DESI 2024: Survey overview and cosmological constraints from DR1 BAO and Full Shape measurements

Arnaud de Mattia

CEA Saclay

CPPM

November 2024

Thanks to our sponsors and

72 Participating Institutions!

DESI 3D Map

Physics program
- Galaxy and quasar clustering
- Lyman-alpha forest
- Clusters and cross-correlations
- Galaxy and quasar physics
- Milky Way Survey
- Transients and low-z

DESI 3D Map

Physics program
- Galaxy and quasar clustering
- Lyman-alpha forest
- Clusters and cross-correlations
- Galaxy and quasar physics
- Milky Way Survey
- Transients and low-z

DESI: a stage IV survey

Schlegel et al. 2022, arXiv:2209.03585

10 years = $10 \times $

DESI Y5 galaxy samples

Bright Galaxies: 14M (SDSS: 600k)

0 < z < 0.4

LRG: 8M (SDSS: 1M)

0.4 < z < 0.8

ELG: 16M (SDSS: 200k)

0.6 < z < 1.6

QSO: 3M (SDSS: 500k)

Lya $1.8 < z$

Tracers $0.8 < z < 2.1$

Y5 $\sim 40$M galaxy redshifts!

$z = 0.4$

$z = 0.8$

$z = 0$

$z = 1.6$

$z = 2.0$

$z = 3.0$

From images to redshifts

imaging surveys (2014 - 2019) + WISE (IR)

target selection

spectroscopic observations

spectra and redshift measurements

Mayall Telescope

focal plane 5000 fibers

wide-field corrector

6 lenses, FoV $\sim 8~\mathrm{deg}^{2}$

Kitt Peak, AZ

4 m mirror

Mayall Telescope

focal plane 5000 fibers

fiber view camera

ten 3-channel spectrographs

49 m, 10-cable fiber run

Kitt Peak, AZ

Focal plane: 5000 robotic positioners

Exposure time (dark): 1000 s

Configuration of the focal plane
CCD readout
Go to next pointing

140 s

0.1 mm

Spectroscopic pipeline

wavelength

fiber number

$z = 2.1$ QSO

$z = 0.9$ ELG

Ly$\alpha$

CIV

CIII

[OII] doublet at $2727 \AA$ up to $z = 1.6$

[OII]

Ly$\alpha$ at $1216 \AA$ down to $z = 2.0$

DESI data release 1 (DR1)

Observations from May 14th 2021 to June 12th 2022

Final survey

- dark time (LRG, ELG, QSO): 7 layers

- bright time (BGS): 5 layers

- 14,000 $\mathrm{deg}^2$

Release of DESI DR1 (BAO) results

April 4th 2024

First batch of DESI DR1 cosmological analyses
https://data.desi.lbl.gov/doc/papers/
• DESI 2024 I: First year data release
• DESI 2024 II: Sample definitions and two-point clustering statistics
• DESI 2024 III: BAO from Galaxies and Quasars
• DESI 2024 IV: BAO from the Lyman-Forest
• DESI 2024 V: Full Shape measurements from Galaxies and Quasars
• DESI 2024 VI: Cosmological constraints from BAO measurements
• DESI 2024 VII: Constraints from the Full Shape measurements

Release of DESI DR1 (FS) results

November 17th 2024

Second batch of DESI DR1 cosmological analyses
https://data.desi.lbl.gov/doc/papers/
• DESI 2024 I: First year data release
• DESI 2024 II: Sample definitions and two-point clustering statistics
• DESI 2024 III: BAO from Galaxies and Quasars
• DESI 2024 IV: BAO from the Lyman-Forest
• DESI 2024 V: Full Shape measurements from Galaxies and Quasars
• DESI 2024 VI: Cosmological constraints from BAO measurements
• DESI 2024 VII: Constraints from the Full Shape measurements

Clustering analysis

galaxy catalog

galaxy power spectrum (or correlation function)

cosmological constraints

compression = "we measure specific features"

"variance of the density field as a function of scale"

Full Shape (baseline)

BAO

ShapeFit (alternative Full Shape)

Baryon acoustic oscillations

Sound waves in primordial plasma

At recombination ($z \sim 1100$)

plasma changes to optically thin
baryons decouple from photons
sound wave stalls

spherical shell in the distribution of galaxies, of radius the distance that sound waves travelled

= sound horizon scale at the drag epoch $ r_\mathrm{d} \sim 150 \; \mathrm{Mpc} \sim 100 \; \mathrm{Mpc}/h $

standard ruler

BAO measurements

transverse to the line-of-sight: $D_\mathrm{M}(z) / r_\mathrm{d}$
along the line-of-sight: $D_\mathrm{H}(z) / r_\mathrm{d} = c / (H(z) r_\mathrm{d}) $

\theta_\mathrm{BAO} = r_\mathrm{d} / D_\mathrm{M}(z)

transverse comoving distance

sound horizon $r_d$

BAO measurements

transverse to the line-of-sight: $D_\mathrm{M}(z) / r_\mathrm{d}$
along the line-of-sight: $D_\mathrm{H}(z) / r_\mathrm{d} = c / (H(z) r_\mathrm{d}) $

\Delta z_\mathrm{BAO} = r_\mathrm{d} / D_\mathrm{H}(z)

Hubble distance

sound horizon $r_d$

transverse to the line-of-sight: $D_\mathrm{M}(z) / r_\mathrm{d}$
along the line-of-sight: $D_\mathrm{H}(z) / r_\mathrm{d} = c / (H(z) r_\mathrm{d}) $

At multiple redshifts $z$

BAO measurements

z_1

z_2

z_3

Probes the expansion history, hence the energy content

Absolute size at $z = 0$: $H_0 r_d$

Release of DESI DR1 (BAO) results

April 4th 2024

First batch of DESI DR1 cosmological analyses
https://data.desi.lbl.gov/doc/papers/
• DESI 2024 I: First year data release
• DESI 2024 II: Sample definitions and two-point clustering statistics
• DESI 2024 III: BAO from Galaxies and Quasars
• DESI 2024 IV: BAO from the Lyman-Forest
• DESI 2024 V: Full Shape measurements from Galaxies and Quasars
• DESI 2024 VI: Cosmological constraints from BAO measurements
• DESI 2024 VII: Constraints from the Full Shape measurements

Correlation functions

BAO peak

Excess probability to find 2 galaxies separated by a distance s

Power spectra

BAO wiggles

Fourier transform of the correlation function

Some fits: correlation function

isotropic measurement

anisotropic measurement

\propto (D_{\mathrm{M}}^{2}(z) D_\mathrm{H}(z))^{1/3} / r_\mathrm{d}

\propto D_{\mathrm{M}}(z) / D_\mathrm{H}(z)

Density field reconstruction

Non-linear structure growth and peculiar velocities blur and shrink (slightly) the ruler

Reconstruction: estimate Zeldovich displacements from observed field and moves galaxies back $\rightarrow$ refurbishes the ruler (improves precision and accuracy)

reconstruction

Density field reconstruction

DR1 BAO analysis: what's new?

