About

Scott Dodelson is a Professor of Physics at Carnegie Mellon University, affiliated with the Department of Physics within the Mellon College of Science. He earned his Ph.D. from Columbia University in 1988 and has held various academic and research positions, including Professor of Physics at Carnegie Mellon since 2017 and Head of the Physics Department there. He has also been a Distinguished Scientist at Fermi National Accelerator Laboratory, where he served in multiple roles including Head of Theoretical Astrophysics and Interim Director of the Center for Particle Astrophysics. Additionally, he has held faculty positions at the University of Chicago and Northwestern University. His research interests focus on understanding fundamental physics through the analysis of data from cosmic surveys. He is involved in exploring the cosmological model, which requires new physics such as dark matter, dark energy, and inflation. Dodelson aims to extract information from increasingly sensitive surveys to investigate questions about the nature of dark matter, the vacuum energy of dark energy, and the occurrence of inflation, as well as its connection to known fields. He serves as co-chair of the Science Committee for the Dark Energy Survey, participates in the LSST Dark Energy Science Collaboration, and works with data from the South Pole Telescope. His work involves understanding observational data, phenomenological modeling, and exploring theoretical alternatives to current cosmological paradigms.

Research topics

• Physics
• Astronomy
• Astrophysics
• Chemistry
• Psychology

Selected publications

• Dark Energy Survey Year 3: Blue shear

  Physical review. D/Physical review. D. · 2026-02-17 · 7 citations

  preprintOpen access

  Modeling the intrinsic alignment (IA) of galaxies poses a challenge to weak lensing analyses. The Dark Energy Survey is expected to be less impacted by IA when limited to blue, star-forming galaxies. The cosmological parameter constraints from this blue cosmic shear sample are stable to IA model choice, unlike passive galaxies in the full DES Y3 sample, the goodness-of-fit is improved and the $Ω_{m}$ and $S_8$ better agree with the cosmic microwave background. Mitigating IA with sample selection, instead of flexible model choices, can reduce uncertainty in $S_8$ by a factor of 1.5.

  PublisherOA PDFDOI

• Brightest Cluster Galaxy ellipticity as proxy for halo shape: Orientation bias, assembly bias, and potential selection effects in SZ-selected clusters

  HAL (Le Centre pour la Communication Scientifique Directe) · 2026-03-24

  preprintOpen access

  The orientation of triaxial galaxy clusters with respect to the line-of-sight is expected to be one of the prime sources of scatter and potential bias in optical observables (e.g., richness and weak-lensing signal) of galaxy clusters. In this work, we use the observed shape of the central Brightest Cluster Galaxy (BCG) as proxy for the orientation along the line-of-sight for clusters selected via the Sunyaev-Zel'dovich (SZ) effect from the South Pole Telescope (SPT) and Atacama Cosmology Telescope (ACT) surveys, matched to optically selected clusters from the Dark Energy Survey Year 3 (DES). We construct two samples of clusters that are designed to be identical in SZ mass estimate and redshift but with the roundest vs. the most elliptical BCGs, which we expect to correspond to BCGs (and clusters) with major axes aligned along the line-of-sight vs. in the plane of the sky, respectively. We find that the optical richness of round-BCG clusters is $\sim 10$\% larger than that of elliptical-BCG clusters, in agreement with the expectation from projection effects and presenting the first such detection in data. The density profiles, however, are not in agreement with the expectation from projection effects: the 1-halo term (below $6~h^{-1}\rm{Mpc}$) of both the weak-lensing and galaxy density profiles are the same for the subsamples, contrary to previous studies based on X-ray selected clusters. In the 2-halo regime (above $6~h^{-1}\rm{Mpc}$), we find a significant excess of the elliptical-BCG cluster profiles compared to the round-BCG cluster profiles, which is the opposite of the expectation from numerical simulations. We hypothesize that the intrinsic shape of the BCG reflects not just the orientation angle, but also intrinsic properties of the cluster which can affect both the SZ signal and the amplitude of the 2-halo term.

