Simulations of polarised dust emission

Transcription

1 Simulations of polarised dust emission Flavien Vansyngel - Institut d Astrophysique Spatiale Collaborators: François Boulanger, Tuhin Ghosh, Andrea Bracco, Jonathan Aumont CMB-S4 meeting 03/016

2 Dust contamination Toward North pole Toward South pole Planck collab. PIPXXX 014 current upper limit for r BICEP field

3 Fake CMB B-modes Figure 1. Recovered posterior distribution P (r) of tensor-to-scalar ratio and impact of incorrect dust modelling. The oretical input tensor-to-scalar value (vertical solid black line) is r = 0 in left-hand panels and r = 0.05 in right-hand panels. Top panels: no foregrounds (left: Model 0a, right: Model 0b). Middle panels: correct foreground modelling (left: Model a, right: Model 1a). Bottom panels: incorrect spectral modelling of rmal dust (left: Model b, right: Model 1b). Recovered tensor-to-scalar distributions: COrE (solid yellow), COrE+ Light (solid light-blue), COrE+ Extended (solid blue), LiteBIRD (dotted red), PIXIE (dashed green), EPIC-LCTES (long-dashed yellow), EPIC-CS (long-dashed purple), EPIC-IM-4K (long-dashed orange), PRISM (dash three-dot black). The top left panel compares overall sensitivity of di erent satellites in absence of foregrounds by showing for Model 0a (r = 0, no foregrounds) r.m.s of residual noise B-mode map after component separation. Remazeilles, Dickinson, Eriksen & Wehus, 015

4 Topical questions What experimental design for optimal cleaning? What level of B-modes can be actually reached? How to quantify confidence in cleaning?

5 Topical questions What experimental design for optimal cleaning? What level of B-modes can we actually reach? How to quantify confidence in cleaning? Need sky simulations to test component separation methods

6 Log[power] Usual ISM dust model At map level a D spatial template scaled through frequencies using a grey-body law At power spectrum level a power law freq. Log[angular scale] Effective model

7 Actual ISM dust...

8 Actual ISM dust dust grains properties turbulence 3D magnetic field bright molecular clouds...

9 Toward realistic dust simulations Why is dust emission polarised? Dust grains are heated by star light They radiate rmal emission (microwave domain) grains are not spherical and aligned with ambient galactic magnetic field One dust grain produced in laboratory

10 STEP 1: Galactic magnetic field ~B gal = ~ B 0 ˆB0 + f m ˆBturb with random Model for mean magnetic field Relative strength of turbulent field 3D power index of turbulent field

11 STEP : Stokes parameters Q/I One random realisation of magnetic field U/I

12 STEP 3: depolarisation Q/I U/I + + Stack N layers of Q/I,U/I B1 B B3

13 STEP 4: dust Stokes parameters Q/I U/I I multiply by an external intensity map I Q U

14 TE correlation TE power Two-point statistics of model TE correlation BB/EE ratio Data PIPXXX 014 ratio 0.5 multipoles fsky Simulations N laye ratio 1 multipoles multipoles

15 STEP 5: introduce correct statistics (I,Q,U)A such that: (I,Q,U)B such that: linear transform at alm level 8 >< b T`m = tat`m b >: È m = p 0(a È m + at`m ) b B`m = p 0fa B`m In particular: include E-B asymmetry and TE correlation

16 Properties of simulations BB power spectrum E-B asymmetry power data sims ratio multipoles multipoles The simulations are able to reproduce data at power spectrum level Vansyngel, Boulanger & Ghosh (in prep.)

17 PDF of power spectra PDF of E power at multipole ~110 Residuals very close to Gaussian Vansyngel, Boulanger & Ghosh (in prep.)

18 EE power at ell=80 EE power at ell=80 Properties of simulations A EE /hii.1 Empirical law A EE /hii 1.9 PIPXXX 014 mean intensity mean intensity Vansyngel, Boulanger & Ghosh (in prep.)

19 Case of synchrotron Suppose that we can apply same procedure with differences: 1. Magnetic field Same statistical model, but a different realisation from that of dust. Intensity map Haslam map with small scales added

20 Dust-Synchrotron correlation dust E x synch E 30% 50% 70% dust B x synch B 30% 50% 70% Common mean field not sufficient

21 Dust-Synchrotron correlation independent realisations: (Q/I,U/I)1 and (Q/I,U/I) dust[qu] = dustint (κ ([QU]/I)1 + (1-κ) ([QU]/I) ) sync[qu] = syncint ( (1-κ) ([QU]/I)1 + κ ([QU]/I) ) κ: ad-hoc input

22 Furr work is needed Full sky modeling Physical modeling of matter-polarisation correlation filament align with magnetic field Need high resolution noiseless intensity template Extrapolation through frequencies beta spatial variation angle decorrelation