Biggest ever spectroscopic BAO dataset ($N_\mathrm{tracer}$ and $V$)

5.7 million unique redshifts

Effective volume $V_\mathrm{eff} = 18 \; \mathrm{Gpc}^{3}$

$3 \times $ bigger than SDSS!

Biggest ever spectroscopic BAO dataset ($N_\mathrm{tracer}$ and $V$)
Blind analysis to mitigate observer / confirmation biases (catalog-level blinding)
Theory developments in BAO fitting code
New and improved reconstruction methods
New combined tracer method used for overlapping galaxy samples (LRG and ELG in $0.8 < z < 1.1$)
Unified BAO pipeline applied to all (discrete) tracer / redshift bins consistently

DR1 BAO analysis: what's new?

Tests of systematic errors

Considered many possible sources of systematic errors using simulations and data:

observational effects (imaging systematics, fiber collisions)
BAO reconstruction (2 algorithms compared)
covariance matrix construction
incomplete theory modelling
choice of fiducial cosmology
galaxy-halo (HOD) model uncertainties

no systematics detected

systematics << statistics

Maximum effect: $\sigma_\mathrm{stat. + syst.} < 1.05 \sigma_\mathrm{stat.}$

Release of DESI DR1 (BAO) results

April 4th 2024

First batch of DESI DR1 cosmological analyses
https://data.desi.lbl.gov/doc/papers/
• DESI 2024 I: First year data release
• DESI 2024 II: Sample definitions and two-point clustering statistics
• DESI 2024 III: BAO from Galaxies and Quasars
• DESI 2024 IV: BAO from the Lyman-Forest
• DESI 2024 V: Full Shape measurements from Galaxies and Quasars
• DESI 2024 VI: Cosmological constraints from BAO measurements
• DESI 2024 VII: Constraints from the Full Shape measurements

Ly$\alpha$ forest

Absorption in QSO spectra by neutral hydrogen in the intergalactic medium: $\lambda_\mathrm{abs} = (1 + z_\mathrm{HI}) \times 1215.17 \; \AA $

Transmitted flux fraction $F = e^{-\tau}$ probes the fluctuation in neutral hydrogen density, $\tau \propto n_\mathrm{HI} $

credit: Andrew Pontzen

Ly$\alpha$ correlation functions in DESI DR1

Ly$\alpha$ - Ly$\alpha$

Ly$\alpha$ - QSO

QSO

HI cloud

QSO

DR1 Ly$\alpha$ BAO analysis: what's new?

Biggest ever Ly$\alpha$ dataset ($N_\mathrm{tracer}$)

>420,000 Ly$\alpha$ QSO at z > 2.1

$2 \times $ more than SDSS!

Biggest ever Ly$\alpha$ dataset ($N_\mathrm{tracer}$)
First blind analysis to mitigate observer / confirmation biases (correlation function-level blinding)

DR1 Ly$\alpha$ BAO analysis: what's new?

Biggest ever Ly$\alpha$ dataset ($N_\mathrm{tracer}$)
First blind analysis to mitigate observer / confirmation biases (correlation function-level blinding)
Modelling of the correlation function: cosmological signal, and many contaminants!
Very stable results, systematic uncertainty neglected

DR1 Ly$\alpha$ BAO analysis: what's new?

transverse to the line-of-sight: $D_\mathrm{M}(z) / r_\mathrm{d}$
along the line-of-sight: $D_\mathrm{H}(z) / r_\mathrm{d} = c / (H(z) r_\mathrm{d}) $
low S/N, isotropic average: $ D_\mathrm{V}(z) / r_\mathrm{d} = (z D_{\mathrm{M}}^{2}(z) D_\mathrm{H}(z))^{1/3} / r_\mathrm{d}$

BAO measurements

Let's factor out the $h$ terms:

$\color{blue}{[D_\mathrm{M}(z) h] (\Omega_\mathrm{m}, f_\mathrm{DE}, \Omega_\mathrm{K}, ...)} \color{black}{/} \color{orange}{[r_\mathrm{d}(\Omega_\mathrm{m} h^{2}, \Omega_\mathrm{b} h^{2}) h]} $
$ \color{blue}{[D_\mathrm{H}(z) h] (\Omega_\mathrm{m}, f_\mathrm{DE}, \Omega_\mathrm{K}, ...)} \color{black}{/} \color{orange}{[r_\mathrm{d}(\Omega_\mathrm{m} h^{2}, \Omega_\mathrm{b} h^{2}) h]} $

BAO measurements at different $z$ constrain:

energy content $ \color{blue}{(\Omega_\mathrm{m}, f_\mathrm{DE}, ...)} $
constant-over-$z$ product $\color{orange}{r_\mathrm{d} h}$ i.e. $\color{orange}{H_{0} r_\mathrm{d}}$

DESI DR1 BAO

DESI DR1 BAO measurements

DESI DR1 BAO

DESI DR1 BAO measurements

DESI DR1 BAO

DESI DR1 BAO measurements

DESI DR1 BAO

DESI DR1 BAO measurements

DESI DR1 BAO

DESI DR1 BAO measurements

DESI DR1 BAO

DESI DR1 BAO measurements

Consistent with each other,

and complementary

\underbrace{\begin{align*} \Omega_\mathrm{m} &= 0.295 \pm 0.015 & \mathbf{(5.1\%)} \\ H_{0} r_\mathrm{d} &= (101.8 \pm 1.3) \, [100 \, \mathrm{km} \, \mathrm{s}^{-1}] & \mathbf{(1.3\%)} \end{align*}}_{\textstyle \text{\color{black}{DESI}}}

DESI DR1 BAO

DESI DR1 BAO measurements

Consistency with other probes

DESI DR1 BAO consistent with:

Consistency with other probes

DESI DR1 BAO consistent with:

SDSS eBOSS Collaboration, 2020

Consistency with other probes

DESI DR1 BAO consistent with:

SDSS eBOSS Collaboration, 2020
primary CMB: Planck Collaboration, 2018 and CMB lensing: Planck PR4 + ACT DR6 lensing ACT Collaboratio n, 2023, Carron, Mirmelstein, Lewis, 2022

