An exploration of dark energy and beyond the standard model with analytical and numerical tools for the large scale structures of the universe

 

Santiago Casas

 

 

Postdoctoral Researcher

TTK, RWTH Aachen University

     @santiagocasas                                                                                        @sant87casas

santiagocasas.github.io

Dark Energy & Modified Gravity

The Horndeski Lagrangian

PhD thesis: Non-linear structure formation in models of Dark Energy and Modified Gravity, http://archiv.ub.uni-heidelberg.de/volltextserver/23120/

Beyond Einstein's GR

Scalar-Tensor theories

Effect on LSS

N-Body simulations

CONCEPT: Python and Neutrinos

GADGET2/CoDECS

Credit: Yun Ling, My bachelor student,

Jeppe Dakin (U. Zurich)

Credit: Dr. Marco Baldi, Master thesis co-supervisor

Approximate methods: COLA

ABACUS: Fits for GCspectro with 1loopEFT

Other codes tested:

gevolution

flowpm

GNQ: Growing Neutrino Quintessence (developed in Heidelberg)

Credit: Winther, SC, Koyama, et al (2019)

Credit: SC, Führer, Ayaita, Weber, Wetterich

Credit: Rademacher, Moradinezhad, Lesgourges, SC

My Journey with Euclid

Credits: www.esa.int/Science_Exploration/Space_Science/Euclid, www.euclid-ec.org, ESA/NASA/SpaceX, Euclid Consortium

Euclid consortium scientist visits Cannes. Credits: ThalesAlenia Space

Euclid preparation: VII. Forecast validation for Euclid cosmological probes,,Blanchard et al. arXiv:1910.09273

★ Awardees of the Euclid STAR Prize Team 2019

EC Builder Status achieved 2023

Early Release Observations. ECICOM, ECEPO: Social media manager of instagram: @euclidconsortium

Euclid Launch: 1st July 2023

Large forecasting projects

The Fingertip Galaxy

WEAK Lensing and Galaxy Clusteering

SC, Lesgourgues, Schöneberg, et al., Euclid: Validation of the MontePython forecasting tools, 2303.09451 

SC, Kunz, Martinelli, Pettorino, Phys.Dark Univ. 18 1703.01271

3x2pt Photometric Cosmic Shear + Clustering

Spectroscopic Galaxy Clustering: BAO+RSD+DM+LSS+Galaxy bias

Excellent complimentarity

https://www.esa.int/Science_Exploration/Space_Science/Euclid/Euclid_test_images_tease_of_riches_to_come

FISHER Matrix FORECASTS

Code: CosmicFish

S.Casas, M.Martinelli and M.Raveri

Soon to be released: Full pythonic version

https://github.com/santiagocasas/cosmicfishpie

Cosmomathica/Fishermathica

Python, Numpy-intensive

Couples to CAMB, CLASS, HiCLASS, MGCAMB, input4cast files

GC, WL, 21cm-IM, 3x2pt, CMB

Euclid, DESI, Rubin LSST, SKAO

Wolfram Language,

Cosmomathica-FORTRAN link for CAMB

GC, WL

Euclid, SKA1

Used to produce and validate IST:F forecasts 2015-2019

Hessian of a Gaussian Likelihood. Used to approximate posterior distributions at the maximum (fiducial value)

First code to be validated against MontePython MCMC forecasts

SC, Lesgourgues, Schöneberg, et al., Euclid: Validation of the MontePython forecasting tools, 2303.09451 

Euclid preparation: VII. Forecast validation for Euclid cosmological probes,,Blanchard et al. arXiv:1910.09273

SC, Kunz, Martinelli, Pettorino, Phys.Dark Univ. 18 1703.01271

https://github.com/santiagocasas/cosmomathica

Euclid theory working group

SC, I. Tutusaus : Work Package lead of WP6, Forecasting and statistics

SC: Member of WP1,2,3,4,6,7,11 : From theory and non-linearities to likelihood

SC: Co-coordinator of the KeyPaper-Theory-1 project

\rm{d}s^2 = -(1+2\Psi) \rm{d}t^2 + a^2(1-2\Phi) \rm{d}x^2
G_{\rm eff}=\left(1+ \frac{2\beta^2(\phi_0)}{Z(\phi_0)}e^{-m(\phi_0)r}\right) G_N
\newcommand{\sg}{\ensuremath{\sigma_{8}}} \newcommand{\de}{\mathrm{d}} S = \frac{c^4}{16\pi G} \int{\de^4 x \sqrt{-g} \left[R+f(R)\right]}

