Subjects: Astronomy >> Astrophysical processes submitted time 2023-02-19
J. Adamek
R. E. Angulo
C. Arnold
M. Baldi
M. Biagetti
B. Bose
C. Carbone
T. Castro
J. Dakin
K. Dolag
W. Elbers
C. Fidler
C. Giocoli
S. Hannestad
F. Hassani
C. Hernández-Aguayo
K. Koyama
B. Li
R. Mauland
P. Monaco
Abstract： The measurement of the absolute neutrino mass scale from cosmological large-scale clustering data is one of the key science goals of the Euclid mission. Such a measurement relies on precise modelling of the impact of neutrinos on structure formation, which can be studied with $N$-body simulations. Here we present the results from a major code comparison effort to establish the maturity and reliability of numerical methods for treating massive neutrinos. The comparison includes eleven full $N$-body implementations (not all of them independent), two $N$-body schemes with approximate time integration, and four additional codes that directly predict or emulate the matter power spectrum. Using a common set of initial data we quantify the relative agreement on the nonlinear power spectrum of cold dark matter and baryons and, for the $N$-body codes, also the relative agreement on the bispectrum, halo mass function, and halo bias. We find that the different numerical implementations produce fully consistent results. We can therefore be confident that we can model the impact of massive neutrinos at the sub-percent level in the most common summary statistics. We also provide a code validation pipeline for future reference.
Peer Review Status:
Awaiting Review
Subjects: Astronomy >> Astrophysical processes submitted time 2023-02-19
Euclid Collaboration
L. Bisigello
C. J. Conselice
M. Baes
M. Bolzonella
M. Brescia
S. Cavuoti
O. Cucciati
A. Humphrey
L. K. Hunt
C. Maraston
L. Pozzetti
C. Tortora
S. E. van Mierlo
N. Aghanim
N. Auricchio
M. Baldi
R. Bender
C. Bodendorf
D. Bonino
Abstract： Next generation telescopes, like Euclid, Rubin/LSST, and Roman, will open new windows on the Universe, allowing us to infer physical properties for tens of millions of galaxies. Machine learning methods are increasingly becoming the most efficient tools to handle this enormous amount of data, because they are often faster and more accurate than traditional methods. We investigate how well redshifts, stellar masses, and star-formation rates (SFR) can be measured with deep learning algorithms for observed galaxies within data mimicking the Euclid and Rubin/LSST surveys. We find that Deep Learning Neural Networks and Convolutional Neutral Networks (CNN), which are dependent on the parameter space of the training sample, perform well in measuring the properties of these galaxies and have a better accuracy than methods based on spectral energy distribution fitting. CNNs allow the processing of multi-band magnitudes together with $H_{\scriptscriptstyle\rm E}$-band images. We find that the estimates of stellar masses improve with the use of an image, but those of redshift and SFR do not. Our best results are deriving i) the redshift within a normalised error of less than 0.15 for 99.9$\%$ of the galaxies with S/N>3 in the $H_{\scriptscriptstyle\rm E}$-band; ii) the stellar mass within a factor of two ($\sim0.3 \rm dex$) for 99.5$\%$ of the considered galaxies; iii) the SFR within a factor of two ($\sim0.3 \rm dex$) for $\sim$70$\%$ of the sample. We discuss the implications of our work for application to surveys as well as how measurements of these galaxy parameters can be improved with deep learning.
Peer Review Status:Awaiting Review
Subjects: Astronomy >> Astrophysical processes submitted time 2023-02-19
Euclid Collaboration
H. Bretonnière
U. Kuchner
M. Huertas-Company
E. Merlin
M. Castellano
D. Tuccillo
F. Buitrago
C. J. Conselice
A. Boucaud
B. Häußler
M. Kümmel
W. G. Hartley
A. Alvarez Ayllon
E. Bertin
F. Ferrari
L. Ferreira
R. Gavazzi
D. Hernández-Lang
G. Lucatelli
Abstract： 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.
