statistics using N-body simulations, using a Gaussian process emulator. We take into account the uncertainty from the remaining, largely unconstrained ΛCDM parameters (Ωb, ns, and h). We include the following lensing systematics: multiplicative shear bias, photometric redshift uncertainty, and galaxy intrinsic alignment. Stringent scale cuts are applied to avoid biases from unmodelled baryonic physics. We find that the additional non-Gaussian information leads to a tightening of the constraints on the structure growth parameter yielding S8 ≡ σ8 √ Ωm/0.3 = 0.797+0.015−0.013 (68 per cent confidence limits), with a precision of 1.8 per cent, an improvement of 38 per cent compared to the angular power spectra only case. The results obtained with the angular power spectra and peak counts are found to be in agreement with each other and no significant difference in S8 is recorded. We find a mild tension of 1.5σ between our study and the results from Planck 2018, with our analysis yielding a lower S8. Furthermore, we observe that the combination of angular power spectra and tomographic peak counts breaks the degeneracy between galaxy intrinsic alignment AIA and S8, improving cosmological constraints. We run a suite of tests concluding that our results are robust and consistent with the results from other studies using DES Y3 data., The ETH Zurich Cosmology group acknowledges support by grants 200021_192243 and 200021_169130 of the Swiss National Science Foundation. We would also like to thank Uwe Schmitt from ETH Zürich for his support with the GitLab server and CI engine. Funding for the DES Projects has been provided by the U.S. Department of Energy, the U.S. National Science Foundation, the Ministry of Science and Education of Spain, the Science and Technology Facilities Council of the United Kingdom, the Higher Education Funding Council for England, the National Center for Supercomputing Applications at the University of Illinois at Urbana-Champaign, the Kavli Institute of Cosmological Physics at the University of Chicago, the Center for Cosmology and Astro-Particle Physic at the Ohio State University, the Mitchell Institute for Fundamental Physics and Astronomy at Texas A&M University, Financiadora de Estudos e Projetos, Fundacao Carlos Chagas Filho de Amparo a Pesquisa do Estado do Rio de Janeiro, Conselho Nacional de Desenvolvimento Científico e Tecnologico and the Ministerio da Ciencia, Tecnologia e Inovacao, the Deutsche Forschungsgemeinschaft and the Collaborating Institutions in the Dark Energy Survey. The Collaborating Institutions are Argonne National Laboratory, the University of California at Santa Cruz, the University of Cambridge, Centro de Investigaciones Energéticas, Medioambientales y Tecnologicas-Madrid, the University of Chicago, University College London, the DES-Brazil Consortium, the University of Edinburgh, the Eidgenoessische Technische Hochschule (ETH) Zurich, Fermi National Accelerator Laboratory, the University of Illinois at Urbana-Champaign, the Institut de Ciencies de l’Espai (IEEC/CSIC), the Institut de Fisica d’Altes Energies, Lawrence Berkeley National Laboratory, the Ludwig-Maximilians Universität Muenchen and the associated Excellence Cluster Universe, the University of Michigan, NFS’s NOIRLab, the University of Nottingham, the Ohio State University, the University of Pennsylvania, the University of Portsmouth, SLAC National Accelerator Laboratory, Stanford University, the University of Sussex, Texas A&M University, and the OzDES Membership Consortium. Based in part on observations at Cerro Tololo Inter-American Observatory at NSF’s NOIRLab (NOIRLab Prop.ID 2012B-0001; PI: J. Frieman), which is managed by the Association of Universities for Research in Astronomy (AURA) under a cooperative agreement with the National Science Foundation. Based on observations obtained with Planck,11 an ESA science mission with instruments and contributions directly funded by ESA Member States, NASA, and Canada.

We constrain the luminosity and redshift dependence of the intrinsic alignment (IA) of a nearly volume-limited sample of luminous red galaxies selected from the fourth public data release of the Kilo-Degree Survey (KiDS-1000). To measure the shapes of the galaxies, we used two complementary algorithms, finding consistent IA measurements for the overlapping galaxy sample. The global significance of IA detection across our two independent luminous red galaxy samples, with our favoured method of shape estimation, is $\sim10.7\sigma$. We find no significant dependence with redshift of the IA signal in the range $0.2, Comment: 21 pages, 14 figures. Accepted for publication in A&A

We present measurements of the radial profiles of the mass and galaxy number density around Sunyaev–Zel’dovich (SZ)-selected clusters using both weak lensing and galaxy counts. The clusters are selected from the Atacama Cosmology Telescope Data Release 5 and the galaxies from the Dark Energy Survey Year 3 data set. With signal-to-noise ratio of 62 (45) for galaxy (weak lensing) profiles over scales of about 0.2–20 h-1 Mpc, these are the highest precision measurements for SZ-selected clusters to date. Because SZ selection closely approximates mass selection, these measurements enable several tests of theoretical models of the mass and light distribution around clusters. Our main findings are: (1) The splashback feature is detected at a consistent location in both the mass and galaxy profiles and its location is consistent with predictions of cold dark matter N-body simulations. (2) The full mass profile is also consistent with the simulations. (3) The shapes of the galaxy and lensing profiles are remarkably similar for our sample over the entire range of scales, from well inside the cluster halo to the quasilinear regime. We measure the dependence of the profile shapes on the galaxy sample, redshift, and cluster mass. We extend the Diemer & Kravtsov model for the cluster profiles to the linear regime using perturbation theory and show that it provides a good match to the measured profiles. We also compare the measured profiles to predictions of the standard halo model and simulations that include hydrodynamics. Applications of these results to cluster mass estimation, cosmology, and astrophysics are discussed.

