Non-linear bayesian inference of cosmic felds in SDSS3 and 2M++ - Guilhem Lavaux (IAP/CNRS) Cosmo21 - Valencia 2018 Aquila consortium ...
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Non-linear bayesian inference
of cosmic felds in SDSS3 and 2M++
Guilhem Lavaux (IAP/CNRS)
and Aquila Consortium
Cosmo21 – Valencia 2018
Aquila consortium (https://aquila-consortium.org)
Outline
The statistical framework
The 2M++ compilation
(presentation, clusters, velocity felds, applications)
SDSS3 BOSS
(more modeling challenges, density feld)
Conclusion
From theory to observations...
Model Observations
Perfect Great but messy
Complete description We do not understand the physics
Full knowledge of physics Systematics not fully known
Did I say perfect ? Good attempt by observers to
seemingly make our life easier
end up bad
Various hacking to make sense of data
From theory to observations...
Model Observations
Perfect Great but messy
Complete description We do not understand the physics
Full knowledge of physics Systematics not fully known
Did I say perfect ? Good attempt by observers to
seemingly make our life easier
end up bad
BORG3
Still far too perfect though… (see later)
Another perspective to automatically solve
this problem: see Tom Charnock’s talk
The BORG3 inference framework
Initial conditions
Jasche et al. (2010), Jasche & Wandelt (2013), Lavaux & Jasche (2016), Jasche & Lavaux (2017, 2018)
The BORG3 inference framework
Initial conditions
Total evolved matter density
Jasche et al. (2010), Jasche & Wandelt (2013), Lavaux & Jasche (2016), Jasche & Lavaux (2017, 2018)
The BORG3 inference framework
Initial conditions
Total evolved matter density
Biased galaxy distribution
Selected/contaminated sample
Random extraction (Poisson, Negative binomial, ...)
Jasche et al. (2010), Jasche & Wandelt (2013), Lavaux & Jasche (2016), Jasche & Lavaux (2017, 2018)
The BORG3 inference framework
Forwa
rd and
Initial conditions adjoin
t m od
el
Total evolved matter density
Biased galaxy distribution
Selected/contaminated sample
Random extraction (Poisson, Negative binomial, ...)
Jasche et al. (2010), Jasche & Wandelt (2013), Lavaux & Jasche (2016), Jasche & Lavaux (2017, 2018)
The BORG3 inference framework
Initial conditions
Total evolved matter density
Biased galaxy distribution
Selected/contaminated sample
Random extraction (Poisson, Negative binomial, ...)
Easily
Easilyexchangeable
exchangeableto totry
try
your
yourfavorite
favoritedifferentiable
differentiablemodel
model
Jasche et al. (2010), Jasche & Wandelt (2013), Lavaux & Jasche (2016), Jasche & Lavaux (2017, 2018)
The BORG3 inference framework
Initial conditions
Total evolved matter density
Biased galaxy distribution
Selected/contaminated sample
Random extraction (Poisson, Negative binomial, ...)
Encode
Encodesurvey
surveysystematic
systematiceffects
effectswith
withexpansions:
expansions:
Jasche et al. (2010), Jasche & Wandelt (2013), Lavaux & Jasche (2016), Jasche & Lavaux (2017, 2018)Application to 2M++ galaxy compilation:
Detailed dynamical modelingThe 2M++ galaxy compilation
SDSS 0 Mpc/h
Galaxy distribution
2MRS
250 Mpc/h
Redshift completeness 6dF
~70 000 galaxies Lavaux & Hudson (MNRAS, 2011)Inferred density fields
Ensemble average density fields at z=0
Clusters
Higher error
Mean
Void
Jasche & Lavaux (2018, in prep.)Performance aspect (2): burnin
Jasche & Lavaux (2018, in prep.)Initial condition powerspectrum
Initial conditions
Post PM simulation
Jasche & Lavaux (2018, in prep.)Virgo cluster
Virgo center
~30 Mpc/h
Jasche & Lavaux; Lavaux & Jasche; Peirani, Lavaux & Jasche (2018, in prep.)Coma dynamical properties
Coma center
Jasche & Lavaux; Lavaux & Jasche; Peirani, Lavaux & Jasche (2018, in prep.)Coma dynamical properties