Peer Review Status:Awaiting Review
Subjects: Astronomy >> Astrophysical processes submitted time 2023-02-19
Euclid Collaboration
L. Gabarra
C. Mancini
L. Rodriguez Munoz
G. Rodighiero
C. Sirignano
M. Scodeggio
M. Talia
S. Dusini
W. Gillard
B. R. Granett
E. Maiorano
M. Moresco
L. Paganin
E. Palazzi
L. Pozzetti
A. Renzi
E. Rossetti
D. Vergani
V. Allevato
Abstract： This work focuses on the pilot run of a simulation campaign aimed at investigating the spectroscopic capabilities of the Euclid Near-Infrared Spectrometer and Photometer (NISP), in terms of continuum and emission line detection in the context of galaxy evolutionary studies. To this purpose we constructed, emulated, and analysed the spectra of 4992 star-forming galaxies at $0.3 \leq z \leq 2.5$ using the NISP pixel-level simulator. We built the spectral library starting from public multi-wavelength galaxy catalogues, with value-added information on spectral energy distribution (SED) fitting results, and from Bruzual and Charlot (2003) stellar population templates. Rest-frame optical and near-IR nebular emission lines were included using empirical and theoretical relations. We inferred the 3.5$\sigma$ NISP red grism spectroscopic detection limit of the continuum measured in the $H$ band for star-forming galaxies with a median disk half-light radius of \ang{;;0.4} at magnitude $H= 19.5\pm0.2\,$AB$\,$mag for the Euclid Wide Survey and at $H = 20.8\pm0.6\,$AB$\,$mag for the Euclid Deep Survey. We found a very good agreement with the red grism emission line detection limit requirement for the Wide and Deep surveys. We characterised the effect of the galaxy shape on the detection capability of the red grism and highlighted the degradation of the quality of the extracted spectra as the disk size increases. In particular, we found that the extracted emission line signal to noise ratio (SNR) drops by $\sim\,$45$\%$ when the disk size ranges from \ang{;;0.25} to \ang{;;1}. These trends lead to a correlation between the emission line SNR and the stellar mass of the galaxy and we demonstrate the effect in a stacking analysis unveiling emission lines otherwise too faint to detect.
Peer Review Status:Awaiting Review
Subjects: Astronomy >> Astrophysical processes submitted time 2023-02-19
Euclid Collaboration
A. Humphrey
L. Bisigello
P. A. C. Cunha
M. Bolzonella
S. Fotopoulou
K. Caputi
C. Tortora
G. Zamorani
P. Papaderos
D. Vergani
J. Brinchmann
M. Moresco
A. Amara
N. Auricchio
M. Baldi
R. Bender
D. Bonino
E. Branchini
M. Brescia
Abstract： The Euclid Space Telescope will provide deep imaging at optical and near-infrared wavelengths, along with slitless near-infrared spectroscopy, across ~15,000 sq deg of the sky. Euclid is expected to detect ~12 billion astronomical sources, facilitating new insights into cosmology, galaxy evolution, and various other topics. To optimally exploit the expected very large data set, there is the need to develop appropriate methods and software. Here we present a novel machine-learning based methodology for selection of quiescent galaxies using broad-band Euclid I_E, Y_E, J_E, H_E photometry, in combination with multiwavelength photometry from other surveys. The ARIADNE pipeline uses meta-learning to fuse decision-tree ensembles, nearest-neighbours, and deep-learning methods into a single classifier that yields significantly higher accuracy than any of the individual learning methods separately. The pipeline has `sparsity-awareness', so that missing photometry values are still informative for the classification. Our pipeline derives photometric redshifts for galaxies selected as quiescent, aided by the `pseudo-labelling' semi-supervised method. After application of the outlier filter, our pipeline achieves a normalized mean absolute deviation of ~< 0.03 and a fraction of catastrophic outliers of ~< 0.02 when measured against the COSMOS2015 photometric redshifts. We apply our classification pipeline to mock galaxy photometry catalogues corresponding to three main scenarios: (i) Euclid Deep Survey with ancillary ugriz, WISE, and radio data; (ii) Euclid Wide Survey with ancillary ugriz, WISE, and radio data; (iii) Euclid Wide Survey only. Our classification pipeline outperforms UVJ selection, in addition to the Euclid I_E-Y_E, J_E-H_E and u-I_E,I_E-J_E colour-colour methods, with improvements in completeness and the F1-score of up to a factor of 2. (Abridged)