We perform a systematic study of the recently discovered Fundamental Plane of galaxy clusters (CFP) using ∼250 simulated clusters from The Three Hundred project, focusing on the stability of the plane against different temperature definitions and its dependence on the dynamical relaxation state of clusters. The CFP is characterized by T∝Mαsrβs⁠, defined with the gas temperature (T) and the characteristic halo scale radius and mass (rs and Ms) assuming a Navarro–Frenk–White halo description. We explore two definitions of weighted temperatures, namely mass-weighted and spectroscopic-like temperatures, in three radial ranges. The Three Hundred project clusters at z = 0 lie on a thin plane whose parameters (α, β) and dispersion (0.015–0.030 dex) depend on the gas temperature definition. The CFP for mass-weighted temperatures is closer to the virial equilibrium expectation (α = 1, β = −1) with a smaller dispersion. For gas temperatures measured within 500 h−1 kpc, the resulting CFP deviates the most from the virial expectation and shifts towards the similarity solution for a secondary infall model (α = 1.5, β = −2). Independently of the temperature definition, we find that clusters at z = 1 and relaxed clusters form a CFP similar to the virial expectation, unlike disturbed clusters exhibiting stronger evolution. Only systems formed over the last 4 Gyr present a CFP that is closer to the similarity solution. All these findings are compatible with the CFP obtained for a Cluster Lensing And Supernova survey with Hubble subsample excluding the hottest clusters with TX > 12 keV. © 2022 The Author(s)., LADG and KU acknowledge support from the Ministry of Science and Technology of Taiwan (grants MOST 106-2628-M-001-003-MY3 and MOST 109-2112-M-001-018-MY3) and from the Academia Sinica (grant AS-IA-107-M01). LADG thanks for financial support from the State Agency for Research of the Spanish MCIU through the ‘Center of Excellence Severo Ochoa’ award to the Instituto de Astrofísica de Andalucía (SEV-2017-0709), and to the PID2019-109067-GB100. EL receives support by contract ASI-INAF n.2017-14-H.0, whereas WC is supported by the European Research Council under grant number 670193 and by the STFC AGP grant ST/V000594/1 and further acknowledges the science research grants from the China Manned Space Project with no. CMS-CSST-2021-A01 and CMS-CSST-2021-B01. The authors are also grateful to Yutaka Fujita for sharing part of tables employed in his work, as well as the discussions carried out with him during this research, which contributed to improve this work. In addition, the authors thank the constructive and fruitful comments provided by the referee that helped to improve the content of this paper. This work has been made possible by The Three Hundred Collaboration. The simulations used in this paper have been performed in the MareNostrum Supercomputer at the Barcelona Supercomputing Center, thanks to CPU time granted by the Red Española de Supercomputación. As part of The Three Hundred Project, this work has received financial support from the European Union’s Horizon 2020 - Research and Innovation Framework Programme under the Marie Sklodowska-Curie Actions grant agreement number 734374, the LACEGAL project. For this research, we made use of multiple PYTHON packages, such as MATPLOTLIB (Hunter 2007), CORNER (Foreman-Mackey 2016), and NUMPY (Harris et al. 2020).