BAO constrains $ r_\mathrm{d}(\blue{\Omega_\mathrm{m}} h^{2}, \orange{\Omega_\mathrm{b} h^{2}}) h $
$ \blue{\Omega_\mathrm{m}} $ constrained by BAO at different $z$
$\orange{\Omega_\mathrm{b}h^2}$ can be constrained by light element abundance from Big Bang Nucleosynthesis (BBN): Schöneberg 2024

$\implies$ constraints on $h$ i.e. $H_0 = 100 h \; \mathrm{km} / \mathrm{s} / \mathrm{Mpc}$

Hubble constant

\underbrace{ H_0 = (68.53 \pm 0.80) \, {\rm km\,s^{-1}\,Mpc^{-1}} }_{\textstyle \color{darkblue}{\text{DESI} + \text{BBN}}}

Hubble constant

\underbrace{ H_0 = (68.52 \pm 0.62) \, {\rm km\,s^{-1}\,Mpc^{-1}} }_{\textstyle \color{darkblue}{\text{DESI} + \theta_\ast + \text{BBN}}}

$\theta_\ast$ CMB angular acoustic scale

Consistency with SDSS

\underbrace{ H_0 = (68.53 \pm 0.80) \, {\rm km\,s^{-1}\,Mpc^{-1}} }_{\textstyle \color{darkblue}{\text{DESI} + \text{BBN}}}

Hubble constant

\underbrace{ H_0 = (68.52 \pm 0.62) \, {\rm km\,s^{-1}\,Mpc^{-1}} }_{\textstyle \color{darkblue}{\text{DESI} + \theta_\ast + \text{BBN}}}

Consistency with SDSS
In agreement with CMB
In $3.7 \sigma$ tension with SH0ES

\underbrace{ H_0 = (68.53 \pm 0.80) \, {\rm km\,s^{-1}\,Mpc^{-1}} }_{\textstyle \color{darkblue}{\text{DESI} + \text{BBN}}}

Hubble constant

\underbrace{ H_0 = (68.52 \pm 0.62) \, {\rm km\,s^{-1}\,Mpc^{-1}} }_{\textstyle \color{darkblue}{\text{DESI} + \theta_\ast + \text{BBN}}}

Release of DESI DR1 (FS) results

November 17th 2024

Second batch of DESI DR1 cosmological analyses
https://data.desi.lbl.gov/doc/papers/
• DESI 2024 I: First year data release
• DESI 2024 II: Sample definitions and two-point clustering statistics
• DESI 2024 III: BAO from Galaxies and Quasars
• DESI 2024 IV: BAO from the Lyman-Forest
• DESI 2024 V: Full Shape measurements from Galaxies and Quasars
• DESI 2024 VI: Cosmological constraints from BAO measurements
• DESI 2024 VII: Constraints from the Full Shape measurements

Full Shape measurements

clustering

We fit the "full shape" (FS) of the galaxy power spectrum multipoles

Full Shape measurements

RSD

observed redshift = Hubble flow and peculiar velocities (RSD = "redshift space distortions")

We fit the "full shape" (FS) of the galaxy power spectrum multipoles

v_\mathrm{pec} \propto f\sigma_8

shape

($ \Omega_\mathrm{cdm} h^2, \Omega_\mathrm{b} h^2, n_\mathrm{s}, \sum m_\nu $)

growth of structure $f\sigma_8$ sensitive to the theory of gravity and dark energy

Full Shape models

Three power spectrum Effective Field Theory models considered:

- velocileptors Maus et al. 2024

- folps Noriega et al. 2024

- pybird Lai et al. 2024

V = 200 \; [\mathrm{Gpc}/h]^3

credit: Mark Maus, Hernan Noriega, Yan Lai

Comparison paper:

Maus et al. 2024

Full Shape models

P_{s, g}(k, \mu) = \blue{P^\mathrm{PT}(k, \mu)} + \orange{(b + f\mu^2) (b \alpha_0 + f\alpha_2 \mu^2 + f\alpha_4 \mu^4) k^2 P_{s, b_1^2}(k)} + \purple{\mathrm{SN}_0 + \mathrm{SN}_2 k^2 \mu^2 + \mathrm{SN}_4 k^4 \mu^4}

perturbation theory term

linear and quasi-linear physics

counter-terms contribution

truncation of perturbative series

stochastic-terms contribution

small-scale galaxy physics

The Effective Field Theory in a nutshell

perturbation theory model + counter-terms and stochastic terms
dependence on cosmology into $P_\mathrm{lin}$, $f$ and Alcock-Paczynski parameters ($\mathrm{R.A.}, \mathrm{Dec.}, z \Rightarrow \mathrm{distance}$)

Biggest ever spectroscopic dataset ($N_\mathrm{tracer}$ and $V$)
Blind analysis to mitigate observer / confirmation biases (catalog-level blinding)
Effective Field Theory models
Full-Modelling ($\Omega_\mathrm{cosmo}$) and updated compression approach (ShapeFit)
Improvements in the treatment of observational systematics (e.g. fiber assignment)
Unified Full Shape pipeline applied to all (discrete) tracer / redshift bins consistently

DR1 Full Shape analysis: what's new?

Pinon et al. 2024, arXiv:2406.04804

Groups of galaxies too close to each other cannot all receive a fiber

$0.05^\circ \simeq$ positioner patrol diameter

Fiber assignment

Pinon et al. 2024

Fiber assignment

Impacts power spectrum measurements (altMTL vs complete)

Pinon et al. 2024

Impacts power spectrum measurements (altMTL vs complete)

Solution: $\theta$-cut = remove all pairs $< 0.05^\circ$

Fiber assignment

Pinon et al. 2024

New window matrix $W^\mathrm{cut}$; $\langle P_o(k) \rangle = W^\mathrm{cut}(k, k^\prime) P_t(k^\prime)$

Fiber collisions

Pinon et al. 2024

New window matrix $W^\mathrm{cut}$; $\langle P_o(k) \rangle = W^\mathrm{cut}(k, k^\prime) P_t(k^\prime)$

Very non diagonal: let's "rotate" it

Fiber collisions

Pinon et al. 2024

Systematic effects

Theoretical modelling (Maus et al. 2024ab, Lai et al. 2024, Noriega et al. 2024, Ramirez et al. 2024)
Galaxy-halo connection (Findlay et al. 2024)
Fiducial cosmology (Gsponer et al. 2024)
Fibre assignment (Pinon et al. 2024)
Inhomogeneities in the target selection (Zhao et al. 2024)
Spectroscopic redshift failures/uncertainties (Yu et al. 2024, Krowleski et al. 2024)
Covariance matrix: mock-based vs analytic (Forero-Sanchez et al. 2024, Alves et al. 2024, Rashkovetskyi et al. 2024)