Peer Review Status:Awaiting Review
Subjects: Astronomy >> Astrophysical processes submitted time 2023-02-19
Euclid Collaboration
V. Ajani
M. Baldi
A. Barthelemy
A. Boyle
P. Burger
V. F. Cardone
S. Cheng
S. Codis
C. Giocoli
J. Harnois-Déraps
S. Heydenreich
V. Kansal
M. Kilbinger
L. Linke
C. Llinares
N. Martinet
C. Parroni
A. Peel
S. Pires
Abstract： Recent cosmic shear studies have shown that higher-order statistics (HOS) developed by independent teams now outperform standard two-point estimators in terms of statistical precision thanks to their sensitivity to the non-Gaussian features of large-scale structure. The aim of the Higher-Order Weak Lensing Statistics (HOWLS) project is to assess, compare, and combine the constraining power of $10$ different HOS on a common set of $Euclid$-like mocks, derived from N-body simulations. In this first paper of the HOWLS series we compute the non-tomographic ($\Omega_{\rm m}$, $\sigma_8$) Fisher information for one-point probability distribution function, peak counts, Minkowski functionals, Betti numbers, persistent homology Betti numbers and heatmap, and scattering transform coefficients, and compare them to the shear and convergence two-point correlation functions in the absence of any systematic bias. We also include forecasts for three implementations of higher-order moments, but these cannot be robustly interpreted as the Gaussian likelihood assumption breaks down for these statistics. Taken individually, we find that each HOS outperforms the two-point statistics by a factor of around $2$ in the precision of the forecasts with some variations across statistics and cosmological parameters. When combining all the HOS, this increases to a $4.5$ times improvement, highlighting the immense potential of HOS for cosmic shear cosmological analyses with $Euclid$. The data used in this analysis are publicly released with the paper.
Peer Review Status:Awaiting Review
Subjects: Astronomy >> Astrophysical processes submitted time 2023-02-19
L. Cabayol
M. Eriksen
J. Carretero
R. Casas
F. J. Castander
E. Fernández
J. Garcia-Bellido
E. Gaztanaga
H. Hildebrandt
H. Hoekstra
B. Joachimi
R. Miquel
C. Padilla
A. Pocino
E. Sanchez
S. Serrano
I. Sevilla
M. Siudek
P. Tallada-Crespí
N. Aghanim
Abstract： Current and future imaging surveys require photometric redshifts (photo-zs) to be estimated for millions of galaxies. Improving the photo-z quality is a major challenge but is needed to advance our understanding of cosmology. In this paper we explore how the synergies between narrow-band photometric data and large imaging surveys can be exploited to improve broadband photometric redshifts. We used a multi-task learning (MTL) network to improve broadband photo-z estimates by simultaneously predicting the broadband photo-z and the narrow-band photometry from the broadband photometry. The narrow-band photometry is only required in the training field, which also enables better photo-z predictions for the galaxies without narrow-band photometry in the wide field. This technique was tested with data from the Physics of the Accelerating Universe Survey (PAUS) in the COSMOS field. We find that the method predicts photo-zs that are 13% more precise down to magnitude i_{AB} < 23; the outlier rate is also 40% lower when compared to the baseline network. Furthermore, MTL reduces the photo-z bias for high-redshift galaxies, improving the redshift distributions for tomographic bins with z>1. Applying this technique to deeper samples is crucial for future surveys such as \Euclid or LSST. For simulated data, training on a sample with i_{AB} <23, the method reduces the photo-z scatter by 16% for all galaxies with i_{AB}<25. We also studied the effects of extending the training sample with photometric galaxies using PAUS high-precision photo-zs, which reduces the photo-z scatter by 20% in the COSMOS field.
