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Mcwilliams Center for Cosmology McWilliams Center for Cosmology McWilliams Center for Cosmology McWilliams Center for Cosmology McWilliams Center for Cosmology ,CODQTGG Rachel Mandelbaum (+Optimus Prime) Observational cosmology: • how can we make the best use of large datasets? (+stats, ML connection) • dark energy • the galaxy-dark matter connection I measure this: for tens of millions of galaxies to (statistically) map dark matter and answer these questions Data I use now: Future surveys I’m involved in: Hung-Jin Huang 0.2 0.090 0.118 0.062 0.047 0.118 0.088 0.044 0.036 0.186 0.016 70 0.011 0.011 − 0.011 − 0.011 − 0.011 − 0.011 − 0.011 0.011 − 0.011 0.011 ± ± ± ± ± ± ± ± ± ± 50 η 0.1 30 ∆ Fraction 10 1 24 23 22 21 0.40.81.2 0.20.61.0 0.6 0.2 0.20.6 0.30.50.70.9 1.41.61.82.02.2 0.15 0.25 0.10.30.5 0.4 0.00.4 − − 0−.1 − − − − . 0.090 ∆log(cen. R )[kpc/h] P ∆ 0.011 0.3 cen. Mr cen. color cen. e eff cen log(richness) z cluster e R ± dom 1 0.2 . − cen 0.1 3 Fraction − 21 Research: − 0.118 0.622 0.3 0.011 0.009 Mr 22 1 . ± ± 0.2 0 − . 23 − 0.1 Fraction cen intrinsic alignments in 24 − 0.8 0.062 0.062 0.084 0.7 1.2 0.011 0.011 0.011 0.6 redMaPPer clusters − ± − ± − ± 0.5 color . 0.4 0.8 0.3 Fraction cen 0.2 0.4 0.1 1.0 0.047 0.048 0.052 0.111 0.3 Advisor : 0.011 0.011 0.011 0.011 e − ± − ± − ± − ± . 0.2 0.6 cen 0.1 Fraction Rachel Mandelbaum 0.2 h] / 0.6 0.6 0.118 0.046 0.000 0.045 0.086 0.5 )[kpc − 0.011 − 0.011 − 0.011 − 0.011 0.011 ff 0.4 e 0.2 ± ± ± ± ± R 0.3 . 0.2 0.2 Fraction − 0.6 0.1 φsat − log(cen 0.6 ∆ 0.9 0.088 0.481 0.393 0.107 0.034 0.089 0.5 0.011 0.010 0.010 0.011 0.011 0.011 0.7 − ± − ± − ± ± − ± ± 0.4 cen 0.3 P 0.5 0.2 Fraction 0.1 0.3 0.5 2.2 0.044 0.164 0.288 0.099 0.003 0.087 0.025 0.4 2.0 0.011 0.011 0.011 0.011 0.011 0.011 0.011 − ± ± − ± ± ± ± ± 0.3 1.8 θcen 0.2 1.6 Fraction 0.1 log(richness) 1.4 0.036 0.175 0.152 0.153 0.074 0.214 0.005 0.022 0.3 0.011 − 0.011 − 0.011 − 0.011 0.011 − 0.011 − 0.011 − 0.011 0.25 ± ± ± ± ± ± ± ± 0.2 z 0.1 Fraction central 0.15 0.186 0.002 0.046 0.028 0.001 0.031 0.056 0.127 0.145 0.3 0.5 − 0.011 0.011 0.011 0.011 0.011 0.011 − 0.011 − 0.011 − 0.011 ± ± ± ± ± ± ± ± ± 0.2 0.3 Fraction cluster e 0.1 0.1 φsat 0.4 0.016 0.057 0.039 0.013 0.074 0.018 0.051 0.010 0.009 0.017 0.3 0.011 0.011 0.011 0.011 0.011 0.011 0.011 0.011 0.011 0.011 ± − ± ± − ± ± − ± − ± ± ± − ± R 0.2 ∆ 0.0 0.1 Fraction 0.4 − 10 30 50 70 3 1 1 24 23 22 21 0.40.81.2 0.20.61.0 0.6 0.2 0.20.6 0.30.50.70.9 1.41.61.82.02.2 0.15 0.25 0.10.30.5 0.4 0.00.4 − − − − 0−.1 − − − − ∆η cen. dom. cen. Mr cen. color cen. e ∆log(cen. Reff)[kpc/h] Pcen log(richness) z cluster e ∆R Sukhdeep Singh Graduate Student with Prof. Rachel Mandelbaum Research 0.8 20 LOWZ-CMB lensing Wm = 0.20 LOWZ-z1 15 W = 0.25 LOWZ-galaxy lensing 0.7 m LOWZ-z2 gm 