Total systematic error = ⅖ of DR1 statistical uncertainty

no systematics detected

Full Shape (+ BAO) measurements

Observable: power spectrum monopole and quadrupole, post-reconstruction BAO
Model: Effective Field Theory
Covariance: mock-based
Systematic error: at the data vector level
Fitting range: $0.02 < k\, [h/\mathrm{Mpc}] < 0.2$
Fitting parameters:
- 7 nuisance parameters
- 5 $\Lambda$CDM parameters

External information

$\Omega_\mathrm{b} h^2$: BBN from Schöneberg 2024

$n_\mathrm{s} \sim \mathcal{G}(0.9649, 0.042^2)$: "$n_{\mathrm{s}10}$" $10\times$ wider than Planck posterior

Full Shape + BAO measurements

$\omega_\mathrm{b}$: BBN, $n_\mathrm{s} \sim \mathcal{G}(0.9649, 0.042^2)$

Full Shape + BAO measurements

$\omega_\mathrm{b}$: BBN, $n_\mathrm{s} \sim \mathcal{G}(0.9649, 0.042^2)$

Full Shape + BAO measurements

$\omega_\mathrm{b}$: BBN, $n_\mathrm{s} \sim \mathcal{G}(0.9649, 0.042^2)$

Full Shape + BAO measurements

$\omega_\mathrm{b}$: BBN, $n_\mathrm{s} \sim \mathcal{G}(0.9649, 0.042^2)$

Full Shape + BAO measurements

$\omega_\mathrm{b}$: BBN, $n_\mathrm{s} \sim \mathcal{G}(0.9649, 0.042^2)$

Full Shape + BAO measurements

$\omega_\mathrm{b}$: BBN, $n_\mathrm{s} \sim \mathcal{G}(0.9649, 0.042^2)$

Full Shape + BAO measurements

\underbrace{\begin{align*} \Omega_\mathrm{m} &= 0.2962\pm 0.0095 & \mathbf{(3.2\%)} \\ \sigma_8 &= 0.842\pm 0.034 & \mathbf{(4.0\%)} \\ H_0 &= (68.56\pm 0.75) \, {\rm km\,s^{-1}\,Mpc^{-1}} & \mathbf{(1.1\%)} \end{align*}}_{\textstyle \text{DESI + BBN + $n_{s10}$}}

$\omega_\mathrm{b}$: BBN, $n_\mathrm{s} \sim \mathcal{G}(0.9649, 0.042^2)$

$S_8$ constraints

\underbrace{ S_8 = 0.836 \pm 0.035 }_{\textstyle \text{\color{blue}{DESI + BBN + $n_{s10}$}}}

$S_8 = \sigma_8 (\Omega_\mathrm{m} / 0.3)^{0.5}$ best constrained by weak lensing surveys

$S_8$ constraints

Consistency with SDSS
In agreement with CMB

$S_8 = \sigma_8 (\Omega_\mathrm{m} / 0.3)^{0.5}$ best constrained by weak lensing surveys

\underbrace{ S_8 = 0.836 \pm 0.035 }_{\textstyle \text{\color{blue}{DESI + BBN + $n_{s10}$}}}

$S_8$ constraints

Consistency with SDSS
In agreement with CMB
Weak lensing prefers lower $S_8$, but still consistent

$S_8 = \sigma_8 (\Omega_\mathrm{m} / 0.3)^{0.5}$ best constrained by weak lensing surveys

\underbrace{ S_8 = 0.836 \pm 0.035 }_{\textstyle \text{\color{blue}{DESI + BBN + $n_{s10}$}}}

Dark Energy fluid, pressure $p$, density $\rho$

Equation of State parameter $w = p / \rho$

Linked to the evolution of Dark Energy $w(z) = -1 + \frac{1}{3}\frac{d \ln f_\mathrm{DE}(z)}{d \ln (1 + z)}$

Let's assume the CPL parameterization

w(z) = w_{0} + \frac{z}{1 + z} w_{a} \qquad \text{(CPL)}

Dynamical Dark Energy - $(w_{0}, w_{a})$

$\Lambda$CDM: $(w_0, w_a) = (-1, 0)$

Dynamical Dark Energy - $(w_{0}, w_{a})$

DESI + CMB + SN (uncalibrated):

Pantheon+ Scolnic, Brout, Carr et al. 2022; Brout, Scolnic, Popovic et al. 2022
Union3 Rubin, Aldering, Betoule et al. 2023
DES-SN5YR DES Collaboration et al. 2024

$\Lambda$CDM

Dynamical Dark Energy - $(w_{0}, w_{a})$

same preference for $w_{0} > -1, w_{a} < 0$
similar significance for $w_0w_a$CDM vs $\Lambda$CDM
$20\%$ better constraints in $(w_0, w_a)$ than without FS

$2.5\sigma$

$3.4\sigma$

$3.8\sigma$

Sum of neutrino masses

Massive neutrinos impact:

i) the expansion history

ii) the growth of structure: $ \Delta P(k)/P(k) \propto -\sum m_\nu / \omega_\mathrm{m} $

the $k$-fitting range

Sum of neutrino masses

Massive neutrinos impact:

i) the expansion history

ii) the growth of structure: $ \Delta P(k)/P(k) \propto -\sum m_\nu / \omega_\mathrm{m} $

Taking $n_\mathrm{s}$ prior from Planck:

\underbrace{ \sum m_\nu < 0.409 \, \mathrm{eV} \; (95\%) }_{\textstyle \text{\color{blue}{DESI + BBN + $n_\mathrm{s10}$}}}

\underbrace{ \sum m_\nu < 0.300 \, \mathrm{eV} \; (95\%) }_{\textstyle \text{\color{blue}{DESI + BBN + $n_\mathrm{s}$}}}

Sum of neutrino masses

Internal CMB degeneracies limiting precision on the sum of neutrino masses

Broken by DESI, especially through $H_{0}$

Sum of neutrino masses

Internal CMB degeneracies limiting precision on the sum of neutrino masses

Broken by DESI, especially through $H_{0}$

Low preferred value of $H_{0}$ yields

$\sum m_\nu < 0.071 \, \mathrm{eV} \; (95\%, \color{green}{\text{DESI + CMB})}$

($15\%$ better than BAO-only: $0.082 \, \mathrm{eV} $)