Peer Review Status:Awaiting Review
Subjects: Astronomy >> Astrophysical processes submitted time 2023-02-19
Euclid Collaboration
A. C. Deshpande
T. Kitching
A. Hall
M. L. Brown
N. Aghanim
L. Amendola
N. Auricchio
M. Baldi
R. Bender
D. Bonino
E. Branchini
M. Brescia
J. Brinchmann
S. Camera
G. P. Candini
V. Capobianco
C. Carbone
V. F. Cardone
J. Carretero
Abstract： This work considers which higher-order effects in modelling the cosmic shear angular power spectra must be taken into account for Euclid. We identify which terms are of concern, and quantify their individual and cumulative impact on cosmological parameter inference from Euclid. We compute the values of these higher-order effects using analytic expressions, and calculate the impact on cosmological parameter estimation using the Fisher matrix formalism. We review 24 effects and find the following potentially need to be accounted for: the reduced shear approximation, magnification bias, source-lens clustering, source obscuration, local Universe effects, and the flat Universe assumption. Upon computing these explicitly, and calculating their cosmological parameter biases, using a maximum multipole of $\ell=5000$, we find that the magnification bias, source-lens clustering, source obscuration, and local Universe terms individually produce significant ($\,>0.25\sigma$) cosmological biases in one or more parameters, and accordingly must be accounted for. In total, over all effects, we find biases in $\Omega_{\rm m}$, $\Omega_{\rm b}$, $h$, and $\sigma_{8}$ of $0.73\sigma$, $0.28\sigma$, $0.25\sigma$, and $-0.79\sigma$, respectively, for flat $\Lambda$CDM. For the $w_0w_a$CDM case, we find biases in $\Omega_{\rm m}$, $\Omega_{\rm b}$, $h$, $n_{\rm s}$, $\sigma_{8}$, and $w_a$ of $1.49\sigma$, $0.35\sigma$, $-1.36\sigma$, $1.31\sigma$, $-0.84\sigma$, and $-0.35\sigma$, respectively; which are increased relative to the $\Lambda$CDM due to additional degeneracies as a function of redshift and scale.
Peer Review Status:Awaiting Review
Subjects: Astronomy >> Astrophysical processes submitted time 2023-02-19
H. Camacho
F. Andrade-Oliveira
A. Troja
R. Rosenfeld
L. Faga
R. Gomes
C. Doux
X. Fang
M. Lima
V. Miranda
T. F. Eifler
O. Friedrich
M. Gatti
G. M. Bernstein
J. Blazek
S. L. Bridle
A. Choi
C. Davis
J. DeRose
E. Gaztanaga
Abstract： We perform a cosmic shear analysis in harmonic space using the first year of data collected by the Dark Energy Survey (DES-Y1). We measure the cosmic weak lensing shear power spectra using the Metacalibration catalogue and perform a likelihood analysis within the framework of CosmoSIS. We set scale cuts based on baryonic effects contamination and model redshift and shear calibration uncertainties as well as intrinsic alignments. We adopt as fiducial covariance matrix an analytical computation accounting for the mask geometry in the Gaussian term, including non-Gaussian contributions. A suite of 1200 lognormal simulations is used to validate the harmonic space pipeline and the covariance matrix. We perform a series of stress tests to gauge the robustness of the harmonic space analysis. Finally, we use the DES-Y1 pipeline in configuration space to perform a similar likelihood analysis and compare both results, demonstrating their compatibility in estimating the cosmological parameters $S_8$, $\sigma_8$ and $\Omega_m$. The methods implemented and validated in this paper will allow us to perform a consistent harmonic space analysis in the upcoming DES data.
Peer Review Status:Awaiting Review
Subjects: Astronomy >> Astrophysical processes submitted time 2023-02-19
A. Amon
N. C. Robertson
H. Miyatake
C. Heymans
M. White
J. DeRose
S. Yuan
R. H. Wechsler
T. N. Varga
S. Bocquet
A. Dvornik
S. More
A. J. Ross
H. Hoekstra
A. Alarcon
M. Asgari
J. Blazek
A. Campos
R. Chen
A. Choi
Abstract： We evaluate the consistency between lensing and clustering probes of
large-scale structure based on measurements of projected galaxy clustering from
BOSS combined with overlapping galaxy-galaxy lensing from three surveys: DES
Y3, HSC Y1, and KiDS-1000. An intra-lensing-survey study finds good agreement
between these lensing data. We model the observations using the Dark Emulator
and fit the data at two fixed cosmologies: Planck, with $S_8=0.83$, and a
Lensing cosmology with $S_8=0.76$. For a joint analysis limited to scales with
$R>5.25h^{-1}$Mpc, we find that both cosmologies provide an acceptable fit to
the data. Full utilisation of the small-scale clustering and lensing
measurements is hindered by uncertainty in the impact of baryon feedback and
assembly bias, which we account for with a reasoned theoretical error budget.