SC, Cardone, Sapone, et al, Euclid: Constraints on f(R) cosmologies from the spectroscopic and photometric primary probes, 2306.11053 

Frusciante, Pace, Cardone, SC et al, Euclid: Constraining linearly scale-independent modifications of gravity with the spectroscopic and photometric primary probes, 2306.12368

Main tasks:

Constrain gravitational potentials

Test for screening mechanisms

Check theories of modified gravity

Requires expertise with modified Einstein-Boltzmann solvers,

Emulators, Halo-model,

Fisher and likelihoods

Euclid: Likelihood and Nonlinear TASKFORCES

  • GCspectro: EFT 1-loop RSD in multipoles
  • 3x2pt photo:
    • Covariance, nonlinear Super-Sample
    • Galaxy Bias expansion
    • Emulators for nonlinear, HMCode, Halofit, Bacco, EuclidEmu
    • Baryonic Feedback: different parameters
  • Different emulators with systematic offsets
  • Euclid error bars can distinguish among them

EUCLID PRELIMINARY

Credit: P. Carrilho for IST:NL

Credit: SC, for IST:NL

Cosmological Likelihood for Observables in Euclid

Credit: SC, for IST:L

Credit: SC, for IST:NL

SC: Main developer and core member of CLOE. KeyPaper co-lead of 3x2pt in IST:NL

Preparation of DR1 analysis

  • Biasing when failing to analyse data with correct model of baryonic feedback

Other Surveys and CROss-correlations

Vera Rubin Observatory, LSST Project Office - http://www.lsst.org/gallery/telescope-rendering-2013

DESI telescope in Tucson, Arizona, in the Schuk Toak District on the Tohono O’odham Nation

Square Kilometer Array Observatory https://www.skao.int/

SC, Carucci, Pettorino et al (2022), Constraining gravity with synergies between radio and optical cosmological surveys, 2210.05705 

CMB Stage-IV experiments:  https://kipac.stanford.edu/research/projects/cmb-stage-4

Invited talk at the Manchester Optical x Radio Synergy meeting

Neutrinos and LSS with Euclid & more

Euclid Preparation: Sensitivity to Neutrino parameters. (Under internal review). Archidiacono, Lesgourgues, SC, Pamuk, et al.

EUCLID PRELIMINARY

  • \(M_{\nu}\) and \(N_{\rm eff}\)
  • Combination of different probes breaks degeneracies
  • For our given \(\ell_{\rm max}\) the effect of baryonic feedback is small <10%
  • Euclid (all) 1\(\sigma\) error: 30-60 meV

Text

future avenues of work

Merci!!

In collaboration with Johanna Schaffmeister and Sven Günther, students at RWTH

  • More work on uncertainty-aware emulators. https://github.com/santiagocasas/looti
  • Both for non-linear power spectra, as well as for baryonic feedback, MG-effects and neutrinos.
  • Work on 1loop-EFT for LSS in the case of GC-spectro (currently in prep. with Linde, Lesgourgues and Moradinezhad. Inclusion of consistent treatment for Neutrinos and Modified Gravity. (in collab with Linde, Pietroni, Fidler).
  • JAX-COSMO: Campagne, Lanusse, Zuntz, SC, et al, 2302.05163.
  • Implement auto-differentiability into commonly used codes in the field: CLASS, CAMB, HMCode, Looti, and Euclid codes: CLOE.
  • Use auto-diff emulators: CosmoPower (Spurio-Mancini, et al)
  • SC: Invited participant at 3-month MIAPP Differentiable physics workshop
  • This allows for fast, efficient variational parameter estimation, orders of magnitude faster than conventional tools. Data compression, automatic Fishers, optimization, etc....
  • Careful study of the effect of emulators and baryonic feedback on the Euclid 3x2pt observables. Parameter estimation biases, efficient sampling, sensible priors....
  • Preparation of consistent (and alternative) pipelines for Euclid data release analysis, including cross-correlations with Clusters, Voids or other non-Gaussian observables and correlations with other surveys such as CMB, radio 21cm IM, SNIa and gravitational wave sirens.