Zoom simulation on Coma
(~250 Mpart in zoom)
Jasche & Lavaux; Lavaux & Jasche; Peirani, Lavaux & Jasche (2018, in prep.)Shapley concentration
Single realisation density
Shapley center
~60 Mpc/h
Lavaux & Jasche (2018, in prep.)Shapley concentration
Ensemble average density
Shapley center
~60 Mpc/h
Lavaux & Jasche (2018, in prep.)Inferred velocity fields
+400 km/s 800 km/s
Outfall
Higher error
Infall
-400 km/s 0 km/s
Jasche & Lavaux (2018, in prep.)Velocity field and Hubble constant
Mean error on Hubble measurement using tracers from observed large scale structures
TODO: Compare all the flow models
Jasche & Lavaux (2018, in prep.), Lavaux & Jasche (2018, in prep.)Application to Sloan Digital Sky Survey III:
Deep cosmological applicationSDSS3 data
Panstarrs
SDSS DR12 galaxy sample
~1.6 millions of galaxies
SDSSForward model becomes more complex
Cosmic expansion Cosmic growth of structures
Non-linear density remapping: Implemented so far for (2)LPT:
(see Doogesh’ poster)
Kodi Ramanah, Lavaux, Jasche, Wandelt (2018, in prep.)Forward model becomes more complex
Cosmic expansion
Lo
ok
ba
ck
tim
e
(see Doogesh’ poster)
Kodi Ramanah, Lavaux, Jasche, Wandelt (2018, in prep.)Forward model becomes more complex
Cosmic expansion
Lo
ok
ba
ck
tim
e
(see Doogesh’ poster)
Kodi Ramanah, Lavaux, Jasche, Wandelt (2018, in prep.)Forward model becomes more complex
Cosmic expansion Cosmic growth of structures
Lo
ok
ba
ck
tim
e
Time
(see Doogesh’ poster)
Kodi Ramanah, Lavaux, Jasche, Wandelt (2018, in prep.)… and systematic cleaning…
11 foregrounds (here only 8)… still much less than Leistedt & Peiris (2014) but improving
DUST
psfWidth
Sky fluxes
0
...
Star densities
...Example fitted composite...
11 foregrounds (here only 8)… still much less than Leistedt & Peiris (2014) but improving
DUST
psfWidth
Sky fluxes
0
...
Star densities
...
PreliminaryInferred density of SDSS3
Ensemble density average Error estimate from ensemble variance
SGC
NGC
Main galaxy sample limit
(not included)
LOWZ limit
CMASS limit PreliminarySky density
PreliminaryConclusion
The Aquila consortium
●
Founded in 2016
●
Gather people interested in working with each other on developing the Bayesian pipelines
and run analysis on data.
https://aquila-consortium.org/The Aquila consortium
●
Founded in 2016
●
Gather people interested in working with each other on developing the Bayesian pipelines
and run analysis on data.
https://aquila-consortium.org/
A biased list of Aquilians… check the website!
Natalia Porqueres Minh Nguyen Doogesh Kodi Ramanah
Tom Charnock Florent LeclercqConclusion: great future
2M++
2M++ SDSS
SDSS CosmicFlows
CosmicFlows LSST?
LSST?
BORG3+
BORG3+
Predictive
Predictivecosmology
cosmology Cosmological
Cosmologicalmeasurement
measurement
●
Velocity field (also VIRBIUS with F. Fuhrer) ●
Cosmic expansion (see Doogesh’s talk)
●
X-ray cluster emission ●
Power spectrum (and governing parameters)
●
Kinetic Sunyaev Zel’dovich ●
Gaussianity tests of initial conditions
●
Rees-Sciama ●
Direct probe of dynamics
●
Dark matter ?Conclusion: great future and challenges
2M++
2M++ SDSS
SDSS CosmicFlows
CosmicFlows LSST?
LSST?
BORG3+
BORG3+
Predictive
Predictivecosmology
cosmology Cosmological
Cosmologicalmeasurement
measurement
●
Velocity field (also VIRBIUS with F. Fuhrer) ●
Cosmic expansion (see Doogesh’s talk)
●
X-ray cluster emission ●
Power spectrum (and governing parameters)
●
Kinetic Sunyaev Zel’dovich ●
Gaussianity tests of initial conditions
●
Rees-Sciama ●
Direct probe of dynamics
●
Dark matter ?
Galaxy
Galaxyformation:
formation:bias
biasand
andlikelihood
likelihood
Instrument
Instrumentmodeling
modelingYou can also read