We incorporate a systematic scaling parameter for each redshift bin, $A$, that
decouples the lensing and clustering to capture any inconsistency. When a wide
range of scales ($0.15
Peer Review Status:Awaiting Review
Subjects: Astronomy >> Astrophysical processes submitted time 2023-02-19
Euclid Collaboration
C. Giocoli
M. Meneghetti
E. Rasia
S. Borgani
G. Despali
G. F. Lesci
F. Marulli
L. Moscardini
M. Sereno
W. Cui
A. Knebe
G. Yepes
T. Castro
P. -S. Corasaniti
S. Pires
G. Castignani
L. Ingoglia
T. Schrabback
G. W. Pratt
Abstract： The photometric catalogue of galaxy clusters extracted from ESA Euclid data is expected to be very competitive for cosmological studies. Using state-of-the-art hydrodynamical simulations, we present systematic analyses simulating the expected weak lensing profiles from clusters in a variety of dynamic states and at wide range of redshifts. In order to derive cluster masses, we use a model consistent with the implementation within the Euclid Consortium of the dedicated processing function and find that, when jointly modelling mass and the concentration parameter of the Navarro-Frenk-White halo profile, the weak lensing masses tend to be, on average, biased low with respect to the true mass. Using a fixed value for the concentration, the mass bias is diminished along with its relative uncertainty. Simulating the weak lensing signal by projecting along the directions of the axes of the moment of inertia tensor ellipsoid, we find that orientation matters: when clusters are oriented along the major axis the lensing signal is boosted, and the recovered weak lensing mass is correspondingly overestimated. Typically, the weak lensing mass bias of individual clusters is modulated by the weak lensing signal-to-noise ratio, and the negative mass bias tends to be larger toward higher redshifts. However, when we use a fixed value of the concentration parameter the redshift evolution trend is reduced. These results provide a solid basis for the weak-lensing mass calibration required by the cosmological application of future cluster surveys from Euclid and Rubin.
Peer Review Status:Awaiting Review
Subjects: Astronomy >> Astrophysical processes submitted time 2023-02-19
K. Naidoo
H. Johnston
B. Joachimi
J. L. van den Busch
H. Hildebrandt
O. Ilbert
O. Lahav
N. Aghanim
B. Altieri
A. Amara
M. Baldi
R. Bender
C. Bodendorf
E. Branchini
M. Brescia
J. Brinchmann
S. Camera
V. Capobianco
C. Carbone
J. Carretero
Abstract： Cosmological constraints from key probes of the Euclid imaging survey rely
critically on the accurate determination of the true redshift distributions,
$n(z)$, of tomographic redshift bins. We determine whether the mean redshift,
$
Peer Review Status:Awaiting Review
Subjects: Astronomy >> Astrophysical processes submitted time 2023-02-19
Euclid Collaboration
A. Fumagalli
A. Saro
S. Borgani
T. Castro
M. Costanzi
P. Monaco
E. Munari
E. Sefusatti
N. Aghanim
N. Auricchio
M. Baldi
C. Bodendorf
D. Bonino
E. Branchini
M. Brescia
J. Brinchmann
S. Camera
V. Capobianco
C. Carbone
Abstract： Aims. We validate a semi-analytical model for the covariance of real-space 2-point correlation function of galaxy clusters. Methods. Using 1000 PINOCCHIO light cones mimicking the expected Euclid sample of galaxy clusters, we calibrate a simple model to accurately describe the clustering covariance. Then, we use such a model to quantify the likelihood analysis response to variations of the covariance, and investigate the impact of a cosmology-dependent matrix at the level of statistics expected for the Euclid survey of galaxy clusters. Results. We find that a Gaussian model with Poissonian shot-noise does not correctly predict the covariance of the 2-point correlation function of galaxy clusters. By introducing few additional parameters fitted from simulations, the proposed model reproduces the numerical covariance with 10 per cent accuracy, with differences of about 5 per cent on the figure of merit of the cosmological parameters $\Omega_{\rm m}$ and $\sigma_8$. Also, we find that the cosmology-dependence of the covariance adds valuable information that is not contained in the mean value, significantly improving the constraining power of cluster clustering. Finally, we find that the cosmological figure of merit can be further improved by taking mass binning into account. Our results have significant implications for the derivation of cosmological constraints from the 2-point clustering statistics of the Euclid survey of galaxy clusters.