$\sum m_\nu < 0.081 \, \mathrm{eV} \; (95\%, \color{green}{\text{DESI + CMB[hillipop]})}$

In $w_0w_a\mathrm{CDM}$, with DES-SN5YR: $\sim 0.2\, \mathrm{eV} \; (95\%)$

Modified gravity constraints

In general relativity, $\green{\mu(a, k)} = \green{\Sigma(a, k)} = 1$

To test GR, introduce $\green{\mu_0, \Sigma_0}$

\mu(a) = 1 + \frac{\Omega_\Lambda(a)}{\Omega_\Lambda} \green{\mu_0}, \Sigma(a) = 1 + \frac{\Omega_\Lambda(a)}{\Omega_\Lambda} \green{\Sigma_0}

Perturbed FLRW metric

$ds^2=a(\tau)^2[-(1+2\orange{\Psi})d\tau^2+(1-2\orange{\Phi})\delta_{ij}dx^i dx^j]$

At late times:

(mass) $k^2\orange{\Psi} = -4\pi G a^2 \green{\mu(a,k)} \blue{\sum_i\rho_i\Delta_i}$

(light) $k^2(\orange{\Phi} + \orange{\Psi})=-8\pi G a^2 \green{\Sigma(a,k)} \blue{\sum_i\rho_i\Delta_i}$

gravitational potentials

density perturbations

Modified gravity constraints

\underbrace{ \mu_0 = 0.11^{+0.45}_{-0.54} }_{\textstyle \text{\color{blue}{DESI + BBN + $n_{\mathrm{s}10}$}}}

DESI constrains

Modified gravity constraints

$\Sigma_0$ constrained by

- CMB (ISW and lensing)

- galaxy lensing

\underbrace{ \mu_0 = 0.11^{+0.45}_{-0.54} }_{\textstyle \text{\color{blue}{DESI + BBN + $n_{\mathrm{s}10}$}}}

DESI constrains

Modified gravity constraints

$\Sigma_0$ constrained by

- CMB (ISW and lensing)

- galaxy lensing

\underbrace{\begin{align*} \mu_0 &= 0.04\pm 0.22 \\ \Sigma_0 &= 0.045\pm 0.046 \end{align*}}_{\textstyle \text{\color{purple}{DESI + CMB-nl + DESY3 ($3\times 2$-pt)}}}

\underbrace{ \mu_0 = 0.11^{+0.45}_{-0.54} }_{\textstyle \text{\color{blue}{DESI + BBN + $n_{\mathrm{s}10}$}}}

compared to CMB-nl + DESY3 (3x2pt) only: $\sigma(\mu_0) / 2.5$, $\sigma(\Sigma_0) / 2$

DESI constrains

Conclusions

BAO

- compared to Planck: low $\Omega_\mathrm{m}$, high $H_{0}$

- hint of dynamical dark energy (depending on SN dataset)

Adding Full Shape

- $\sigma_8, S_8$ consistent with Planck

- modified gravity $\mu_0$ parameter consistent with GR

- small improvements in $w_0, w_a$ and $\sum m_\nu$ constraints

What to do next?

DR2 data (Y3 > Y1) on disk, DR2 BAO analysis on-going... stay tuned!

DR2 analyses will include joint 2-pt, 3-pt measurements: new challenges!

Possible improvements to the current analyses:

- more / improved mocks

- faster cosmological inference with emulators / JAX

- simplify $P(k)$ and associated window measurements

$f_\mathrm{NL}^\mathrm{loc}$ - mock constraints

Chaussidon et al. 2024, in prep

DR1: $\sigma(f_\mathrm{NL}^\mathrm{loc}) \sim 10$

SDSS: $\sigma(f_\mathrm{NL}^\mathrm{loc}) \sim 20$

LRG

QSO

Successfully removes the $ > 1 \sigma$ bias

credit: Ruiyang Zhao

Fiber collisions

Pinon et al. 2024

Combined constraints

*DES and SPT collaborations 2022
6x2pt = galaxy-galaxy, galaxy-shear, shear-shear, galaxy-CMB lensing, shear-CMB lensing, CMB lensing-CMB lensing

Adding DESI to DESY3 6x2pt improves $\sigma_8$ and $\Omega_\mathrm{m}$ precision by $\times 2$ ($S_8$ by $20\%$)

Combined constraints

Adding DESI to DESY3 6x2pt improves $\sigma_8$ and $\Omega_\mathrm{m}$ precision by $\times 2$ ($S_8$ by $20\%$)
Adding DESI to CMB improves $\Omega_\mathrm{m}$, $H_{0}$ and $S_{8}$ precision by $30\%$

Combined constraints

Adding DESI to DESY3 6x2pt improves $\sigma_8$ and $\Omega_\mathrm{m}$ precision by $\times 2$ ($S_8$ by $20\%$)
Adding DESI to CMB improves $\Omega_\mathrm{m}$, $H_{0}$ and $S_{8}$ precision by $30\%$

\underbrace{\begin{align*} \Omega_\mathrm{m} &= 0.3009 \pm 0.0034 & \mathbf{(1\%)} \\ \sigma_8 &= 0.8028^{+0.0050}_{-0.0045} & \mathbf{(0.6\%)} \\ H_0 &= (68.40\pm 0.27) \, {\rm km\,s^{-1}\,Mpc^{-1}} & \mathbf{(0.4\%)} \end{align*}}_{\textstyle \text{\color{green}{DESI + DESY3 (6$\times$2pt) + CMB-nl}}}

Dynamical Dark Energy - $(\Omega_\mathrm{m}, \sigma_{8})$

($\Omega_\mathrm{m}, \sigma_{8})$ constraints remain stable when opening up to $w_0w_a\text{CDM}$

Dynamical Dark Energy - $(\Omega_\mathrm{m}, \sigma_{8})$

($\Omega_\mathrm{m}, \sigma_{8})$ constraints remain stable when opening up to $w_0w_a\text{CDM}$

SN (uncalibrated):

Pantheon+ Brout, Scolnic, Popovic et al., 2022
Union3 Rubin, Aldering, Betoule et al. 2023
DES-SN5YR DES Collaboration et al. 2024