10 Wm = 0.30 CMASS ° 1. Weak Lensing p r LOWZ Pullen+,15 5 0.6 0 i 5 G 0.5 Closed markers: Galaxy lensing Science E − h 100 LOWZ-CMB lensing Open markers: CMB lensing LOWZ-galaxy lensing 0.4 - Gravitational Physics error gm 1 10− 0.3 - Nature of Dark Matter, Dark Energy ° 0.2 100 101 102 0.20 0.25 0.30 0.35 0.40 0.45 0.50 0.55 0.60 rp [Mpc/h] z IA 2. Intrinsic Alignments measurement - Galaxy Formation and Evolution - Weak Lensing Systematics ́μ˧ͽ̏΍͕υ Ͱ˧ͽϝυυ̤ ࠇ °ųɯƚɟʲŏɾǞȩȘŏȀ żȩɯȒȩȀȩǃʿ ࠇ ĦƚŏǺ ƚȘɯǞȘǃ ࠇ ɯɾɟȩɯɾŏɾǞɯɾǞżɯ ࠇ ëɔŏɟɯǞɾʿ ࠘ ŏżǕǞȘƚ ƚŏɟȘǞȘǃ ÚȩɯɾƇȩż ʶǞɾǕ áŏżǕƚȀ ŏȘƇƚȀųŏʕȒ Danielle Leonard McWilliams Postdoctoral Fellow • Weak lensing + other LSS probes of non-standard cosmology, especially alternative theories of gravity • Degeneracies involving beyond-LCDM parameters • Understanding theoretical uncertainties, as related to next-generation surveys Matthew G. Walker Mao-Sheng Liu (Terrence) Advisor: Matthew Walker Study the distribution of dark matter at small scale through sampling-based inference, including: ρ g o • Likelihood Approximation L • Approximate Bayesian Computation • Machine Learning Log r Evan Tucker - 4th Year Grad Student Working with Matt Walker, we developed a new model for fitting galaxy spectra extracting population properties: age, [Fe/H], vlos, and mass. We are now developing a new mixture model to understands dynamics of galaxy clusters. Alex Ge!n"r-SamePostdoctoral# researcher Astroparticle physics astrophysical observation = dark matter + backgrounds particle physics ⇥ distribution gamma-rays dwarf galaxies 5 10− statistical tools ] annihilation 1 1 − 10 6 sr stellar dark matter 1 13390 18 11 − 1 Fermi Reticulums II 51 33 22 2 135.4 detecting unresolved sources − kinematics distribution 96.3 59.2 6 33.5 WIMPs 10− 19.9 11.5 6.5 3.9 2.3 [GeV cm 1.3 0.6 0.3 0.2 0.1 0.1 velocity dispersion profile pulsars, dF/dE correlations 2 E 7 10− 0 1 2 moving objects 10 10 10 Energy [GeV] search for new particles beyond the t VERITAS Standard Model + 24 ⌧ ⌧ − 10− 1.0 3 25 ] 10 ⌦ 1 Annihilation known populations of gamma- − 24 Draco y s β 0.8 3 ray emitters vs dark matter 25 , dJ/d 10− 23 ⌦ unassoc (178) bin (1) [cm ? 0.6 2 /d fsrq (100) hmb (3) i 10 22 v Decay bll (36) nov (1) σ h 21 decay 26 0.4 bcu (22) snr (13) − dJ inferred dark matter i 20 agn (2) spp (15) v 26 nlsy1 (2) psr (11) Curvature parameter σ x 0.5 10−1 distribution 0.2 h 10 3 19 statistical framework to 10 0.9 rdg (2) pwn (2) 19 ,J 18 gal (1) glc (6) J 0.8 0.0 1 0 1 2 3 4 5 extract particle physics 1 2 3 10 10 10 decay 17 − J Spectral index ↵ at 1 GeV 3σ 100 0.7 1.0 from astro data Mass [GeV] 16 0.4 ¯ b¯b hh 0.6 bb 15 2σ + 2 1 2 GeV 0 + 100.8− 10 GeV 10− 10 ⌧ ⌧ − µ µ− 0.5 2 1 10 ✓ [deg] 104 1σ 10− 1 GeV 1 2 3 0.4 10 10 10 0.6 spacetime correlation function 0.3 1000 0σ Mass [GeV] 0.3 Search power to search for