Peer Review Status:Awaiting Review
Subjects: Astronomy >> Astrophysical processes submitted time 2023-02-19
A. Porredon
M. Crocce
J. Elvin-Poole
R. Cawthon
G. Giannini
J. De Vicente
A. Carnero Rosell
I. Ferrero
E. Krause
X. Fang
J. Prat
M. Rodriguez-Monroy
S. Pandey
A. Pocino
F. J. Castander
A. Choi
A. Amon
I. Tutusaus
S. Dodelson
I. Sevilla-Noarbe
Abstract： Two of the most sensitive probes of the large scale structure of the universe are the clustering of galaxies and the tangential shear of background galaxy shapes produced by those foreground galaxies, so-called galaxy-galaxy lensing. Combining the measurements of these two two-point functions leads to cosmological constraints that are independent of the galaxy bias factor. The optimal choice of foreground, or lens, galaxies is governed by the joint, but conflicting requirements to obtain accurate redshift information and large statistics. We present cosmological results from the full 5000 sq. deg. of the Dark Energy Survey first three years of observations (Y3) combining those two-point functions, using for the first time a magnitude-limited lens sample (MagLim) of 11 million galaxies especially selected to optimize such combination, and 100 million background shapes. We consider two cosmological models, flat $\Lambda$CDM and $w$CDM. In $\Lambda$CDM we obtain for the matter density $\Omega_m = 0.320^{+0.041}_{-0.034}$ and for the clustering amplitude $S_8 = 0.778^{+0.037}_{-0.031}$, at 68% C.L. The latter is only 1$\sigma$ smaller than the prediction in this model informed by measurements of the cosmic microwave background by the Planck satellite. In $w$CDM we find $\Omega_m = 0.32^{+0.044}_{-0.046}$, $S_8=0.777^{+0.049}_{-0.051}$, and dark energy equation of state $w=-1.031^{+0.218}_{-0.379}$. We find that including smaller scales while marginalizing over non-linear galaxy bias improves the constraining power in the $\Omega_m-S_8$ plane by $31$% and in the $\Omega_m-w$ plane by $41$% while yielding consistent cosmological parameters from those in the linear bias case. These results are combined with those from cosmic shear in a companion paper to present full DES-Y3 constraints from the three two-point functions (3x2pt).
Peer Review Status:Awaiting Review
Subjects: Astronomy >> Astrophysical processes submitted time 2023-02-19
J. Sánchez
Y. Omori
C. Chang
L. E. Bleem
T. Crawford
A. Drlica-Wagner
S. Raghunathan
G. Zacharegkas
T. M. C. Abbott
M. Aguena
A. Alarcon
S. Allam
O. Alves
A. Amon
S. Avila
E. Baxter
K. Bechtol
B. A. Benson
G. M. Bernstein
E. Bertin
Abstract： We cross-correlate positions of galaxies measured in data from the first three years of the Dark Energy Survey with Compton-$y$-maps generated using data from the South Pole Telescope (SPT) and the {\it Planck} mission. We model this cross-correlation measurement together with the galaxy auto-correlation to constrain the distribution of gas in the Universe. We measure the hydrostatic mass bias or, equivalently, the mean halo bias-weighted electron pressure $\langle b_{h}P_{e}\rangle$, using large-scale information. We find $\langle b_{h}P_{e}\rangle$ to be $[0.16^{+0.03}_{-0.04},0.28^{+0.04}_{-0.05},0.45^{+0.06}_{-0.10},0.54^{+0.08}_{-0.07},0.61^{+0.08}_{-0.06},0.63^{+0.07}_{-0.08}]$ meV cm$^{-3}$ at redshifts $z \sim [0.30, 0.46, 0.62,0.77, 0.89, 0.97]$. These values are consistent with previous work where measurements exist in the redshift range. We also constrain the mean gas profile using small-scale information, enabled by the high-resolution of the SPT data. We compare our measurements to different parametrized profiles based on the cosmo-OWLS hydrodynamical simulations. We find that our data are consistent with the simulation that assumes an AGN heating temperature of $10^{8.5}$K but are incompatible with the model that assumes an AGN heating temperature of $10^{8.0}$K. These comparisons indicate that the data prefer a higher value of electron pressure than the simulations within $r_{500c}$ of the galaxies' halos.