Other datasets

SDSS (for comparisons only): eBOSS Collaboration, 2020
Primary CMB: Planck Collaboration, 2018
CMB lensing: Planck PR4 + ACT DR6 lensing ACT Collaboratio n, 2023, Carron, Mirmelstein, Lewis, 2022
BBN: Schöneberg 2024
SN: Pantheon+ Brout, Scolnic, Popovic et al. 2022, Union3 Rubin, Aldering, Betoule et al. 2023, DES-SN5YR DES Collaboration
DESY3 3x2pt DES collaboration 2021, 6x2pt DES and SPT collaborations 2022

DESI + CMB measurements favor a flat Universe

\Omega_\mathrm{K} = 0.0024 \pm 0.0016 \; \green{(\text{DESI} + \text{CMB})}

Spatial curvature

Dark Energy Equation of State

\underbrace{\begin{align*} \Omega_\mathrm{m} &= 0.293 \pm 0.015 & \mathbf{(5.1\%)} \\ w &= -0.99^{+0.15}_{-0.13} & \mathbf{(15\%)} \end{align*}}_{\textstyle \text{\color{darkblue}{DESI}}}

Constant EoS parameter $w = p / \rho$

\Lambda

Dark Energy Equation of State

\underbrace{\begin{align*} \Omega_\mathrm{m} &= 0.293 \pm 0.015 & \mathbf{(5.1\%)} \\ w &= -0.99^{+0.15}_{-0.13} & \mathbf{(15\%)} \end{align*}}_{\textstyle \text{\color{darkblue}{DESI}}}

Constant EoS parameter $w = p / \rho$

Dark Energy Equation of State

SNe (uncalibrated):

Pantheon+ Brout, Scolnic, Popovic et al., 2022

\underbrace{\begin{align*} \Omega_\mathrm{m} &= 0.293 \pm 0.015 & \mathbf{(5.1\%)} \\ w &= -0.99^{+0.15}_{-0.13} & \mathbf{(15\%)} \end{align*}}_{\textstyle \text{\color{darkblue}{DESI}}}

Constant EoS parameter $w = p / \rho$

Dark Energy Equation of State

SNe (uncalibrated):

Pantheon+ Brout, Scolnic, Popovic et al., 2022
Union3 Rubin, Aldering, Betoule et al. 2023

\underbrace{\begin{align*} \Omega_\mathrm{m} &= 0.293 \pm 0.015 & \mathbf{(5.1\%)} \\ w &= -0.99^{+0.15}_{-0.13} & \mathbf{(15\%)} \end{align*}}_{\textstyle \text{\color{darkblue}{DESI}}}

Constant EoS parameter $w = p / \rho$

Dark Energy Equation of State

SNe (uncalibrated):

Pantheon+ Brout, Scolnic, Popovic et al., 2022
Union3 Rubin, Aldering, Betoule et al. 2023
DES-SN5YR DES Collaboration et al. 2024

\underbrace{\begin{align*} \Omega_\mathrm{m} &= 0.293 \pm 0.015 & \mathbf{(5.1\%)} \\ w &= -0.99^{+0.15}_{-0.13} & \mathbf{(15\%)} \end{align*}}_{\textstyle \text{\color{darkblue}{DESI}}}

Constant EoS parameter $w = p / \rho$

Dark Energy Equation of State

\underbrace{\begin{align*} \Omega_\mathrm{m} &= 0.3095 \pm 0.0065 & \mathbf{(2.1\%)} \\ w &= -0.997 \pm 0.025 & \mathbf{(2.5\%)} \end{align*}}_{\textstyle \text{\color{orange}{DESI + CMB + Pantheon+}}}

Assuming a constant EoS, DESI BAO fully compatible with a cosmological constant...

\underbrace{\begin{align*} \Omega_\mathrm{m} &= 0.293 \pm 0.015 & \mathbf{(5.1\%)} \\ w &= -0.99^{+0.15}_{-0.13} & \mathbf{(15\%)} \end{align*}}_{\textstyle \text{\color{darkblue}{DESI}}}

Constant EoS parameter $w = p / \rho$

w(z) = w_{0} + \frac{z}{1 + z} w_{a} \qquad \text{(CPL)}

\left. \begin{align*} w_{0} &= -0.55^{+0.39}_{-0.21} \\ w_{a} &< -1.32 \end{align*} \right\rbrace {\text{\color{black}{DESI}}}

Dark Energy Equation of State

Varying EoS

\Lambda

Dark Energy Equation of State

\underbrace{ w_{0} = -0.45^{+0.34}_{-0.21} \qquad w_{a} = -1.79^{+0.48}_{-1.00} }_{\textstyle \purple{\text{DESI + CMB} \; \implies \; 2.6\sigma}}

Varying EoS

w(z) = w_{0} + \frac{z}{1 + z} w_{a} \qquad \text{(CPL)}

Dark Energy Equation of State

\underbrace{ w_{0} = -0.45^{+0.34}_{-0.21} \qquad w_{a} = -1.79^{+0.48}_{-1.00} }_{\textstyle \purple{\text{DESI + CMB} \; \implies \; 2.6\sigma}}

Varying EoS

w(z) = w_{0} + \frac{z}{1 + z} w_{a} \qquad \text{(CPL)}

Dark Energy Equation of State

\underbrace{ w_{0} = -0.45^{+0.34}_{-0.21} \qquad w_{a} = -1.79^{+0.48}_{-1.00} }_{\textstyle \purple{\text{DESI + CMB} \; \implies \; 2.6\sigma}}

Varying EoS

w(z) = w_{0} + \frac{z}{1 + z} w_{a} \qquad \text{(CPL)}

Dark Energy Equation of State

\underbrace{ w_{0} = -0.45^{+0.34}_{-0.21} \qquad w_{a} = -1.79^{+0.48}_{-1.00} }_{\textstyle \purple{\text{DESI + CMB} \; \implies \; 2.6\sigma}}

Varying EoS

w(z) = w_{0} + \frac{z}{1 + z} w_{a} \qquad \text{(CPL)}

Dark Energy Equation of State

Combining all DESI + CMB + SN

\underbrace{ w_{0} = -0.827 \pm 0.063 \qquad w_{a} = -0.75^{+0.29}_{-0.25} }_{\textstyle \blue{\text{DESI + CMB + Pantheon+} \; \implies \; 2.5\sigma}}

Dark Energy Equation of State

Combining all DESI + CMB + SN

\underbrace{ w_{0} = -0.827 \pm 0.063 \qquad w_{a} = -0.75^{+0.29}_{-0.25} }_{\textstyle \blue{\text{DESI + CMB + Pantheon+} \; \implies \; 2.5\sigma}}

\underbrace{ w_{0} = -0.64 \pm 0.11\qquad w_{a} = -1.27^{+0.40}_{-0.34} }_{\textstyle \color{orange}{\text{DESI + CMB + Union3} \; \implies \; 3.5\sigma}}