  PublisherOA PDFDOI

• Constraining the Stellar-to-Halo Mass Relation with Galaxy Clustering and Weak Lensing from DES Year 3 Data

  The Open Journal of Astrophysics · 2026-01-08

  articleOpen access

  We develop a framework to study the relation between the stellar mass of a galaxy and the total mass of its host dark matter halo using galaxy clustering and galaxy-galaxy lensing measurements. We model a wide range of scales, roughly from to , using a theoretical framework based on the Halo Occupation Distribution and data from Year 3 of the Dark Energy Survey (DES) dataset. The new advances of this work include: 1) the generation and validation of a new stellar mass-selected galaxy sample in the range of <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"> <mml:mrow> <mml:mo>log</mml:mo> <mml:msub> <mml:mi>M</mml:mi> <mml:mo>⋆</mml:mo> </mml:msub> <mml:mi>/</mml:mi> <mml:msub> <mml:mi>M</mml:mi> <mml:mo>⊙</mml:mo> </mml:msub> <mml:mo>∼</mml:mo> <mml:mn>9.6</mml:mn> </mml:mrow> </mml:math> to <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"> <mml:mrow> <mml:mo>∼</mml:mo> <mml:mn>11.5</mml:mn> </mml:mrow> </mml:math> ; 2) the joint-modeling framework of galaxy clustering and galaxy-galaxy lensing that is able to describe our stellar mass-selected sample deep into the 1-halo regime; and 3) stellar-to-halo mass relation (SHMR) constraints from this dataset. In general, our SHMR constraints agree well with existing literature with various weak lensing measurements. We constrain the free parameters in the SHMR functional form <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"> <mml:mrow> <mml:mo>log</mml:mo> <mml:msub> <mml:mi>M</mml:mi> <mml:mo>⋆</mml:mo> </mml:msub> <mml:mrow> <mml:mo stretchy="true" form="prefix">(</mml:mo> <mml:msub> <mml:mi>M</mml:mi> <mml:mi>h</mml:mi> </mml:msub> <mml:mo stretchy="true" form="postfix">)</mml:mo> </mml:mrow> <mml:mo>=</mml:mo> <mml:mo>log</mml:mo> <mml:mrow> <mml:mo stretchy="true" form="prefix">(</mml:mo> <mml:mi>ϵ</mml:mi> <mml:msub> <mml:mi>M</mml:mi> <mml:mn>1</mml:mn> </mml:msub> <mml:mo stretchy="true" form="postfix">)</mml:mo> </mml:mrow> <mml:mo>+</mml:mo> <mml:mi>f</mml:mi> <mml:mrow> <mml:mo stretchy="true" form="prefix">[</mml:mo> <mml:mo>log</mml:mo> <mml:mrow> <mml:mo stretchy="true" form="prefix">(</mml:mo> <mml:msub> <mml:mi>M</mml:mi> <mml:mi>h</mml:mi> </mml:msub> <mml:mi>/</mml:mi> <mml:msub> <mml:mi>M</mml:mi> <mml:mn>1</mml:mn> </mml:msub> <mml:mo stretchy="true" form="postfix">)</mml:mo> </mml:mrow> <mml:mo stretchy="true" form="postfix">]</mml:mo> </mml:mrow> <mml:mo>−</mml:mo> <mml:mi>f</mml:mi> <mml:mrow> <mml:mo stretchy="true" form="prefix">(</mml:mo> <mml:mn>0</mml:mn> <mml:mo stretchy="true" form="postfix">)</mml:mo> </mml:mrow> </mml:mrow> </mml:math> , with <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"> <mml:mrow> <mml:mi>f</mml:mi> <mml:mrow> <mml:mo stretchy="true" form="prefix">(</mml:mo> <mml:mi>x</mml:mi> <mml:mo stretchy="true" form="postfix">)</mml:mo> </mml:mrow> <mml:mo>≡</mml:mo> <mml:mo>−</mml:mo> <mml:mo>log</mml:mo> <mml:mrow> <mml:mo stretchy="true" form="prefix">(</mml:mo> <mml:msup> <mml:mn>10</mml:mn> <mml:mrow> <mml:mi>α</mml:mi> <mml:mi>x</mml:mi> </mml:mrow> </mml:msup> <mml:mo>+</mml:mo> <mml:mn>1</mml:mn> <mml:mo stretchy="true" form="postfix">)</mml:mo> </mml:mrow> <mml:mo>+</mml:mo> <mml:mi>δ</mml:mi> <mml:msup> <mml:mrow> <mml:mo stretchy="true" form="prefix">[</mml:mo> <mml:mo>log</mml:mo> <mml:mrow> <mml:mo stretchy="true" form="prefix">(</mml:mo> <mml:mn>1</mml:mn> <mml:mo>+</mml:mo> <mml:mo>exp</mml:mo> <mml:mrow> <mml:mo stretchy="true" form="prefix">(</mml:mo> <mml:mi>x</mml:mi> <mml:mo stretchy="true" form="postfix">)</mml:mo> </mml:mrow> <mml:mo stretchy="true" form="postfix">)</mml:mo> </mml:mrow> <mml:mo stretchy="true" form="postfix">]</mml:mo> </mml:mrow> <mml:mi>γ</mml:mi> </mml:msup> <mml:mi>/</mml:mi> <mml:mrow> <mml:mo stretchy="true" form="prefix">[</mml:mo> <mml:mn>1</mml:mn> <mml:mo>+</mml:mo> <mml:mo>exp</mml:mo> <mml:mrow> <mml:mo stretchy="true" form="prefix">(</mml:mo> <mml:msup> <mml:mn>10</mml:mn> <mml:mrow> <mml:mo>−</mml:mo> <mml:mi>x</mml:mi> </mml:mrow> </mml:msup> <mml:mo stretchy="true" form="postfix">)</mml:mo> </mml:mrow> <mml:mo stretchy="true" form="postfix">]</mml:mo> </mml:mrow> </mml:mrow> </mml:math> , to be <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"> <mml:mrow> <mml:mo>log</mml:mo> <mml:msub> <mml:mi>M</mml:mi> <mml:mn>1</mml:mn> </mml:msub> <mml:mo>=</mml:mo> <mml:msubsup> <mml:mn>11.506</mml:mn> <mml:mrow> <mml:mo>−</mml:mo> <mml:mn>0.404</mml:mn> </mml:mrow> <mml:mrow> <mml:mo>+</mml:mo> <mml:mn>0.325</mml:mn> </mml:mrow> </mml:msubsup> </mml:mrow> </mml:math> , <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"> <mml:mrow> <mml:mo>log</mml:mo> <mml:mi>ϵ</mml:mi> <mml:mo>=</mml:mo> <mml:mo>−</mml:mo> <mml:msubsup> <mml:mn>1.632</mml:mn> <mml:mrow> <mml:mo>−</mml:mo> <mml:mn>0.181</mml:mn> </mml:mrow> <mml:mrow> <mml:mo>+</mml:mo> <mml:mn>0.306</mml:mn> </mml:mrow> </mml:msubsup> </mml:mrow> </mml:math> , <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"> <mml:mrow> <mml:mi>α

