Euclid preparation Huertas-Company, M.; Lanusse, F.; Jullo, E. ...
Astronomy and astrophysics (Berlin),
01/2022, Letnik:
657
Journal Article
Recenzirano
Odprti dostop
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 deg
2
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 10
10.6
M
⊙
(resp. 10
9.6
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.
Abstract
The Complete Calibration of the Color–Redshift Relation (C3R2) survey is obtaining spectroscopic redshifts in order to map the relation between galaxy color and redshift to a depth of
i
∼ ...24.5 (AB). The primary goal is to enable sufficiently accurate photometric redshifts for Stage
iv
dark energy projects, particularly Euclid and the Nancy Grace Roman Space Telescope (Roman), which are designed to constrain cosmological parameters through weak lensing. We present 676 new high-confidence spectroscopic redshifts obtained by the C3R2 survey in the 2017B–2019B semesters using the DEIMOS, LRIS, and MOSFIRE multiobject spectrographs on the Keck telescopes. Combined with the 4454 redshifts previously published by this project, the C3R2 survey has now obtained and published 5130 high-quality galaxy spectra and redshifts. If we restrict consideration to only the 0.2 <
z
p
< 2.6 range of interest for the Euclid cosmological goals, then with the current data release, C3R2 has increased the spectroscopic redshift coverage of the Euclid color space from 51% (as reported by Masters et al.) to the current 91%. Once completed and combined with extensive data collected by other spectroscopic surveys, C3R2 should provide the spectroscopic calibration set needed to enable photometric redshifts to meet the cosmology requirements for Euclid, and make significant headway toward solving the problem for Roman.
Context. The standard cosmological model is based on the fundamental assumptions of a spatially homogeneous and isotropic universe on large scales. An observational detection of a violation of these ...assumptions at any redshift would immediately indicate the presence of new physics.
Aims. We quantify the ability of the Euclid mission, together with contemporary surveys, to improve the current sensitivity of null tests of the canonical cosmological constant Λ and the cold dark matter (ΛCDM) model in the redshift range 0 < z < 1.8.
Methods. We considered both currently available data and simulated Euclid and external data products based on a ΛCDM fiducial model, an evolving dark energy model assuming the Chevallier-Polarski-Linder parameterization or an inhomogeneous Lemaître-Tolman-Bondi model with a cosmological constant Λ, and carried out two separate but complementary analyses: a machine learning reconstruction of the null tests based on genetic algorithms, and a theory-agnostic parametric approach based on Taylor expansion and binning of the data, in order to avoid assumptions about any particular model.
Results. We find that in combination with external probes, Euclid can improve current constraints on null tests of the ΛCDM by approximately a factor of three when using the machine learning approach and by a further factor of two in the case of the parametric approach. However, we also find that in certain cases, the parametric approach may be biased against or missing some features of models far from ΛCDM.
Conclusions. Our analysis highlights the importance of synergies between Euclid and other surveys. These synergies are crucial for providing tighter constraints over an extended redshift range for a plethora of different consistency tests of some of the main assumptions of the current cosmological paradigm.
Euclid preparation van Mierlo, S. E.; Caputi, K. I.; Atek, H. ...
Astronomy and astrophysics (Berlin),
10/2022, Letnik:
666
Journal Article
Recenzirano
Odprti dostop
Context.
The
Euclid
mission is expected to discover thousands of
z
> 6 galaxies in three deep fields, which together will cover a ∼50 deg
2
area. However, the limited number of
Euclid
bands (four) ...and the low availability of ancillary data could make the identification of
z
> 6 galaxies challenging.
Aims.
In this work we assess the degree of contamination by intermediate-redshift galaxies (
z
= 1–5.8) expected for
z
> 6 galaxies within the Euclid Deep Survey.
Methods.
This study is based on ∼176 000 real galaxies at
z
= 1–8 in a ∼0.7 deg
2
area selected from the UltraVISTA ultra-deep survey and ∼96 000 mock galaxies with 25.3 ≤
H
< 27.0, which altogether cover the range of magnitudes to be probed in the Euclid Deep Survey. We simulate
Euclid
and ancillary photometry from fiducial 28-band photometry and fit spectral energy distributions to various combinations of these simulated data.
Results.