Dark Energy Equation of State

Combining all DESI + CMB + SN

\underbrace{ w_{0} = -0.827 \pm 0.063 \qquad w_{a} = -0.75^{+0.29}_{-0.25} }_{\textstyle \blue{\text{DESI + CMB + Pantheon+} \; \implies \; 2.5\sigma}}

\underbrace{ w_{0} = -0.64 \pm 0.11\qquad w_{a} = -1.27^{+0.40}_{-0.34} }_{\textstyle \color{orange}{\text{DESI + CMB + Union3} \; \implies \; 3.5\sigma}}

\underbrace{ w_{0} = -0.727 \pm 0.067 \qquad w_{a} = -1.05^{+0.31}_{-0.27} }_{\textstyle \color{green}{\text{DESI + CMB + DES-SN5YR} \; \implies \; 3.9\sigma}}

Dark Energy Equation of State

Combining all DESI + CMB + SN

$w_{0} > -1, w_{a} < 0$ favored, level varying on the SN dataset

\underbrace{ w_{0} = -0.827 \pm 0.063 \qquad w_{a} = -0.75^{+0.29}_{-0.25} }_{\textstyle \blue{\text{DESI + CMB + Pantheon+} \; \implies \; 2.5\sigma}}

\underbrace{ w_{0} = -0.64 \pm 0.11\qquad w_{a} = -1.27^{+0.40}_{-0.34} }_{\textstyle \color{orange}{\text{DESI + CMB + Union3} \; \implies \; 3.5\sigma}}

\underbrace{ w_{0} = -0.727 \pm 0.067 \qquad w_{a} = -1.05^{+0.31}_{-0.27} }_{\textstyle \color{green}{\text{DESI + CMB + DES-SN5YR} \; \implies \; 3.9\sigma}}

Sum of neutrino masses

Internal CMB degeneracies limiting precision on the sum of neutrino masses

Sum of neutrino masses

Internal CMB degeneracies limiting precision on the sum of neutrino masses

Broken by BAO, especially through $H_{0}$

Low preferred value of $H_{0}$ yields

$\sum m_\nu < 0.072 \, \mathrm{eV} \; (95\%, \color{green}{\text{DESI + CMB})}$

Limit relaxed for extensions to $\Lambda\mathrm{CDM}$

$\sum m_\nu < 0.195 \, \mathrm{eV}$ for $w_0w_a\mathrm{CDM}$

Neutrino mass hierarchies

\sum m_\nu < 0.113 \, \mathrm{eV} \; (95\%, \color{green}{\text{DESI + CMB})}

With $> 0.059 \, \mathrm{eV}$ prior (NH)

Neutrino mass hierarchies

\sum m_\nu < 0.113 \, \mathrm{eV} \; (95\%, \color{green}{\text{DESI + CMB})}

\sum m_\nu < 0.145 \, \mathrm{eV} \; (95\%, \color{green}{\text{DESI + CMB})}

With $> 0.059 \, \mathrm{eV}$ prior (NH)

With $> 0.1 \, \mathrm{eV}$ prior (IH)

Neutrino mass hierarchies

\sum m_\nu < 0.113 \, \mathrm{eV} \; (95\%, \color{green}{\text{DESI + CMB})}

\sum m_\nu < 0.145 \, \mathrm{eV} \; (95\%, \color{green}{\text{DESI + CMB})}

With $> 0.059 \, \mathrm{eV}$ prior (NH)

With $> 0.1 \, \mathrm{eV}$ prior (IH)

Current constraints do not strongly favor normal over inverted hierarchy ($\simeq 2 \sigma$)

Summary

DESI already has the most precise BAO measurements ever

Summary

DESI already has the most precise BAO measurements ever

DESI BAO is consistent (at the $\sim 1.9\sigma$ level) with CMB in flat ΛCDM

Summary

DESI already has the most precise BAO measurements ever

DESI BAO is consistent (at the $\sim 1.9\sigma$ level) with CMB in flat ΛCDM

In flat ΛCDM, DESI prefers "small $\Omega_\mathrm{m}$, large $H_0$ (though $3.7\sigma$ away from SH0ES), small $\sum m_\nu$"

Summary

DESI already has the most precise BAO measurements ever

DESI BAO is consistent (at the $\sim 1.9\sigma$ level) with CMB in flat ΛCDM

In flat ΛCDM, DESI prefers "small $\Omega_\mathrm{m}$, large $H_0$ (though $3.7\sigma$ away from SH0ES), small $\sum m_\nu$"

Some hint of time-varying Dark Energy equation of state especially when combined with supernovae measurements

DESI data release 1 (DR1)

5.7 million unique redshifts at z < 2.1 and > 420,000 Ly$\alpha$ QSO at z > 2.1

DESI Y5 forecasts

Survey Validation (arXiv:2306.06307)

BAO and RSD constraints at the end of the survey ($ \Delta z = 0.1 $)

Ly$\alpha$

DESI Y5 forecasts

Survey Validation (arXiv:2306.06307)

BAO and RSD constraints at the end of the survey ($ \Delta z = 0.1 $)

Ly$\alpha$

(w/ Planck)

Power spectra

Power spectra

BAO wiggles

Density field reconstruction

DESI DR1 Ly$\alpha$ BAO analysis

Biggest ever Ly$\alpha$ dataset ($N_\mathrm{tracer}$)
First blind analysis to mitigate observer / confirmation biases (correlation function-level blinding)
Modelling of the correlation function:
- cosmo signal

P_{\mathrm{Ly}\alpha}(k, \mu) = \blue{b^{2} (1 + \beta \mu^2)^2} \orange{P_\mathrm{lin}(k, \mu)} \green{F_\mathrm{NL}(k, \mu)}

linear bias + RSD

hydro-sim

BAO

\mu = r_\parallel / \sqrt{r_\parallel^2 + r_\perp^2}

DESI DR1 Ly$\alpha$ BAO analysis

Biggest ever Ly$\alpha$ dataset ($N_\mathrm{tracer}$)
First blind analysis to mitigate observer / confirmation biases (correlation function-level blinding)
Modelling of the correlation function:
- cosmo signal
- high-column density
- metal absorbers

r_\parallel \propto \left\vert\frac{1}{\lambda_{\mathrm{Ly}\alpha}} - \frac{1}{\lambda_{\mathrm{metal}}}\right\vert