Peer Review Status:Awaiting Review
Subjects: Astronomy >> Astrophysical processes submitted time 2023-02-19
D. Hernández-Lang
J. J. Mohr
M. Klein
S. Grandis
J. -B. Melin
P. Tarrío
M. Arnaud
G. W. Pratt
T. M. C. Abbott
M. Aguena
O. Alves
F. Andrade-Oliveira
D. Bacon
E. Bertin
D. Brooks
D. L. Burke
A. Carnero Rosell
M. Carrasco Kind
J. Carretero
F. J. Castander
Abstract： We present the first systematic follow-up of Planck Sunyaev-Zeldovich effect (SZE) selected candidates down to signal-to-noise (S/N) of 3 over the 5000 deg$^2$ covered by the Dark Energy Survey. Using the MCMF cluster confirmation algorithm, we identify optical counterparts, determine photometric redshifts and richnesses and assign a parameter, $f_{\rm cont}$, that reflects the probability that each SZE-optical pairing represents a real cluster rather than a random superposition of physically unassociated systems. The new MADPSZ cluster catalogue consists of 1092 MCMF confirmed clusters and has a purity of 85%. We present the properties of subsamples of the MADPSZ catalogue that have purities ranging from 90% to 97.5%, depending on the adopted $f_{\rm cont}$ threshold. $M_{500}$ halo mass estimates, redshifts, richnesses, and optical centers are presented for all MADPSZ clusters. The MADPSZ catalogue adds 828 previously unknown Planck identified clusters over the DES footprint and provides redshifts for an additional 50 previously published Planck selected clusters with S/N>4.5. Using the subsample with spectroscopic redshifts, we demonstrate excellent cluster photo-$z$ performance with an RMS scatter in $\Delta z/(1+z)$ of 0.47%. Our MCMF based analysis allows us to infer the contamination fraction of the initial S/N>3 Planck selected candidate list, which is 50%. We present a method of estimating the completeness of the MADPSZ cluster sample and $f_{\rm cont}$ selected subsamples. In comparison to the previously published Planck cluster catalogues. this new S/N $>$ 3 MCMF confirmed cluster catalogue populates the lower mass regime at all redshifts and includes clusters up to z$\sim$1.3.
Peer Review Status:Awaiting Review
Subjects: Astronomy >> Astrophysical processes submitted time 2023-02-19
DES Collaboration
T. M. C. Abbott
M. Aguena
A. Alarcon
O. Alves
A. Amon
J. Annis
S. Avila
D. Bacon
E. Baxter
K. Bechtol
M. R. Becker
G. M. Bernstein
S. Birrer
J. Blazek
S. Bocquet
A. Brandao-Souza
S. L. Bridle
D. Brooks
D. L. Burke
Abstract： We constrain extensions to the $\Lambda$CDM model using measurements from the Dark Energy Survey's first three years of observations and external data. The DES data are the two-point correlation functions of weak gravitational lensing, galaxy clustering, and their cross-correlation. We use simulated data and blind analyses of real data to validate the robustness of our results. In many cases, constraining power is limited by the absence of nonlinear predictions that are reliable at our required precision. The models are: dark energy with a time-dependent equation of state, non-zero spatial curvature, sterile neutrinos, modifications of gravitational physics, and a binned $\sigma_8(z)$ model which serves as a probe of structure growth. For the time-varying dark energy equation of state evaluated at the pivot redshift we find $(w_{\rm p}, w_a)= (-0.99^{+0.28}_{-0.17},-0.9\pm 1.2)$ at 68% confidence with $z_{\rm p}=0.24$ from the DES measurements alone, and $(w_{\rm p}, w_a)= (-1.03^{+0.04}_{-0.03},-0.4^{+0.4}_{-0.3})$ with $z_{\rm p}=0.21$ for the combination of all data considered. Curvature constraints of $\Omega_k=0.0009\pm 0.0017$ and effective relativistic species $N_{\rm eff}=3.10^{+0.15}_{-0.16}$ are dominated by external data. For massive sterile neutrinos, we improve the upper bound on the mass $m_{\rm eff}$ by a factor of three compared to previous analyses, giving 95% limits of $(\Delta N_{\rm eff},m_{\rm eff})\leq (0.28, 0.20\, {\rm eV})$. We also constrain changes to the lensing and Poisson equations controlled by functions $\Sigma(k,z) = \Sigma_0 \Omega_{\Lambda}(z)/\Omega_{\Lambda,0}$ and $\mu(k,z)=\mu_0 \Omega_{\Lambda}(z)/\Omega_{\Lambda,0}$ respectively to $\Sigma_0=0.6^{+0.4}_{-0.5}$ from DES alone and $(\Sigma_0,\mu_0)=(0.04\pm 0.05,0.08^{+0.21}_{-0.19})$ for the combination of all data. Overall, we find no significant evidence for physics beyond $\Lambda$CDM.