We demonstrate that identifying
z
> 6 galaxies with
Euclid
data alone will be very effective, with a
z
> 6 recovery of 91% (88%) for bright (faint) galaxies. For the UltraVISTA-like bright sample, the percentage of
z
= 1–5.8 contaminants amongst apparent
z
> 6 galaxies as observed with
Euclid
alone is 18%, which is reduced to 4% (13%) by including ultra-deep
Rubin
(
Spitzer
) photometry. Conversely, for the faint mock sample, the contamination fraction with
Euclid
alone is considerably higher at 39%, and minimised to 7% when including ultra-deep
Rubin
data. For UltraVISTA-like bright galaxies, we find that
Euclid
(
I
E
−
Y
E
) > 2.8 and (
Y
E
−
J
E
) < 1.4 colour criteria can separate contaminants from true
z
> 6 galaxies, although these are applicable to only 54% of the contaminants as many have unconstrained (
I
E
−
Y
E
) colours. In the best scenario, these cuts reduce the contamination fraction to 1% whilst preserving 81% of the fiducial
z
> 6 sample. For the faint mock sample, colour cuts are infeasible; we find instead that a 5
σ
detection threshold requirement in at least one of the
Euclid
near-infrared bands reduces the contamination fraction to 25%.
Euclid preparation Pocino, A.; Tutusaus, I.; Fosalba, P. ...
Astronomy and astrophysics (Berlin),
11/2021, Letnik:
655
Journal Article
Recenzirano
Odprti dostop
Photometric redshifts (photo-
z
s) are one of the main ingredients in the analysis of cosmological probes. Their accuracy particularly affects the results of the analyses of galaxy clustering with ...photometrically selected galaxies (GC
ph
) and weak lensing. In the next decade, space missions such as
Euclid
will collect precise and accurate photometric measurements for millions of galaxies. These data should be complemented with upcoming ground-based observations to derive precise and accurate photo-
z
s. In this article we explore how the tomographic redshift binning and depth of ground-based observations will affect the cosmological constraints expected from the
Euclid
mission. We focus on GC
ph
and extend the study to include galaxy-galaxy lensing (GGL). We add a layer of complexity to the analysis by simulating several realistic photo-
z
distributions based on the
Euclid
Consortium Flagship simulation and using a machine learning photo-
z
algorithm. We then use the Fisher matrix formalism together with these galaxy samples to study the cosmological constraining power as a function of redshift binning, survey depth, and photo-
z
accuracy. We find that bins with an equal width in redshift provide a higher figure of merit (FoM) than equipopulated bins and that increasing the number of redshift bins from ten to 13 improves the FoM by 35% and 15% for GC
ph
and its combination with GGL, respectively. For GC
ph
, an increase in the survey depth provides a higher FoM. However, when we include faint galaxies beyond the limit of the spectroscopic training data, the resulting FoM decreases because of the spurious photo-
z
s. When combining GC
ph
and GGL, the number density of the sample, which is set by the survey depth, is the main factor driving the variations in the FoM. Adding galaxies at faint magnitudes and high redshift increases the FoM, even when they are beyond the spectroscopic limit, since the number density increase compensates for the photo-
z
degradation in this case. We conclude that there is more information that can be extracted beyond the nominal ten tomographic redshift bins of
Euclid
and that we should be cautious when adding faint galaxies into our sample since they can degrade the cosmological constraints.
Euclid preparation Castellano, M.; Huertas-Company, M.; Kuchner, U. ...
Astronomy and astrophysics (Berlin),
03/2023, Letnik:
671
Journal Article
Recenzirano
Odprti dostop
The European Space Agency's
Euclid
mission will provide high-quality imaging for about 1.5 billion galaxies. A software pipeline to automatically process and analyse such a huge amount of data in ...real time is being developed by the Science Ground Segment of the Euclid Consortium; this pipeline will include a model-fitting algorithm, which will provide photometric and morphological estimates of paramount importance for the core science goals of the mission and for legacy science. The
Euclid
Morphology Challenge is a comparative investigation of the performance of five model-fitting software packages on simulated
Euclid
data, aimed at providing the baseline to identify the best-suited algorithm to be implemented in the pipeline. In this paper we describe the simulated dataset, and we discuss the photometry results. A companion paper is focussed on the structural and morphological estimates. We created mock
Euclid
images simulating five fields of view of 0.48 deg
2
each in the
I
E
band of the VIS instrument, containing a total of about one and a half million galaxies (of which 350 000 have a nominal signal-to-noise ratio above 5), each with three realisations of galaxy profiles (single and double Sérsic, and 'realistic' profiles obtained with a neural network); for one of the fields in the double Sérsic realisation, we also simulated images for the three near-infrared
Y
E
,
J
E
, and
H
E
bands of the NISP-P instrument, and five Rubin/LSST optical complementary bands (
u
,
g, r, i,
and
z
), which together form a typical dataset for an
Euclid
observation. The images were simulated at the expected
Euclid
Wide Survey depths. To analyse the results, we created diagnostic plots and defined metrics to take into account the completeness of the provided catalogues, as well as the median biases, dispersions, and outlier fractions of their measured flux distributions. Five model-fitting software packages (
DeepLeGATo
,
Galapagos-2
,
Morfometryka
,
ProFit
, and
SourceXtractor++
) were compared, all typically providing good results. Of the differences among them, some were at least partly due to the distinct strategies adopted to perform the measurements. In the best-case scenario, the median bias of the measured fluxes in the analytical profile realisations is below 1% at a signal-to-noise ratio above 5 in
I
E
, and above 10 in all the other bands; the dispersion of the distribution is typically comparable to the theoretically expected one, with a small fraction of catastrophic outliers. However, we can expect that real observations will prove to be more demanding, since the results were found to be less accurate for the most realistic realisation. We conclude that existing model-fitting software can provide accurate photometric measurements on
Euclid
datasets. The results of the challenge are fully available and reproducible through an online plotting tool.