SiII

DESI DR1 Ly$\alpha$ BAO analysis

Biggest ever Ly$\alpha$ dataset ($N_\mathrm{tracer}$)
First blind analysis to mitigate observer / confirmation biases (correlation function-level blinding)
Modelling of the correlation function:
- cosmo signal
- high-column density
- metal absorbers
- correlated noise (sky subtraction)

DESI DR1 Ly$\alpha$ BAO analysis

Biggest ever Ly$\alpha$ dataset ($N_\mathrm{tracer}$)
First blind analysis to mitigate observer / confirmation biases (correlation function-level blinding)
Modelling of the correlation function:
- cosmo signal
- high-column density
- metal absorbers
- correlated noise (sky subtraction)

DESI DR1 Ly$\alpha$ BAO analysis

Biggest ever Ly$\alpha$ dataset ($N_\mathrm{tracer}$)
First blind analysis to mitigate observer / confirmation biases (correlation function-level blinding)
Modelling of the correlation function

physical model fit

+ broadband polynomial

broadband: $< 0.1\sigma$

DESI DR1 Ly$\alpha$ BAO analysis

Biggest ever Ly$\alpha$ dataset ($N_\mathrm{tracer}$)
First blind analysis to mitigate observer / confirmation biases (correlation function-level blinding)
Modelling of the correlation function
Covariance matrix

Correlation matrix

smoothed jackknife, validated with mocks

Tests of systematic errors

tests with same dataset (not red): shifts $< \sigma_\mathrm{stat}/3$

tests with varying datasets (red): shifts consistent with stat.

Tests of systematic errors

DESI DR1 BAO analysis

Biggest ever spectroscopic BAO dataset ($N_\mathrm{tracer}$ and $V$)
Blind analysis to mitigate observer / confirmation biases (catalog-level blinding)

(\mathrm{R.A.}, \mathrm{Dec.}, z) \Longrightarrow (x, y, z) \Longrightarrow (\mathrm{R.A.}^\prime, \mathrm{Dec.}^\prime, z^\prime)

fiducial cosmology

blinded cosmology ($\Omega_\mathrm{m}, w_0, w_a$)

(random & unknown)

+ RSD blinding: change reconstructed peculiar velocities

+ $f_\mathrm{NL}$ blinding: add clustering-dependent signal on large scales with weights

DESI DR1 BAO analysis

Biggest ever spectroscopic BAO dataset ($N_\mathrm{tracer}$ and $V$)
Blind analysis to mitigate observer / confirmation biases (catalog-level blinding)
Theory developments in BAO fitting code

P_\mathrm{gg}(k, \mu) = \mathcal{B}(k, \mu) P_\mathrm{nw}(k) + \mathcal{C}(k, \mu) P_\mathrm{w}(k) + \orange{\mathcal{D}(k, \mu)}

Chen, Howlett et al. 2024

Some fits: Fourier space

$\sum m_\nu$

credit: Christophe Yèche

$w(z)$

DESI - SDSS consistency ($\Omega_\mathrm{m}$)

Perfectly consistent!

Using these 2 points alone moves $\Omega_\mathrm{m}$ by $< 2 \sigma$

Are SN $\Omega_\mathrm{m}$ consistent?

Not so much in flat $\Lambda\mathrm{CDM}$...

(so we do not combine them in this model!)

Are SN $\Omega_\mathrm{m}$ consistent?

Consistent in $w_0w_a\mathrm{CDM}$!

plik vs PR4 Planck likelihoods

Appendix B

$w_0 - w_a$ with $\sum m_\nu$ free

$w_0 - w_a$ with $\Omega_\mathrm{K}$

Preference for $w_{0} > -1, w_{a} < 0$ persists when curvature is left free

DE constraints driven by low-$z$ ?

Not that much!

DESI + SDSS swaps DESI measurements with SDSS for $z < 0.6$

$- 0.4 \sigma$ compared to DESI only

$w(z)$

Dark energy equation of state:

$P = w \rho$

$w$ = constant

BAO measurements: dark energy

Dark energy equation of state:

$P = w \rho$

CPL parameterization: $w(a) = w_0 + (1 - a) w_a$

DESI 2024: Survey overview and cosmological constraints from DR1 BAO and Full Shape measurements

DESI 3D Map

DESI 3D Map

DESI: a stage IV survey

DESI Y5 galaxy samples

From images to redshifts

Mayall Telescope

Mayall Telescope

Focal plane: 5000 robotic positioners

Focal plane: 5000 robotic positioners

Spectroscopic pipeline

DESI data release 1 (DR1)

Release of DESI DR1 (BAO) results

Release of DESI DR1 (FS) results

Clustering analysis

Baryon acoustic oscillations

BAO measurements

BAO measurements

BAO measurements

Release of DESI DR1 (BAO) results

Correlation functions

Power spectra

Some fits: correlation function

Density field reconstruction

Density field reconstruction

DR1 BAO analysis: what's new?

DR1 BAO analysis: what's new?

Tests of systematic errors

Release of DESI DR1 (BAO) results

Ly\(\alpha\) forest

Ly\(\alpha\) correlation functions in DESI DR1

DR1 Ly\(\alpha\) BAO analysis: what's new?

DR1 Ly\(\alpha\) BAO analysis: what's new?

DR1 Ly\(\alpha\) BAO analysis: what's new?

BAO measurements

DESI DR1 BAO

DESI DR1 BAO

DESI DR1 BAO

DESI DR1 BAO

DESI DR1 BAO

DESI DR1 BAO

DESI DR1 BAO

Consistency with other probes

Consistency with other probes

Consistency with other probes

Hubble constant

Hubble constant

Hubble constant

Hubble constant

Release of DESI DR1 (FS) results

Full Shape measurements

Full Shape measurements

Full Shape models

Full Shape models

DR1 Full Shape analysis: what's new?

Fiber assignment

Fiber assignment

Fiber assignment

Fiber collisions

Fiber collisions

Systematic effects

Full Shape (+ BAO) measurements

Full Shape + BAO measurements

Full Shape + BAO measurements

Full Shape + BAO measurements

Full Shape + BAO measurements

Full Shape + BAO measurements

Full Shape + BAO measurements

Full Shape + BAO measurements

\(S_8\) constraints

\(S_8\) constraints

\(S_8\) constraints

Dynamical Dark Energy - \((w_{0}, w_{a})\)

Dynamical Dark Energy - \((w_{0}, w_{a})\)

Dynamical Dark Energy - \((w_{0}, w_{a})\)

Sum of neutrino masses

Sum of neutrino masses

Sum of neutrino masses

Sum of neutrino masses

Modified gravity constraints