With the dramatic rise in high-quality galaxy data expected from Euclid and Vera C. Rubin Observatory, there will be increasing demand for fast high-precision methods for measuring galaxy fluxes. These will be essential for inferring the redshifts of the galaxies. In this paper, we introduce LUMOS, a deep learning method to measure photometry from galaxy images. LUMOS builds on BKGNET, an algorithm to predict the background and its associated error, and predicts the background-subtracted flux probability density function. We have developed LUMOS for data from the Physics of the Accelerating Universe Survey (PAUS), an imaging survey using a 40 narrow-band filter camera (PAUCam). PAUCam images are affected by scattered light, displaying a background noise pattern that can be predicted and corrected for. On average, LUMOS increases the SNR of the observations by a factor of 2 compared to an aperture photometry algorithm. It also incorporates other advantages like robustness towards distorting artefacts, e.g. cosmic rays or scattered light, the ability of deblending and less sensitivity to uncertainties in the galaxy profile parameters used to infer the photometry. Indeed, the number of flagged photometry outlier observations is reduced from 10 to 2 per cent, comparing to aperture photometry. Furthermore, with LUMOS photometry, the photo-z scatter is reduced by ≈10 per cent with the Deepz machine-learning photo-z code and the photo-z outlier rate by 20 per cent. The photo-z improvement is lower than expected from the SNR increment, however, currently the photometric calibration and outliers in the photometry seem to be its limiting factor., The PAU Survey is partially supported by MINECO under grants CSD2007-00060, AYA2015-71825, ESP2017-89838, PGC2018-094773, PGC2018-102021, SEV-2016-0588, SEV-2016-0597, MDM-2015-0509, PID2019-111317GB-C31 and Juan de la Cierva fellowship and LACEGAL and EWC Marie Sklodowska-Curie grant No 734374 and no.776247 with ERDF funds from the EU Horizon 2020 Programme, some of which include ERDF funds from the European Union. IEEC and IFAE are partially funded by the CERCA and Beatriu de Pinos program of the Generalitat de Catalunya. Funding for PAUS has also been provided by Durham University (via the ERC StG DEGAS-259586), ETH Zurich, Leiden University (via ERC StG ADULT-279396 and Netherlands Organisation for Scientific Research (NWO) Vici grant 639.043.512), Bochum University (via a Heisenberg grant of the Deutsche Forschungsgemeinschaft (Hi 1495/5-1) as well as an ERC Consolidator Grant (No. 770935)), University College London, Portsmouth support through the Royal Society Wolfson fellowship and from the European Union’s Horizon 2020 research and innovation programme under the grant agreement No 776247 EWC.

We measure the galaxy two- and three-point correlation functions at z = [0.5, 0.7] and z = [0.7, 0.9], from the Public Data Release 2 (PDR2) of the VIMOS Public Extragalactic Redshift Survey (VIPERS). We model the two statistics including a non-linear one-loop model for the two-point function and a tree-level model for the three-point function, and perform a joint likelihood analysis. The entire process and non-linear corrections are tested and validated through the use of the 153 highly realistic VIPERS mock catalogues, showing that they are robust down to scales as small as 10 h-1 Mpc. The mocks are also adopted to compute the covariance matrix that we use for the joint two- and three-point analysis. Despite the limited statistics of the two (volume-limited) subsamples analysed, we demonstrate that such a combination successfully breaks the degeneracy existing at two-point level between clustering amplitude σ8, linear bias b1, and the linear growth rate of fluctuations f. For the latter, in particular, we measure f(z=0.61)=0.64+0.55-0.37 and f(z = 0.8) = 1.0 ± 1.0, while the amplitude of clustering is found to be σ8(z = 0.61) = 0.50 ± 0.12 and σ8(z=0.8)=0.39+0.11-0.13}. These values are in excellent agreement with the extrapolation of a Planck cosmology., AV, EB, LG, and LM are supported by ASI/INAF agreement no. 2018-23-HH.0 ‘Scientific Activity for Euclid Mission, Phase D’ and INFN Project ‘InDark’. EB and LG are further supported by MIUR/PRIN 2017 ‘From Darklight to Dark Matter: Understanding the Galaxy–Matter Connection to Measure the Universe’. EB is also supported by ASI/INAF agreement no. 2017-14-H.O ‘Unveiling Dark Matter and Missing Baryons in the High-Energy Sky’. MM acknowledges the grants ASI no. I/023/12/0, ASI no. 2018-23-HH.0, and support from MIUR, PRIN 2017 (grant 20179ZF5KS). This research was supported by the Munich Institute for Astro- and Particle Physics (MIAPP) that is funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under Germany’s Excellence Strategy – EXC – 2094 - 390783311. LM also acknowledges the support from the grant PRIN-MIUR 2017 WSCC32.

We present a strong lensing analysis of the galaxy cluster PSZ1 G311.65-18.48 (z = 0.443) using multi-band observations with Hubble Space Telescope complemented with VLT/MUSE spectroscopic data. The MUSE observations provide redshift estimates for the lensed sources and help to reduce misidentification of the multiple images. Spectroscopic data are also used to measure the inner velocity dispersions of 15 cluster galaxies and calibrate the scaling relations to model the subhalo cluster component. The model is based on 62 multiple images grouped in 17 families belonging to four different sources. The majority of them are multiple images of compact stellar knots belonging to a single star-forming galaxy at z = 2.3702. This source is strongly lensed by the cluster to form the Sunburst Arc system. To accurately reproduce all the multiple images, we built a parametric mass model, which includes both cluster-scale and galaxy-scale components. The resulting model has a rms separation between the model-predicted and the observed positions of the multiple images of only 0.14″. We conclude that PSZ1 G311.65-18.48 has a relatively round projected shape and a large Einstein radius (29″ for zs = 2.3702), which could indicate that the cluster is elongated along the line of sight. The Sunburst Arc source is located at the intersection of a complex network of caustics, which explains why parts of the arc are imaged with unprecedented multiplicity (up to 12 times).