The
Euclid
space telescope will survey a large dataset of cosmic voids traced by dense samples of galaxies. In this work we estimate its expected performance when exploiting angular photometric void ...clustering, galaxy weak lensing, and their cross-correlation. To this aim, we implemented a Fisher matrix approach tailored for voids from the
Euclid
photometric dataset and we present the first forecasts on cosmological parameters that include the void-lensing correlation. We examined two different probe settings, pessimistic and optimistic, both for void clustering and galaxy lensing. We carried out forecast analyses in four model cosmologies, accounting for a varying total neutrino mass,
M
ν
, and a dynamical dark energy (DE) equation of state,
w
(
z
), described by the popular Chevallier-Polarski-Linder parametrization. We find that void clustering constraints on
h
and Ω
b
are competitive with galaxy lensing alone, while errors on
n
s
decrease thanks to the orthogonality of the two probes in the 2D-projected parameter space. We also note that, as a whole, with respect to assuming the two probes as independent, the inclusion of the void-lensing cross-correlation signal improves parameter constraints by 10 − 15%, and enhances the joint void clustering and galaxy lensing figure of merit (FoM) by 10% and 25%, in the pessimistic and optimistic scenarios, respectively. Finally, when further combining with the spectroscopic galaxy clustering, assumed as an independent probe, we find that, in the most competitive case, the FoM increases by a factor of 4 with respect to the combination of weak lensing and spectroscopic galaxy clustering taken as independent probes. The forecasts presented in this work show that photometric void clustering and its cross-correlation with galaxy lensing deserve to be exploited in the data analysis of the
Euclid
galaxy survey and promise to improve its constraining power, especially on
h
, Ω
b
, the neutrino mass, and the DE evolution.
Pair-instability supernovae are theorized supernovae that have not yet been observationally confirmed. They are predicted to exist in low-metallicity environments. Because overall metallicity becomes ...lower at higher redshifts, deep near-infrared transient surveys probing high-redshift supernovae are suitable to discover pair-instability supernovae. The
Euclid
satellite, which is planned launch in 2023, has a near-infrared wide-field instrument that is suitable for a high-redshift supernova survey. The Euclid Deep Survey is planned to make regular observations of three Euclid Deep Fields (40 deg
2
in total) spanning
Euclid
’s six-year primary mission period. While the observations of the Euclid Deep Fields are not frequent, we show that the predicted long duration of pair-instability supernovae would allow us to search for high-redshift pair-instability supernovae with the Euclid Deep Survey. Based on the current observational plan of the
Euclid
mission, we conduct survey simulations in order to estimate the expected numbers of pair-instability supernova discoveries. We find that up to several hundred pair-instability supernovae at
z
≲ 3.5 can be discovered within the Euclid Deep Survey. We also show that pair-instability supernova candidates can be efficiently identified by their duration and color, which can be determined with the current Euclid Deep Survey plan. We conclude that the
Euclid
mission can lead to the first confirmation of pair-instability supernovae if their event rates are as high as those predicted by recent theoretical studies. We also update the expected numbers of superluminous supernova discoveries in the Euclid Deep Survey based on the latest observational plan.