  PublisherDOI

• Dark Energy Survey: Implications for cosmological expansion models from the final DES baryon acoustic oscillation and supernova data

  Physical review. D/Physical review. D. · 2026-01-30 · 6 citations

  article

  International audience

  PublisherDOI

• The Dark Energy Survey supernova program: a reanalysis of cosmology results and evidence for evolving dark energy with an updated Type Ia supernova calibration

  Monthly Notices of the Royal Astronomical Society · 2026-04-01 · 2 citations

  preprintOpen access

  ABSTRACT We present improved cosmological constraints from a re-analysis of the Dark Energy Survey (DES) 5-year sample of Type Ia supernovae (DES-SN5YR). This re-analysis includes an improved photometric cross-calibration, recent white dwarf observations to cross-calibrate between DES and low-redshift surveys, retraining the salt3 light-curve model and fixing a numerical approximation in the host-galaxy colour law. Our fully recalibrated sample, which we call DES-Dovekie, comprises $\sim$1600 likely Type Ia SNe from DES and $\sim$200 low-redshift SNe from other surveys. With DES-Dovekie, we obtain $\Omega _{\rm m} = 0.330 \pm 0.015$ in flat Lambda-cold dark matter ($\Lambda$CDM) which changes $\Omega _{\rm m}$ by $-0.022$ compared to DES-SN5YR. Combining DES-Dovekie with cosmic microwave background data from Planck, Atacama Cosmology Telescope, and South Pole Telescope and the DESI DR2 measurements in a flat $w_0 w_a$CDM cosmology, we find $w_0 = -0.803 \pm 0.054$ and $w_a = -0.72 \pm 0.21$. Our results hold a significance of $3.2\sigma$, reduced from $4.2\sigma$ for DES-SN5YR, to reject the null hypothesis that the data are compatible with the cosmological constant. This significance is equivalent to a Bayesian model preference odds of approximately 5:1 in favour of the flat $w_0 w_a$CDM model. Using generally accepted thresholds for model preference, our updated data exhibits only a weak preference for evolving dark energy.

