Synergistic cosmology across the spectrum

Synergistic cosmology across the spectrum Stefano Camera Dipartimento di Fisica, Università degli Studi di Torino, Italy

Fundamental Cosmology Lion Panther She-wolf

Fundamental Cosmology Dark matter Dark energy Inflation

Synergies

UNIVERSITÀ Stefano Camera Synergies Synergistic cosmology across the spectrum 24 v 2017

Outline Synergies: Why and how? Synergies vs Noise: Synergies vs Cosmic Variance:

Correlations Cosmological perturbation [temperature anisotropies, density fluctuations ] f(t,x) Correlation function Power spectrum ξ f (t, x y )=hf(t,x)f(t,y)i hˆf k (t)ˆf? k 0 (t)i = δ D (k k 0 )P f (k,t) Example #1: Cosmic microwave background temperature anisotropies f(t,x) T(t rec, ~ ) T CMB

Correlations `(`+1)C T` /(2 )[(TCMB/µK) 2 ] θ[deg] [Planck Collaboration, 2015] `

Correlations Cosmological perturbation [temperature anisotropies, density fluctuations ] f(t,x) Correlation function Power spectrum ξ f (t, x y )=hf(t,x)f(t,y)i hˆf k (t)ˆf? k 0 (t)i = δ D (k k 0 )P f (k,t) Example #2: Matter power spectrum f(t,x) δ g (t,x)=b g (t)δ(t,x)

Correlations [SDSS-III BOSS Collaboration, 2012] ξ g (s = x y ) s[mpc/h]

Correlations [Klypin et al., 2016]

Cross-Correlations Cosmological perturbation Correlation function f(t,x) ξ fg (t, x y )=hf(t,x)g(t,y)i Power spectrum hˆf k (t)ĝ? k 0 (t)i = δ D (k k 0 )P fg (k,t)

Cross-Correlations Cosmological perturbation Correlation function f(t,x) ξ fg (t, x y )=hf(t,x)g(t,y)i Power spectrum hˆf k (t)ĝ? k 0 (t)i = δ D (k k 0 )P fg (k,t) WHY!?

Cross-Correlations Cosmological perturbation Correlation function f(t,x) ξ fg (t, x y )=hf(t,x)g(t,y)i Power spectrum hˆf k (t)ĝ? k 0 (t)i = δ D (k k 0 )P fg (k,t) Measurement [noise, systematic effects, cosmic variance ] C f,obs ` = s 2 f` C +Cf,sys (2`+1)f ` sky +N f`

Outline Synergies: Why and how? Synergies vs Noise: Indirect search of particle dark matter signatures Synergies vs Cosmic Variance: Multi-tracing galaxy number counts

Particle Dark Matter Particle dark matter established ingredient of concordance cosmology Weakly interacting massive particles (WIMPs) Indirect detection experimentrs: WIMP-sourced cosmic & gamma rays Decay Annihilation

DM-Sourced Gamma Rays

DM-Sourced Gamma Rays Hunting down signals of annihilations/decays of dark matter particles Gamma-ray energy spectrum [Fornasa & Sánchez-Conde, 2015] 10 10 10 10-2 10 DGRB energy spectrum (Ackermann et al. 2014) Foreground system. error (Ackermann et al. (2014) Blazars (Ajello et al. (2015) 10 s -1 sr -1 ] -2-3 10 Misaligned AGNs (Di Mauro et al. 2014) Star-forming galaxies (Tamborra et al. 2014) Dark matter Millisecond pulsars (Calore et al. 2014) 10 dφ/dedω [MeV cm -4 10-5 10 10 10 2 E -6 10 10-7 10 3 10 4 10 Energy [MeV] m DM 5 10 10 6 10

DM-Sourced Gamma Rays Hunting down signals of annihilations/decays of dark matter particles Gamma-ray anisotropies angular spectrum 10 1 10 0 [SC, Fornasa, Fornengo & Regis, ApJL 2013] Auto-correlation γ-rays E > 1 GeV l (l+1) C l /(2π) 10-1 10-2 10-3 10-4 10-5 blazars annihilating DM Fermi-LAT star-forming galaxies decaying DM 10 100 1000 10000 Multipole l

Direct Gravitational Probes [Lukic et al.; Image: Casey Stark] Potential wells of the cosmic large-scale structure Gamma rays from astrophysical sources hosted within the dark matter halo Gamma rays from annihilations/decays of dark matter particles forming the halo

Direct Gravitational Probes Find an optimal tracer of the cosmic dark matter distribution on large scale to filter out astrophysical non-thermal emission from the dark matter gamma-ray signal Main tracers of the cosmic large-scale structure: Weak gravitational lensing (cosmic shear, CMB lensing ) Clustering of structures (galaxies, galaxy clusters ) [SC, Fornasa, Fornengo & Regis, ApJL 2013; Fornengo, Perrotto, Regis & SC, ApJL 2015; Shirasaki et al. 2013; 2015] [Fornengo & Regis, 2014; Ando et al., 2014; Xia et al., ApJS 2015; Regis et al., PRL 2015; Shirasaki et al., 2015, Branchini, SC et al., ApJS 2017]

