3 research outputs found
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Dark Energy Survey Year 3 results: cosmological constraints from galaxy clustering and galaxy-galaxy lensing using the MagLim lens sample
The cosmological information extracted from photometric surveys is most robust when multiple probes of the large scale structure of the Universe are used. Two of the most sensitive probes 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 way galaxies trace matter (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 deg2 of the Dark Energy Survey's 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 flat cosmological models, the Standard Model with dark energy and cold dark matter (ΛCDM) a variation with a free parameter for the dark energy equation of state (wCDM). Both models are marginalized over 25 astrophysical and systematic nuisance parameters. In ΛCDM we obtain for the matter density ωm=0.320-0.034+0.041 and for the clustering amplitude S8σ8(ωm/0.3)0.5=0.778-0.031+0.037, at 68% C.L. The latter is only 1σ smaller than the prediction in this model informed by measurements of the cosmic microwave background by the Planck satellite. In wCDM we find ωm=0.32-0.046+0.044, S8=0.777-0.051+0.049 and dark energy equation of state w=-1.031-0.379+0.218. We find that including smaller scales, while marginalizing over nonlinear galaxy bias, improves the constraining power in the ωm-S8 plane by 31% and in the ωm-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 (3×2pt)
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The Dark Energy Survey: Cosmology Results with ∼1500 New High-redshift Type Ia Supernovae Using the Full 5 yr Data Set
We present cosmological constraints from the sample of Type Ia supernovae (SNe Ia) discovered and measured during the full 5 yr of the Dark Energy Survey (DES) SN program. In contrast to most previous cosmological samples, in which SNe are classified based on their spectra, we classify the DES SNe using a machine learning algorithm applied to their light curves in four photometric bands. Spectroscopic redshifts are acquired from a dedicated follow-up survey of the host galaxies. After accounting for the likelihood of each SN being an SN Ia, we find 1635 DES SNe in the redshift range 0.10 0.5 SNe compared to the previous leading compilation of Pantheon+ and results in the tightest cosmological constraints achieved by any SN data set to date. To derive cosmological constraints, we combine the DES SN data with a high-quality external low-redshift sample consisting of 194 SNe Ia spanning 0.025 < z < 0.10. Using SN data alone and including systematic uncertainties, we find ΩM = 0.352 ± 0.017 in flat ΛCDM. SN data alone now require acceleration (q
0 < 0 in ΛCDM) with over 5σ confidence. We find
(
Ω
M
,
w
)
=
(
0.264
−
0.096
+
0.074
,
−
0.80
−
0.16
+
0.14
)
in flat wCDM. For flat w
0
w
a
CDM, we find
(
Ω
M
,
w
0
,
w
a
)
=
(
0.495
−
0.043
+
0.033
,
−
0.36
−
0.30
+
0.36
,
−
8.8
−
4.5
+
3.7
)
, consistent with a constant equation of state to within ∼2σ. Including Planck cosmic microwave background, Sloan Digital Sky Survey baryon acoustic oscillation, and DES 3 × 2pt data gives (ΩM, w) = (0.321 ± 0.007, −0.941 ± 0.026). In all cases, dark energy is consistent with a cosmological constant to within ∼2σ. Systematic errors on cosmological parameters are subdominant compared to statistical errors; these results thus pave the way for future photometrically classified SN analyses.</p
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The Dark Energy Survey Supernova Program: cosmological analysis and systematic uncertainties
We present the full Hubble diagram of photometrically classified Type Ia supernovae (SNe Ia) from the Dark Energy Survey supernova program (DES-SN). DES-SN discovered more than 20,000 SN candidates and obtained spectroscopic redshifts of 7000 host galaxies. Based on the light-curve quality, we select 1635 photometrically identified SNe Ia with spectroscopic redshift 0.10 0.5 supernovae by a factor of 5. In a companion paper, we present cosmological results of the DES-SN sample combined with 194 spectroscopically classified SNe Ia at low redshift as an anchor for cosmological fits. Here we present extensive modeling of this combined sample and validate the entire analysis pipeline used to derive distances. We show that the statistical and systematic uncertainties on cosmological parameters are
σ
Ω
M
,
stat
+
sys
Λ
CDM
=
0.017 in a flat ΛCDM model, and
(
σ
Ω
M
,
σ
w
)
stat
+
sys
w
CDM
= (0.082, 0.152) in a flat wCDM model. Combining the DES SN data with the highly complementary cosmic microwave background measurements by Planck Collaboration reduces by a factor of 4 uncertainties on cosmological parameters. In all cases, statistical uncertainties dominate over systematics. We show that uncertainties due to photometric classification make up less than 10% of the total systematic uncertainty budget. This result sets the stage for the next generation of SN cosmology surveys such as the Vera C. Rubin Observatory's Legacy Survey of Space and Time.</p