DES: Recent Cosmology Results DES Overview SE TRUTH == WF EDI Initiatives DES Papers Milky Way Satellites and Dark Matter Physics DES Cosmology Overview Y3 Weak Lensing and Large-Scale Structure Results COADD TRUTH == 10x WF Y6 Data for Cosmology, DR2 Updated Analysis Timeline Tom Diehl & Rich Kron @ PAC June 10, 2021 DEEPEST > 100x WF Dark Energy Survey Collaboration Started in 2003, DES is an International Collaboration ~700 people with diverse scientific interests. ● DECam: The 570 Megapixel camera for the Blanco 4m telescope in Chile. ● Survey Observations 2013-2019 (Y3 2013-16). ● Wide field: 5000 sq. deg. in 5 bands. ~23 magnitude. ● 27 sq. deg. 5-yr SNIa survey Dark Energy Survey Collaboration C.M. May 17-21, 2021 Focused on Y6 Plans (especially for Cosmology Key Projects) & EDI/EPO. The Collaboration was enthusiastic and well-prepared, and looking forward to meeting in-person (hopefully) next time. Equity, Diversity, and Inclusion Initiatives ● Currently engaged with the NOVA Collective (HOME - The Nova Collective), ○ We recently completed a climate survey. We’ll get the results soon. ● Mentorship Program ○ Volunteer Mentors. 25 Mentor/Mentee pairs. A dedicated Mentorship Coordinator. ● Adjustments to DES Collaboration written policies so that engagement with underrepresented people in STEM is encouraged ● Focus at Collaboration Meeting ○ Plenary Speaker from outside DES ○ EDI Parallel Sessions: Connecting with minority-serving institutions, Focusing EPO efforts on inclusion, Giving Credit in DES ○ EDI One-slides at the beginning of every Plenary session 91 DES PH.D’s DES Publications Update (so far) https://dbweb8.fnal.gov:8443/DESPub/app/PB/pub/pbpublished Through May 25, 2021, DES has 347 refereed science papers (not counting pre-data technical papers) with 14,700+ citations. Some of the recent papers (before May 25): Instrumental: “A Machine Learning Approach to the Detection of Ghosting and Scattered Light Artifacts in Dark Energy Survey Images”, “Reducing ground-based astrometric errors with Gaia and Gaussian processes” will both be useful to LSST Solar System: “Testing the isotropy of the Dark Energy Survey's extreme trans-Neptunian objects” SN1ae: “OzDES multifibre spectroscopy for the Dark Energy Survey: Results and implications for future surveys”, “The Effect of Environment on Type Ia Supernovae in the Dark Energy Survey Three-Year Cosmological Sample”, “The Dark Energy Survey Supernova Program: Modelling selection efficiency and observed core collapse supernova contamination”, “Rates and delay times of type Ia supernovae in the Dark Energy Survey” Galaxy Clusters: “Is diffuse intracluster light a good tracer of the galaxy cluster matter distribution?”, “ * Masses: Weak Lensing Calibration of the Dark Energy Survey Year 1 redMaPPer Clusters using Stellar Masses”, “The WaZP galaxy cluster sample of the Dark Energy Survey Year 1” Weak Lensing: “Galaxy Clustering in Harmonic Space from the Dark Energy Survey Year 1 Data: Compatibility with Real Space Results” Galaxy Clusters + WL: “Combination of cluster number counts and two-point correlations: Validation on Mock Dark Energy Survey”, “Dark Energy Survey Year 1 Results: Cosmological Constraints from Cluster Abundances, Weak Lensing, and Galaxy Correlations” Galaxy Clusters + External Data: “Cosmological Constraints from DES Y1 Cluster Abundances and SPT Multi-wavelength data”, “Probing galaxy evolution in massive clusters using ACT and DES: splashback as a cosmic clock”, “The Atacama Cosmology Telescope: A Catalog of > 4000 Sunyaev- Zel'dovich Galaxy Clusters” Modified Gravity: “Probing gravity with the DES-CMASS sample and BOSS spectroscopy”, “Galaxy-galaxy lensing with the DES-CMASS catalogue: measurement and constraints on the galaxy-matter cross-correlation” Optical + GW: “Constraints on the Physical Properties of S190814bv through Simulations based on DECam Follow-up Observations by DES” Dark Matter: “Milky Way Satellite Census. III. Constraints on Dark Matter Properties from Observations of Milky Way Satellite Galaxies”, “Constraints on Decaying Dark Matter with DES-Y1 and external data” . Galaxy Evolution: “Galaxy Morphological Classification Catalogue of the Dark Energy Survey Year 3 data with Convolutional Neural Networks” 6 Current Standard Cosmological model: ΛCDM Flat Universe with Dark Energy in the form of a cosmological constant Λ + Cold Dark Matter. It assumes General Relativity. ΛCDM became the standard model following observations from Type Ia Supernovae and the Cosmic Microwave Background. 