Primordial features, in particular oscillatory signals, imprinted in the primordial power spectrum of density perturbations represent a clear window of opportunity for detecting new physics at ...high-energy scales. Future spectroscopic and photometric measurements from the Euclid space mission will provide unique constraints on the primordial power spectrum, thanks to the redshift coverage and high-accuracy measurement of nonlinear scales, thus allowing us to investigate deviations from the standard power-law primordial power spectrum. We consider two models with primordial undamped oscillations superimposed on the matter power spectrum described by 1 + X sin ( ω X Ξ X + 2 πϕ X ), one linearly spaced in k space with Ξ lin ≡ k / k * where k * = 0.05 Mpc −1 and the other logarithmically spaced in k space with Ξ log ≡ ln( k / k * ). We note that X is the amplitude of the primordial feature, ω X is the dimensionless frequency, and ϕ X is the normalised phase, where X = {lin, log}. We provide forecasts from spectroscopic and photometric primary Euclid probes on the standard cosmological parameters Ω m, 0 , Ω b, 0 , h , n s , and σ 8 , and the primordial feature parameters X , ω X , and ϕ X . We focus on the uncertainties of the primordial feature amplitude X and on the capability of Euclid to detect primordial features at a given frequency. We also study a nonlinear density reconstruction method in order to retrieve the oscillatory signals in the primordial power spectrum, which are damped on small scales in the late-time Universe due to cosmic structure formation. Finally, we also include the expected measurements from Euclid ’s galaxy-clustering bispectrum and from observations of the cosmic microwave background (CMB). We forecast uncertainties in estimated values of the cosmological parameters with a Fisher matrix method applied to spectroscopic galaxy clustering (GC sp ), weak lensing (WL), photometric galaxy clustering (GC ph ), the cross correlation (XC) between GC ph and WL, the spectroscopic galaxy clustering bispectrum, the CMB temperature and E -mode polarisation, the temperature-polarisation cross correlation, and CMB weak lensing. We consider two sets of specifications for the Euclid probes (pessimistic and optimistic) and three different CMB experiment configurations, that is, Planck , Simons Observatory (SO), and CMB Stage-4 (CMB-S4). We find the following percentage relative errors in the feature amplitude with Euclid primary probes: for the linear (logarithmic) feature model, with a fiducial value of X = 0.01, ω X = 10, and ϕ X = 0: 21% (22%) in the pessimistic settings and 18% (18%) in the optimistic settings at a 68.3% confidence level (CL) using GC sp +WL+GC ph +XC. While the uncertainties on the feature amplitude are strongly dependent on the frequency value when single Euclid probes are considered, we find robust constraints on X from the combination of spectroscopic and photometric measurements over the frequency range of (1, 10 2.1 ). Due to the inclusion of numerical reconstruction, the GC sp bispectrum, SO-like CMB reduces the uncertainty on the primordial feature amplitude by 32%–48%, 50%–65%, and 15%–50%, respectively. Combining all the sources of information explored expected from Euclid in combination with the future SO-like CMB experiment, we forecast lin ≃ 0.010 ± 0.001 at a 68.3% CL and log ≃ 0.010 ± 0.001 for GC sp (PS rec + BS)+WL+GC ph +XC+SO-like for both the optimistic and pessimistic settings over the frequency range (1, 10 2.1 ).
Multi-object spectroscopic galaxy surveys typically make use of photometric and colour criteria to select their targets. That is not the case of which will use the NISP slitless spectrograph to ...record spectra for every source over its field of view. Slitless spectroscopy has the advantage of avoiding defining a priori a specific galaxy sample, but at the price of making the selection function harder to quantify. In its Wide Survey was designed to build robust statistical samples of emission-line galaxies with fluxes brighter than $ 2e-16 erg s cm $, using the Halpha -$ N ii right $ complex to measure redshifts within the range $ $. Given the expected signal-to-noise ratio of NISP spectra, at such faint fluxes a significant contamination by incorrectly measured redshifts is expected, either due to misidentification of other emission lines, or to noise fluctuations mistaken as such, with the consequence of reducing the purity of the final samples. This can be significantly ameliorated by exploiting the extensive photometric information to identify emission-line galaxies over the redshift range of interest. Beyond classical multi-band selections in colour space, machine learning techniques provide novel tools to perform this task. Here, we compare and quantify the performance of six such classification algorithms in achieving this goal. We consider the case when only the photometric and morphological measurements are used, and when these are supplemented by the extensive set of ancillary ground-based photometric data, which are part of the overall scientific strategy to perform lensing tomography. The classifiers are trained and tested on two mock galaxy samples, the EL-COSMOS and Euclid Flagship2 catalogues. The best performance is obtained from either a dense neural network or a support vector classifier, with comparable results in terms of the adopted metrics. When training on on-board photometry alone, these are able to remove $87<!PCT!>$ of the sources that are fainter than the nominal flux limit or lie outside the $0.9<z<1.8$ redshift range, a figure that increases to $97<!PCT!>$ when ground-based photometry is included. These results show how by using the photometric information available to it will be possible to efficiently identify and discard spurious interlopers, allowing us to build robust spectroscopic samples for cosmological investigations.
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