Gamma Rays & Weak Lensing [SC, Fornasa, Fornengo & Regis, ApJL 2013] 10-3 shear - blazar, b bla = b h (M(L bla )) shear - SFG, b sfg = b h (M(L sfg )) shear - dec. DM 10-3 shear - blazar, b bla = b h (M(L bla )) shear - SFG, b sfg = b h (M(L sfg )) shear - ann. DM l (l+1) C l /(2π) 10-4 10-5 10-6 F lim = 2 10-9 cm -2 s -1 (E > 100 MeV) E > 1 GeV x 100 l (l+1) C l /(2π) 10 1 10 0 10-1 10-2 10-3 Cross-correlation Fermi LAT - Dark Energy Survey 10-4 Auto-correlation E > 1 GeV blazars annihilating DM 10 100 10-5 1000 10 100 1000 10 100 1000 10000 Multipole l Multipole l Multipole l l (l+1) C l /(2π) Fermi-LAT star-forming galaxies γ-rays 10-4 10-5 decaying DM 10-6 F lim = 2 10-9 cm -2 s -1 (E > 100 MeV) E > 1 GeV x 100 Cross-correlation Fermi LAT - Euclid

Gamma Rays & Weak Lensing [SC, Fornasa, Fornengo & Regis, 2015] Uncertainty on dark matter properties Thermal cross-section Benchmark model Uncertainty on unresolved astrophysical emission

Gamma Rays & Weak Lensing σannv [cm 3 s 1 ] 10 21 10 22 10 23 10 24 10 25 10 26 HIGH HIGH + astro MID LOW Thermal cross-section [Tröster, SC et al., 2017] b b, CFHTLenS + RCSLenS + KiDS 10 1 10 2 10 m DM [GeV]

Gamma Rays & Clusters [(cm -2 s -1 sr -1 ) sr] 10-9 10-10 10-11 10-12 Fermi-LAT x redmapper E γ > 1 GeV [Branchini, SC et al., 2017] blazars magn SFG ICM noise C l γc 10-13 10-14 10 100 1000 Multipole l

Outline Synergies: Why and how? Synergies vs Noise: Indirect search of particle dark matter signatures Synergies vs Cosmic Variance: Multi-tracing galaxy number counts

Galaxy Number Counts Proxy of the matter power spectrum f(t,x) δ g (t,x)=b g (t)δ(t,x) Primordial non-gaussianity One of inflation s 4 smoking guns Tightest available constraints from CMB: f NL < ~10 f NL > 0 P δ (k,z) P g (k,z)

Galaxy Number Counts Proxy of the matter power spectrum f(t,x) δ g (z,ˆn)= N g(z,ˆn) N g (z) N g (z)

Galaxy Number Counts Proxy of the matter power spectrum N g (z,ˆn) N g (z) N g (z) δρ(z,ˆn) ρ( z) d ρ d z δz(z,ˆn) ρ( z) + δv(z,ˆn) V(z) [Yoo, 2010; Bonvin & Durrer, 2011; Challinor & Lewis, 2011; Bertacca et al., 2012]

Galaxy Number Counts Proxy of the matter power spectrum N g (z,ˆn) N g (z) N g (z) δρ(z,ˆn) ρ( z) d ρ d z δz(z,ˆn) ρ( z) + δv(z,ˆn) V(z) Newtonian density fluctuations [Yoo, 2010; Bonvin & Durrer, 2011; Challinor & Lewis, 2011; Bertacca et al., 2012] Redshift-space distortions Lensing Gravitational redshift, time delay, Sachs-Wolfe and integrated Sachs-Wolfe

Accessing the Largest Scales Probe huge volumes [high sensitivity at high-z over large sky areas] [SDSS-III BOSS Collaboration, 2012] Beat cosmic variance [we have only one Universe to observe!]???????

Multi-Tracer Technique Comparing the relative clustering of different populations of tracers [Seljak, 2009; Seljak & McDonald, 2009]

Multi-Tracer Technique Comparing the relative clustering of different populations of tracers [Seljak, 2009; Seljak & McDonald, 2009] [Fonseca, SC, Santos & Maartens, ApJ Lett. 2015] Forecast error on fnl Noise level

Summary Great time for synergies among cosmological surveys at various wavelengths Cross-correlations valuable for: Cross-checking validity of cosmological results Accessing signal buried in noise or cosmic variance [e.g. particle dark matter signatures, multi-tracing for non-gaussianity] Removing/alleviating contamination from systematic effects [e.g. radio-optical cosmic shear]