  PublisherDOI

• Dark Energy Survey Year 3 results: Simulation-based <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"> <mml:mrow> <mml:mi>w</mml:mi> <mml:mi>CDM</mml:mi> </mml:mrow> </mml:math> inference from weak lensing and galaxy clustering maps with deep learning: Analysis design

  Physical review. D/Physical review. D. · 2026-02-17

  preprintOpen access

  Data-driven approaches using deep learning are emerging as powerful techniques to extract non-Gaussian information from cosmological large-scale structure. This work presents the first simulation-based inference (SBI) pipeline that combines weak lensing and galaxy clustering maps in a realistic Dark Energy Survey Year 3 (DES Y3) configuration and serves as preparation for a forthcoming analysis of the survey data. We develop a scalable forward model based on the 1 suite of <a:math xmlns:a="http://www.w3.org/1998/Math/MathML" display="inline"> <a:mi>N</a:mi> </a:math> -body simulations to generate over one million self-consistent mock realizations of DES Y3 at the map level. Leveraging this large dataset, we train deep graph convolutional neural networks on the full survey footprint in spherical geometry to learn low-dimensional features that approximately maximize mutual information with target parameters. These learned compressions enable neural density estimation of the implicit likelihood via normalizing flows in a ten-dimensional parameter space spanning cosmological <c:math xmlns:c="http://www.w3.org/1998/Math/MathML" display="inline"> <c:mi>w</c:mi> </c:math> CDM, intrinsic alignment, and linear galaxy bias parameters, while marginalizing over baryonic, photometric redshift, and shear bias nuisances. To ensure robustness, we extensively validate our inference pipeline using synthetic observations derived from both systematic contaminations in our forward model and independent galaxy catalogs. Our forecasts yield significant improvements in cosmological parameter constraints, achieving <e:math xmlns:e="http://www.w3.org/1998/Math/MathML" display="inline"> <e:mn>2</e:mn> <e:mi>–</e:mi> <e:mn>3</e:mn> <e:mo>×</e:mo> </e:math> higher figures of merit in the <g:math xmlns:g="http://www.w3.org/1998/Math/MathML" display="inline"> <g:msub> <g:mi mathvariant="normal">Ω</g:mi> <g:mi>m</g:mi> </g:msub> <g:mtext>−</g:mtext> <g:msub> <g:mi>S</g:mi> <g:mn>8</g:mn> </g:msub> </g:math> plane relative to our implementation of baseline two-point statistics and effectively breaking parameter degeneracies through probe combination. These results demonstrate the potential of SBI analyses powered by deep learning for upcoming stage-IV wide-field imaging surveys.

  PublisherDOI

• Testing the Standard Cosmological Model: Late-Universe Constraints on the Clustering of Matter with Early-Universe Priors

  Knowledge@UChicago (University of Chicago) · 2026-01-01

  otherOpen accessSenior author

  The Standard Cosmological Model (ΛCDM) successfully predicts a series of observations, but it has tensions when the model parameters are constrained using different observational probes. The s8 tension is a disagreement in the level of clustering of matter (“clumpiness” of the universe) between early-time, Cosmic Microwave Background (CMB) and late-time galactic surveys; the latter measure less clustering today than suggested by CMB surveys at the 2-3σ level, making it a significant puzzle in cosmology. Here, this tension is addressed using the final data release of the Dark Energy Survey. Bayesian parameter inference with CosmoSIS is employed but enforcing informative CMB priors. We ask: does feeding early-universe informed priors in our inference with late universe data worsen or alleviate the s8 tension? The answer will help discern whether the tension originates from systematics in the data or if physics beyond ΛCDM is needed.

  PublisherOA PDFDOI

• Biasing from galaxy trough and peak profiles with the DES Y3 redMaGiC galaxies and the weak lensing mass map