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24 se se a a Galactic Galactic magnetic magnetic field field model model Planck Collaboration: The local structure of Galactic magnetic field One-point statistics of model STEP 1 with 1 STEP with se a Galactic magnetic field model se a GalacticPolarisation magneticfraction field model Polarisation angle (direction of pola)fig. 10. spherical harmonic spherical harmonic decomposition Planck Collaboration: The local structure of Galactic magnetic field decomposition (Q+U )/I Nlayers Planck Collaboration: The local structure of Galactic magnetic field Fig. 10. Cartoon showing integration along line of sight of a modelled qc with four distinct polarization layers having a same value of fm and a same ordered-field direction. mean magnetic field mean magnetic field with 1 in which i = 1, and p = 11.89%. Thus, modelled p with results from Q Q +U U p =. (14) (D ) relative strength of turbulent field In bottom panel of Fig. 9 we show comparison between relative strength of turbulent field 0.4 histograms of p of data (black dots) and of model. In e M1 M M 353 M1 M of a mod same val particular, we present average over 0 realizations of model 3D power index of D power index of Nlayers spherical harmonic B (blue line) and corresponding 1 (bright blue shade) and (dark blue shade) variations. The dashed vertical line spherical harmonic decomposition refers to value of p = 11.89%. We notice that modelling p turbulent field decomposition allows us to nicely control level of noise in data. Indeed, turbulent field e mean magnetic field mean magnetic field Fig. 9. Top: histogram of about south Galactic pole 7 ROT (black dots), polarization angle inferred from Stokes parameters rotated with respect to best-fit uniform direction R of magnetic field (QR353 and U353 ). The error bars represent Poisson noise within each bin of histogram. The green line represents mean model B for fm = 0.4 over 0 different realizations. The green shades correspond to 1 (light green) and (dark green) variations of model. The dashed vertical line indicates no dispersion about uniform direction. Bottom: histogram of p obtained combining Yearmaps (black dots) as described in text for same pixels of top panel. The error bars represent Poisson noise within each bin of histogram. Model B is now in blue and it has same characteristics described in top panel. The dashed vertical line corresponds to an e ective polarization fraction of pe = 11.89%. in which results fr Planck Collaboration: we manage to recover all negative p values, which are only The local structure of Galactic magnetic field caused by noise in combination of Year-maps. Fig. 10. Cartoon showing integration From figure it is clear that our description of of a modelled qc with four distinct pola magnetic-field structure (using A and B) Fig. 1. Modelled histograms of models p (normalized to does unity not withsupp0 ) same value of fm and a same ordered-fie ply a satisfying of. The obtained around characterization south-galactic poledistribution from modelofc,p where data strong depolarization toward low p 1values, fm =show 0.9, aand value of N varies as follows: (dark which blue), is not seen in model, where distribution tends to peak at in which i = 1, and pe = 11.89%. (light blue), 7 (turquoise), 30 (yellow), 60 (orange), 100 (dark value of p. Moreover, large variance in data, also e results from red). In se models noise is not added. Q M1 Q M + U M1 found by Planck Collaboration Int. XIX (015) at intermediate pm = Galactic latitudes, produces a significant tail in distribution (D353 ) toward high values of p that is not reproduced by our model. In bottom panel of Fig. 9 we show t histograms of p of data (black do Making use of qc and uc, we replace qb and ub in Eq. (13), and 4.3. C: importance of modelled turbulencedistributions along line of particular, we present average over Q353 Model and U353 in Eq. (10), to get around sight B (blue line) and corresponding 1 south-galactic pole of p and ROT, given a magnetic-field and (dark blue shade) variations. T structure composed of an ordered field and LOS and POS turat this stage, it is important to keep in mind that observed refers to value of pe = 11.89%. We n bulent components. We stress that, thanks to model C, p in depolarization also depends on several factors that we havee not allows us to nicely control level of n Eq. (13) is now replaced by p. The modelled distributions deconsidered in modelling 0yet (see Eq. ()), such as variwe manage to recover all negative p pend on three parameters: p, f, and N. We fit data with 0 M ations of dust properties, encoded in p0, and fluctuations of caused by noise in combination of th model C structure exploringalong parameter of p0 between 15% and field LOS space and within Planck beam, From figure it is clear that o 40%, of fm between 1 and 17. parametrized by F. 0. and 1.8, and of N between magnetic-field structure (using models A For Being each triad of parameters we perform amagnetic-field -minimization of this work a specific study of ROT strucfig. 9. Top: about south Galactic pole ply Fig.a 1. Modelled histograms of of p (no histogram satisfying characterization combined reduced distributions of p -fit and -fit, ROT ture in Planck data at high-galactic latitudes, (black polarization dots), polarization angle inferred from Stokes pa- data obtained south-galactic po show around a strong depolarization towar as follows here we propose a phenomenological model (hereafter rameters rotated with respect to best-fitmodel uniform direction isfmnot=seen 0.9, and value of N varies in model, where distra R for variations R and C), which does of pu error southof not account magnetic field (Q ). The bars represent 0 across = +. (16) (light blue), 30 large (yellow value of pe 7. (turquoise), Moreover, va tot p ROT Galactic pole, and which only LOS e ects. The green found Poisson noisefocuses within on each bingeometric of histogram. red). In models noise is not byse Planck Collaboration Int.added XIX relative strength of turbulent field relative strength of turbulent field 0.9 3D power index of turbulent field D power index of turbulent field Fig. 11. Same as in Fig. 9 but with modelled histograms now fm = 0.4. In to doing so Cwewith nowfmproduce two in corresponding model = 0.9, N = 7, andvariables p0 = 6% Eq. (6) where turbulent component is considered (hereafter (dashed-vertical line) (see text for definition of paramese two variables are qb and ub ). We n make four realizaters). tions of Planck statistical noise (nqi and nui, with i = 1, ), and, as in Eq. (7), we produce two pairs of independent samples data sims In bo histo figures from A. Bracco Ph.D sis

25 PDF of power spectra r cosmic variance total variance 30% 1%