7 Missing Satellites Problem & Known MW satellites vs year Dark Matter Physics DECam A long-time controversy: DM halo models Distribution of MW satellite masses predict hundreds of captured “satellite” enables model-dependent constraints galaxies for the Milky Way. DES data and on Dark Matter properties. i.e. DM must selection function vs. magnitude (mass be massive. proxy) shows that there are! Mass v. Mixing angle Absolute Magnitude Drlica-Wagner et al. ApJ 893, 1 (2020) Nadler et al. PRL 126, 091101 (2021) Testing ΛCDM: Is the late time clustering compatible with the ΛCDM prediction assuming initial conditions from the CMB? Spheres with radius 8 Mpc/h As: Amplitude of primordial σ8: Amplitude of mass scalar density fluctuations. fluctuations today, at 9 distance 8 Mpc/h Y3 Spectr. SNIa + Y1 DES: Cosmology Y1 3x2pt WL 7 Ways DES, PRL 122, 171301 (2019) Growth rate of structure and Expansion History: Weak Gravitational Lensing, Galaxy Clustering, & Galaxy Cluster Abundance Expansion History: BAO (standard rulers), DES, PRD 102, 023509 (2020) SNIa (standard candles), Gravitational Wave Follow up (standard sirens), Strongly-Lensed Palmese et al. ApJL 900, L33 (2020) Time varying SL quasar Transients. H0 = 74.2+2.7-3.0 Standard km/s/Mpc Y1 Combo Sirens To et al. arxiv:20100.01138 10 Shahib et al., MNRAS 494, 6072 (2020) New Results from DES: “Y3 3x2pt WL” Weak Gravitational Lensing: Sources and Lenses Galaxies trace the Light from distant galaxies underlying dark matter passes the foreground structure : they are structures and acquires observed to be spatially coherent distortions : they clustered. We construct a are observe to be lensed. power spectrum, or real- We correlate the lensing space correlation function of sources by the of the positions of foreground objects in (foreground) lens galaxies redshift / redshift bins (position- in redshift bins (position- distance shear). position). Image plane We also measure the correlation of the shapes Cosmic Shear : shape-shape (shear-shear) of source galaxy pairs as a Galaxy Clustering : position-position 3x2pt function of angular radius 2x2pt and redshift (shear-shear). Galaxy-Galaxy Lensing : position-shear 11 Y3 “3x2pt” Methodology: Pixels to Cosmology Webinar from May 27, 2021 https://www.youtube.com/watch?v=8aHbLMUOwLc LCDM —— WL+LSS —— Redshifts —— Shapes —— Clustering — Simulations —— Theory —— Results 12 Y3 WL 3x2-pt “29” Papers in https://www.darkenergysurvey.org/des-year-3-cosmology-results-papers/ 1. “Blinding Multi-probe Cosmological Experiments” J. Muir, G. M. Bernstein, D. Huterer et al., arXiv: 1911.05929, MNRAS 494 (2020) 4454 2. “Photometric Data Set for Cosmology”, I. Sevilla-Noarbe, K. Bechtol, M. Carrasco Kind et al., arXiv:2011.03407, ApJS 254 (2021) 24 3. “Weak Lensing Shape Catalogue”, M. Gatti, E. Sheldon, A. Amon et al., arXiv:2011.03408, MNRAS 504 (2021) 4312 4. “Point Spread Function Modelling”, M. Jarvis, G. M. Bernstein, A. Amon et al., arXiv:2011.03409, MNRAS 501 (2021) 1282 5. “Measuring the Survey Transfer Function with Balrog”, S. Everett, B. Yanny, N. Kuropatkin et al., arXiv:2012.12825 6. “Deep Field Optical + Near-Infrared Images and Catalogue”, W. Hartley, A. Choi, A. Amon et al., arXiv:2012.12824 7. “Blending Shear and Redshift Biases in Image Simulations”, N. MacCrann, M. R. Becker, J. McCullough et al., arXiv:2012.08567 8. “Redshift Calibration of the Weak Lensing Source Galaxies”, J. Myles, A. Alarcon, A. Amon et al., arXiv:2012.08566 9. “Redshift Calibration of the MagLim Lens Sample using Self-Organizing Maps and Clustering Redshifts”, G. Giannini et al., in prep. 10. “Clustering Redshifts – Calibration of the Weak Lensing Source Redshift Distributions with redMaGiC and BOSS/eBOSS”, M. Gatti, G. Giannini, et al., arXiv:2012.08569 11. “Calibration of Lens Sample Redshift Distributions using Clustering Redshifts with BOSS/eBOSS”, R. Cawthon et al. arXiv:2012.12826 12. “Phenotypic Redshifts with SOMs: a Novel Method to Characterize Redshift Distributions of Source Galaxies for Weak Lensing Analysis” R. Buchs, C.Davis, D. Gruen et al. MNRAS 489 (2019) 820 13. “Marginalising over Redshift Distribution Uncertainty in Weak Lensing Experiments”, J. Cordero, I. Harrison et al., in prep. 14. “Exploiting Small-Scale Information using Lensing Ratios”, C. Sánchez, J. Prat et al., in prep. 15. “Cosmology from Combined Galaxy Clustering and Lensing - Validation on Cosmological Simulations”, J. de Rose et al., in prep. 16. “Unbiased fast sampling of cosmological posterior distributions”, P. Lemos, R. Rollins, N. Weaverdyck, A. Ferte, A. Liddle et al., in prep. 17. “Assessing Tension Metrics with DES and Planck Data”, P. Lemos, M. Raveri, A. Campos et al., arXiv:2012.09554 18. “Dark Energy Survey Internal Consistency Tests of the Joint Cosmological Probe Analysis with Posterior Predictive Distributions”, C. Doux, E. Baxter, P. Lemos et al. MNRAS 503 (2021) 2688 19. “Covariance Modelling and its Impact on Parameter Estimation and Quality of Fit”, O. Friedrich, F. Andrade-Oliveira,