  Monthly Notices of the Royal Astronomical Society · 2026-01-05

  preprintOpen access

  ABSTRACT We measure the correspondence between the distribution of galaxies and matter around troughs and peaks in the projected galaxy density, by comparing redMaGiC galaxies ($0.15&amp;lt; z&amp;lt;0.65$) to weak lensing mass maps from the Dark Energy Survey (DES) Y3 data release. We obtain stacked profiles, as a function of angle $\theta$, of the galaxy density contrast $\delta _{\rm g}$ and the weak lensing convergence $\kappa$, in the vicinity of these identified troughs and peaks, referred to as ‘void’ and ‘cluster’ superstructures. The ratio of the profiles depend mildly on $\theta$, indicating good consistency between the profile shapes. We model the amplitude of this ratio using a function $F(\boldsymbol{\eta }, \theta)$ that depends on cosmological parameters $\boldsymbol{\eta }$, scaled by the galaxy bias. We construct templates of $F(\boldsymbol{\eta }, \theta)$ using a suite of N-body (Gower Street) simulations forward-modelled with DES Y3-like noise and systematics. We discuss and quantify the caveats of using a linear bias model to create galaxy maps from the simulation dark matter shells. We measure the galaxy bias in three lens tomographic bins (near to far): $2.32^{+0.86}_{-0.27}, 2.18^{+0.86}_{-0.23}, 1.86^{+0.82}_{-0.23}$ for voids, and $2.46^{+0.73}_{-0.27}, 3.55^{+0.96}_{-0.55}, 4.27^{+0.36}_{-1.14}$ for clusters, assuming the best-fitting Planck cosmology. Similar values with $\sim 0.1\sigma$ shifts are obtained assuming the mean DES Y3 cosmology. The biases from troughs and peaks are broadly consistent, although a larger bias is derived for peaks, which is also larger than those measured from the DES Y3 $3\times 2$-point analysis. This method shows an interesting avenue for measuring field-level bias that can be applied to future lensing surveys.

  PublisherOA PDFDOI

• Brightest Cluster Galaxy ellipticity as proxy for halo shape: Orientation bias, assembly bias, and potential selection effects in SZ-selected clusters

  ArXiv.org · 2026-03-24

  articleOpen access

  The orientation of triaxial galaxy clusters with respect to the line-of-sight is expected to be one of the prime sources of scatter and potential bias in optical observables (e.g., richness and weak-lensing signal) of galaxy clusters. In this work, we use the observed shape of the central Brightest Cluster Galaxy (BCG) as proxy for the orientation along the line-of-sight for clusters selected via the Sunyaev-Zel'dovich (SZ) effect from the South Pole Telescope (SPT) and Atacama Cosmology Telescope (ACT) surveys, matched to optically selected clusters from the Dark Energy Survey Year 3 (DES). We construct two samples of clusters that are designed to be identical in SZ mass estimate and redshift but with the roundest vs. the most elliptical BCGs, which we expect to correspond to BCGs (and clusters) with major axes aligned along the line-of-sight vs. in the plane of the sky, respectively. We find that the optical richness of round-BCG clusters is $\sim 10$\% larger than that of elliptical-BCG clusters, in agreement with the expectation from projection effects and presenting the first such detection in data. The density profiles, however, are not in agreement with the expectation from projection effects: the 1-halo term (below $6~h^{-1}\rm{Mpc}$) of both the weak-lensing and galaxy density profiles are the same for the subsamples, contrary to previous studies based on X-ray selected clusters. In the 2-halo regime (above $6~h^{-1}\rm{Mpc}$), we find a significant excess of the elliptical-BCG cluster profiles compared to the round-BCG cluster profiles, which is the opposite of the expectation from numerical simulations. We hypothesize that the intrinsic shape of the BCG reflects not just the orientation angle, but also intrinsic properties of the cluster which can affect both the SZ signal and the amplitude of the 2-halo term.

  PublisherOA PDF

• AI Has Striking Science Skills, but Grad Students Are Still Wanted

  Physics · 2026-05-21

  articleOpen access1st authorCorresponding
  PublisherOA PDFDOI

Recent grants

• AI Institute: Planning: Physics of the Future

  NSF · $750k · 2020–2023

• Precision Measures of the Dark Sector

  NSF · $191k · 2009–2012

Frequent coauthors

• A. Carnero Rosell

  375 shared

• D. Gruen

  340 shared

• L. N. da Costa

  Laboratório Interinstitucional de e-Astronomia

  334 shared

• E. Bertin

  Orange (France)

  302 shared

• A. Roodman

  SLAC National Accelerator Laboratory

  284 shared

• M. Carrasco Kind

  Urbana University

  272 shared

• K. Kuehn

  Netherlands Institute for Radio Astronomy

  262 shared

• R. Miquel

  Institute for High Energy Physics

  260 shared

Education

• Ph.D.

  Columbia University

  1988

• Other

  Harvard University

  1991

• Other

  Fermi National Accelerator Laboratory

  1994

• Other

  Fermi National Accelerator Laboratory

  1999

• Other

  Dept. of Physics and Astronomy, Northwestern University

  2004

• Other

  Dept. of Astronomy and Astrophysics, University of Chicago

  2004

• Other

  Dept. of Astronomy and Astrophysics, University of Chicago

  2004

Awards & honors

• Fellow, American Physical Society