scholarly journals Dark Energy Survey year 1 results: Joint analysis of galaxy clustering, galaxy lensing, and CMB lensing two-point functions

2019 ◽  
Vol 100 (2) ◽  
Author(s):  
T. M. C. Abbott ◽  
F. B. Abdalla ◽  
A. Alarcon ◽  
S. Allam ◽  
J. Annis ◽  
...  
2016 ◽  
Vol 94 (6) ◽  
Author(s):  
Y. Park ◽  
E. Krause ◽  
S. Dodelson ◽  
B. Jain ◽  
A. Amara ◽  
...  

2019 ◽  
Vol 489 (4) ◽  
pp. 5453-5482 ◽  
Author(s):  
S Samuroff ◽  
J Blazek ◽  
M A Troxel ◽  
N MacCrann ◽  
E Krause ◽  
...  

Abstract We perform a joint analysis of intrinsic alignments and cosmology using tomographic weak lensing, galaxy clustering, and galaxy–galaxy lensing measurements from Year 1 (Y1) of the Dark Energy Survey. We define early- and late-type subsamples, which are found to pass a series of systematics tests, including for spurious photometric redshift error and point spread function correlations. We analyse these split data alongside the fiducial mixed Y1 sample using a range of intrinsic alignment models. In a fiducial non-linear alignment model analysis, assuming a flat Λ cold dark matter cosmology, we find a significant difference in intrinsic alignment amplitude, with early-type galaxies favouring $A_\mathrm{IA} = 2.38^{+0.32}_{-0.31}$ and late-type galaxies consistent with no intrinsic alignments at $0.05^{+0.10}_{-0.09}$. The analysis is repeated using a number of extended model spaces, including a physically motivated model that includes both tidal torquing and tidal alignment mechanisms. In multiprobe likelihood chains in which cosmology, intrinsic alignments in both galaxy samples and all other relevant systematics are varied simultaneously, we find the tidal alignment and tidal torquing parts of the intrinsic alignment signal have amplitudes $A_1 = 2.66 ^{+0.67}_{-0.66}$, $A_2=-2.94^{+1.94}_{-1.83}$, respectively, for early-type galaxies and $A_1 = 0.62 ^{+0.41}_{-0.41}$, $A_2 = -2.26^{+1.30}_{-1.16}$ for late-type galaxies. In the full (mixed) Y1 sample the best constraints are $A_1 = 0.70 ^{+0.41}_{-0.38}$, $A_2 = -1.36 ^{+1.08}_{-1.41}$. For all galaxy splits and IA models considered, we report cosmological parameter constraints consistent with the results of the main DES Y1 cosmic shear and multiprobe cosmology papers.


2022 ◽  
Vol 105 (2) ◽  
Author(s):  
T. M. C. Abbott ◽  
M. Aguena ◽  
A. Alarcon ◽  
S. Allam ◽  
O. Alves ◽  
...  

2016 ◽  
Vol 464 (4) ◽  
pp. 4045-4062 ◽  
Author(s):  
J. Kwan ◽  
C. Sánchez ◽  
J. Clampitt ◽  
J. Blazek ◽  
M. Crocce ◽  
...  

2018 ◽  
Vol 98 (4) ◽  
Author(s):  
J. Elvin-Poole ◽  
M. Crocce ◽  
A. J. Ross ◽  
T. Giannantonio ◽  
E. Rozo ◽  
...  

Author(s):  
Erika L Wagoner ◽  
Eduardo Rozo ◽  
Xiao Fang ◽  
Martín Crocce ◽  
Jack Elvin-Poole ◽  
...  

Abstract We implement a linear model for mitigating the effect of observing conditions and other sources of contamination in galaxy clustering analyses. Our treatment improves upon the fiducial systematics treatment of the Dark Energy Survey (DES) Year 1 (Y1) cosmology analysis in four crucial ways. Specifically, our treatment 1) does not require decisions as to which observable systematics are significant and which are not, allowing for the possibility of multiple maps adding coherently to give rise to significant bias even if no single map leads to a significant bias by itself; 2) characterizes both the statistical and systematic uncertainty in our mitigation procedure, allowing us to propagate said uncertainties into the reported cosmological constraints; 3) explicitly exploits the full spatial structure of the galaxy density field to differentiate between cosmology-sourced and systematics-sourced fluctuations within the galaxy density field; 4) is fully automated, and can therefore be trivially applied to any data set The updated correlation function for the DES Y1 redMaGiC catalog minimally impacts the cosmological posteriors from that analysis. Encouragingly, our analysis does improve the goodness of fit statistic of the DES Y1 3×2pt data set (Δχ2 = −6.5 with no additional parameters). This improvement is due in nearly equal parts to both the change in the correlation function and the added statistical and systematic uncertainties associated with our method. We expect the difference in mitigation techniques to become more important in future work as the size of cosmological data sets grows.


2019 ◽  
Vol 99 (12) ◽  
Author(s):  
T. M. C. Abbott ◽  
F. B. Abdalla ◽  
S. Avila ◽  
M. Banerji ◽  
E. Baxter ◽  
...  

2018 ◽  
Vol 98 (4) ◽  
Author(s):  
T. M. C. Abbott ◽  
F. B. Abdalla ◽  
A. Alarcon ◽  
J. Aleksić ◽  
S. Allam ◽  
...  

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