moving sources 0.5 GeV 0.2 0.4 Angular separation [deg] 100 0.2 1σ Mass used for search [GeV] − 0.1 containment fraction Detection significance 0.1 J 0.2 10 2σ search for an 101 0.0 0 Counts 0 1 − 2 1 2 3 10 10 10 annihilation signal 10 10 10 Draco 3σ True mass [GeV] 0.0 1 Event energy [GeV] − 1 2 3 10 10 10 0.0 0.2 0.4 0.6 0.8 1.0 tail due to unresolved pulsars Mass [GeV] ✓ [deg] 0.1 0.01 20 25 30 35 40 Score Tina Kahniashvili The McWilliams Center For Cosmology – Cosmology – Astrophysics • Very Early Universe • Cosmic Magne9c Fields – Fundamental • MHD Turbulence Symmetries Tests – Gravita9onal Waves – Cosmic Microwave Background • Accelerated Expansion – Modified Gravity – Dark Energy • Astro-Par9cle Physics – Neutrino Mass Origin Hy Trac CMB Asst Prof 8307 Wean Hall First Stars & Galaxies [email protected] Galaxy Clusters Group Minghan Chen, Paul La Plante, Michelle Ntampaka, Jeff Patrick, Layne Price Interests Structure formation & evolution, large-scale structure, dark matter halos, Meshing Meshfree galaxies, clusters, cosmic reionization Tools Cosmological simulations, N-body, hydro, radiative transfer Ether (finite-volume particle method) Hyper (fast hydro-particle-mesh) Michelle'Ntampaka' Research:' Outreach:' • Graduate'student'working'in' • Early'Childhood'Astronomy' Hy'Trac’s'group' • Research:''Galaxy'Cluster' Dynamics'with'ML'and'Stats' Paul La Plante • Graduate student, soon-to-be postdoc • Works with Prof. Hy Trac • Simulations of helium reionization • Quasar properties, IGM thermal history, Lyman-alpha forest • Efficient, scalable algorithms Helium reionization in action for cosmological simulations z =2.9820 and analysis 1.0 HI 0.8 HeII 0.6 Flux 0.4 0.2 0.0 Peta-scale 0 5000 10000 15000 20000 computation Lyman-alpha forest used to v [km/s] measure large-scale structure Diane Turnshek, Special Faculty, Physics, CMU • Teaches Astronomy and manages classroom demos • Teacher Advisory Panelist at Carnegie Science Center • IDA Dark Sky Defender • Chair of IAU Technical Working Group against light pollution Layne Price Cosmo/Stats/ML Early universe Machine Bayesian theory learning modelling Jeff$Peterson:$Radio$Astronomy$With$ 20007receiver$Telescopes$ • Building$three$radically$new$telescopes$in$Canada$(CHIME),$ South$Africa$(HIRAX)$and$China$(Tianlai).$$ • Primary$Goals:$$ – Map$LSS$via$217cm$intensity$field—BAO$dark$energy$test$ – Find$and$localize$10$Fast$Radio$Burst$per$day$ Thanks! Zhonghao Luo (Roy) ● Advisor: Jeff Peterson ● 4th year graduate student ● Lyman Alpha Intensity Mapping using a small aperture telescope with grism spectrotomography Hsiu-Hsien Lin • 4th year physics graduate student Advisor: Jeffrey Peterson • Search Fast Radio Bursts (FRBs) and Pulsars by using Green Bank Telescope and incoming telescopes.
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