Peer Review Status:Awaiting Review
Subjects: Astronomy >> Astrophysical processes submitted time 2023-02-19
E. Zaborowski
A. Drlica-Wagner
F. Ashmead
J. F. Wu
R. Morgan
C. R. Bom
A. J. Shajib
S. Birrer
W. Cerny
L. Buckley-Geer
B. Mutlu-Pakdil
P. S. Ferguson
K. Glazebrook
S. J. Gonzalez Lozano
Y. Gordon
M. Martinez
V. Manwadkar
J. O'Donnell
J. Poh
A. Riley
Abstract： We perform a search for galaxy-galaxy strong lens systems using a convolutional neural network (CNN) applied to imaging data from the first public data release of the DECam Local Volume Exploration Survey (DELVE), which contains $\sim 520$ million astronomical sources covering $\sim 4,000$ $\mathrm{deg}^2$ of the southern sky to a $5\sigma$ point-source depth of $g=24.3$, $r=23.9$, $i=23.3$, and $z=22.8$ mag. Following the methodology of similar searches using DECam data, we apply color and magnitude cuts to select a catalog of $\sim 11$ million extended astronomical sources. After scoring with our CNN, the highest scoring 50,000 images were visually inspected and assigned a score on a scale from 0 (definitely not a lens) to 3 (very probable lens). We present a list of 617 strong lens candidates, 599 of which are previously unreported. We categorize our candidates using their human-assigned scores, resulting in 60 Grade A candidates, 160 Grade B candidates, and 397 Grade C candidates. We additionally highlight 8 potential quadruply lensed quasars from this sample. Due to the location of our search footprint in the northern Galactic cap ($b > 10$ deg) and southern celestial hemisphere (${\rm Dec.}<0$ deg), our candidate list has little overlap with other existing ground-based searches. Where our search footprint does overlap with other searches, we find a significant number of high-quality candidates which were previously unidentified, indicating a degree of orthogonality in our methodology. We report properties of our candidates including apparent magnitude and Einstein radius estimated from the image separation.
Peer Review Status:Awaiting Review
Subjects: Astronomy >> Astrophysical processes submitted time 2023-02-19
C. Sánchez
A. Alarcon
G. M. Bernstein
J. Sanchez
S. Pandey
M. Raveri
J. Prat
N. Weaverdyck
I. Sevilla-Noarbe
C. Chang
E. Baxter
Y. Omori
B. Jain
O. Alves
A. Amon
K. Bechtol
M. R. Becker
J. Blazek
A. Choi
A. Campos
Abstract： The fiducial cosmological analyses of imaging galaxy surveys like the Dark Energy Survey (DES) typically probe the Universe at redshifts $z < 1$. This is mainly because of the limited depth of these surveys, and also because such analyses rely heavily on galaxy lensing, which is more efficient at low redshifts. In this work we present the selection and characterization of high-redshift galaxy samples using DES Year 3 data, and the analysis of their galaxy clustering measurements. In particular, we use galaxies that are fainter than those used in the previous DES Year 3 analyses and a Bayesian redshift scheme to define three tomographic bins with mean redshifts around $z \sim 0.9$, $1.2$ and $1.5$, which significantly extend the redshift coverage of the fiducial DES Year 3 analysis. These samples contain a total of about 9 million galaxies, and their galaxy density is more than 2 times higher than those in the DES Year 3 fiducial case. We characterize the redshift uncertainties of the samples, including the usage of various spectroscopic and high-quality redshift samples, and we develop a machine-learning method to correct for correlations between galaxy density and survey observing conditions. The analysis of galaxy clustering measurements, with a total signal-to-noise $S/N \sim 70$ after scale cuts, yields robust cosmological constraints on a combination of the fraction of matter in the Universe $\Omega_m$ and the Hubble parameter $h$, $\Omega_m h = 0.195^{+0.023}_{-0.018}$, and 2-3% measurements of the amplitude of the galaxy clustering signals, probing galaxy bias and the amplitude of matter fluctuations, $b \sigma_8$. A companion paper $\textit{(in preparation)}$ will present the cross-correlations of these high-$z$ samples with CMB lensing from Planck and SPT, and the cosmological analysis of those measurements in combination with the galaxy clustering presented in this work.
Peer Review Status:Awaiting Review
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